BookPDF Available

Riding the wave How Europe can gain from the rising tide of scientific data Final report of the High Level Expert Group on Scientific Data A submission to the European Commission

January 2010

January 2010

Publisher: European Commission

Authors:

Los Consultancy

The report of a high-level advisory group is presenting its view on the future of scientific data and of an emerging data infrastructure.

Content uploaded by Wouter Los

Content may be subject to copyright.

Riding the wave

How Europe can gain from the rising tide of scientiﬁc data

Final report of the High Level Expert Group on Scientic Data

A submission to the European Commission

October 2010

Reproduction is authorised provided the source is acknowledged.

The views expressed in this report are those of the authors and do not

necessarily reﬂect the oﬃcial European Commission's view on the subject.

Printed by Osmotica.it

The members of the HLG would like to thank the project GRDI2020 for supporting the meetings

logistics and the arrangements for the publication of the ﬁnal report. GRDI2020 is a coordination

action project funded by the European Seventh Framework Programme for Research and

Development (FP7) under Grant Agreement RI-246682.

Riding the wave

How Europe can gain from the rising tide of scientiﬁc data

Final report of the High level Expert Group on Scientic Data

A submission to the European Commission

October 2010

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

he Digital Agenda for Europe outlines policies

and actions to maximise the benefit of the

digital revolution for all. Supporting research

and innovation is a key priority of the Agenda,

essential if we want to establish a flourishing digital

economy by 2020.

Scientific research is supported by its infrastructures:

technical tools and instruments and socio-economic

systems for organising and sharing knowledge.

These have been in constant change for many

centuries reflecting advances in technology and

change in political systems. Key inventions like the

microscope or the telescope resulted in huge

scientific progress by allowing the validation or

rejection of theories; and the invention of book

printing in the 15th century and the organisation of

knowledge in research libraries allowed

unprecedented access to knowledge.

Information and Communication Technologies (ICT)

are the most recent transformational factors in

science. They enable close and almost instantaneous

collaboration between scientists all over the world

and they provide access to unprecedented volumes

of scientific information that can in turn be

processed on powerful computational platforms.

Many younger scientific disciplines would not even

Unlocking the full value of scientific data

“Information and

Communication

Technologies (ICT) are

the most recent

transformational factors

in science. “

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

exist without access to these technologies. Today ICT-

based infrastructures (e-infrastructures) have

become an essential foundation of all research and

innovation.

This is reflected in the European Commission and EU

Member States investing in different domains of e-

infrastructures. Together we have been working on

connecting researchers, scholars, educators and

students through high speed research networks like

GÉANT, providing access to shared grid and cloud

computing facilities, and developing

supercomputing capacity for very demanding

applications through the European partnership

PRACE. To complement these developments, Europe

is putting the seeds for the emergence of a robust

platform for access and preservation of scientific

information.

All these are and will remain important elements

underpinning European research and innovation

policies. However, with robust infrastructure for data

transmission and data processing in place, we can

now start to think about the next step: data itself. My

vision is a scientific community that does not waste

resources on recreating data that have already been

produced, in particular if public money has helped

to collect those data in the first place. Scientists

should be able to concentrate on the best ways to

make use of data. Data become an infrastructure

that scientists can use on their way to new frontiers.

Making this a reality is a more difficult task than it

may seem. To collect, curate, preserve and make

available ever-increasing amounts of scientific data,

new types of infrastructures will be needed. The

potential benefits are enormous but the same is

true for the costs. We therefore need to lay the right

foundations and the sooner we start the better. This

report of the High-Level Group on Scientific Data

will be an invaluable input for formulating our

research and research-infrastructure policies. I invite

every citizen and every organisation involved in

scientific research to take note of this report and to

use it as a reference point when discussing the

priorities of EU research investments.

Neelie Kroes

Vice-President of the European Commission,

responsible for the Digital Agenda

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

F ROM T H E CHAIR

On the challenges ahead

present the report of the High Level Group on the future of scientific data. The

importance of facing up to the challenges before us is crucial if European

research is to remain at the leading edge globally.

The resulting actions that we propose will affect all areas of research, not just big

science. This range has been reflected in the group as we have considered the

impact on, for example, the humanities, publishing, and bio-diversity in addition

to large international science facilities. Indeed, getting it right will affect the way

research is done in the future and will be instrumental in ensuring that the

challenges before us are solved in a holistic way rather than allowing individual

disciplines to dig entrenched positions. Just how students will be trained in the

future, or how the profession of “data scientist” will be developed, are among the

questions the resolution of which is still evolving and will present intellectual

challenges for both privately and publicly supported research. Critical to

everything is how trust can not only be fostered but ensured so that the “Fifth

Freedom of Knowledge” is pursued with vigour for the good of all society.

In addition to the High Level Group coming from a diversity of backgrounds, the

liveliness of the discussions and the working atmosphere have been a delight and

I thank the members for their excellent contributions. Also my thanks to the

Commission staff who have entered into the debate with an exemplary degree of

open-mindedness. Finally I would like to acknowledge the assistance of the

various people who came to the group to share their thoughts and experience

with us from around the world, to rapporteur David Giaretta who brought the

discussions together into a coherent structure and action plan, and to Richard

Hudson who miraculously took our stream of consciousness ideas and turned

them into a coherent report.

John Wood

Chair

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

E X E C U T I V E S U M M A R Y

fundamental characteristic of our age is the

rising tide of data – global, diverse, valuable

and complex. In the realm of science, this is

both an opportunity and a challenge. This report,

prepared for the European Commission’s

Directorate-General for Information Society and

Media, identifies the benefits and costs of

accelerating the development of a fully functional e-

infrastructure for scientific data – a system already

emerging piecemeal and spontaneously across the

globe, but now in need of a far-seeing, global

framework. The outcome will be a vital scientific

asset: flexible, reliable, efficient, cross-disciplinary

and cross-border.

The benefits are broad. With a proper scientific e-

infrastructure, researchers in different domains can

collaborate on the same data set, finding new

insights. They can share a data set easily across the

globe, but also protect its integrity and ownership.

They can use, re-use and combine data, increasing

productivity. They can more easily solve today’s

Grand Challenges, such as climate change and

energy supply. Indeed, they can engage in whole

new forms of scientific inquiry, made possible by

the unimaginable power of the e-infrastructure to

find correlations, draw inferences and trade ideas

and information at a scale we are only beginning to

see. For society as a whole, this is beneficial. It

empowers amateurs to contribute more easily to

the scientific process, politicians to govern more

effectively with solid evidence, and the European

and global economy to expand.

But there are many challenges. How can we

organise such a fiendishly complicated global effort,

without hindering its flexibility and openness? How

do we incentivise researchers, companies, and

individuals to contribute their own data to the

e-infrastructure – while still trusting that they can

protect their privacy or ownership? How can we

manage to preserve all this data, despite changing

technologies and needs? How to convey the context

and provenance of the data? How to pay for it all?

Our vision is a scientific e-infrastructure that

supports seamless access, use, re-use, and trust of

data. In a sense, the physical and technical

infrastructure becomes invisible and the data

themselves become the infrastructure – a valuable

asset, on which science, technology, the economy

and society can advance. Our vision is that, by 2030:

■ All stakeholders, from scientists to national

authorities to the general public, are aware of the

critical importance of conserving and sharing

reliable data produced during the scientific

process.

■ Researchers and practitioners from any discipline

are able to find, access and process the data they

need. They can be confident in their ability to use

and understand data, and they can evaluate the

degree to which that data can be trusted.

■ Producers of data benefit from opening it to

broad access, and prefer to deposit their data

with confidence in reliable repositories. A

framework of repositories work to international

standards, to ensure they are trustworthy.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

■ Public funding rises, because funding bodies

have confidence that their investments in

research are paying back extra dividends to

society, through increased use and re-use of

publicly generated data.

■ The innovative power of industry and enterprise

is harnessed by clear and efficient arrangements

for exchange of data between private and public

sectors, allowing appropriate returns to both.

■ The public has access to and can make creative

use of the huge amount of data available; it can

also contribute to the data store and enrich it. All

can be adequately educated and prepared to

benefit from this abundance of information.

■ Policy makers are able to make decisions based

on solid evidence, and can monitor the impacts

of these decisions. Government becomes more

trustworthy.

■ Global governance promotes international trust

and interoperability.

There is a clear role for government in all this; and

we offer a short-list of action by various EU

institutions – building on work already begun across

the EU in recent years, and complementing efforts in

the US, Japan and elsewhere in the world.

1. Develop an international framework for a

Collaborative Data Infrastructure

The emerging infrastructure for scientific data must

be flexible but reliable, secure yet open, local and

global, affordable yet high-performance. There is no

one technology that can achieve it all. So we need a

broad, conceptual framework for how different

companies, institutes, universities, governments and

individuals would interact with the system. We call

this framework a Collaborative Data Infrastructure,

and we urge the European Commission to accelerate

efforts – in Europe and around the globe – to make it

real.

2. Earmark additional funds for scientific e-

infrastructure

Development of e-infrastructure for scientific data

will cost money, obviously – and as there is a

significant element of public good in this, so there

must be a significant degree of public support. One

obvious source is found in the EU’s Structural Funds

– a portion of the budget mostly used to build roads,

industrial parks and other key infrastructure,

targeted at those regions of Europe most in need.

Already, a portion of this budget is earmarked for

research and innovation, including digital

infrastructure. We call upon the European Council to

expand the funding possibilities.

3. Develop and use new ways to measure

data value, and reward those who

contribute it

If we are to encourage broader use, and re-use, of

scientific data we need more, better ways to

measure its impact and quality. We urge the

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

European Commission to lead the study of how to

create meaningful metrics, in collaboration with the

‘power users’ in industry and academia, and in

cooperation with international bodies.

4. Train a new generation of data scientists,

and broaden public understanding

We urge that the European Commission promote,

and the member-states adopt, new policies to foster

the development of advanced-degree programmes

at our major universities for the emerging field of

data scientist. We also urge the member-states to

include data management and governance

considerations in the curricula of their secondary

schools, as part of the IT familiarisation programmes

that are becoming common in European education.

5. Create incentives for green technologies

in the data infrastructure

Computers use energy; and as the tide of scientific

data rises further the energy consumption risks rising

in tandem. We urge the European institutions, as

they review plans for CO2 management and energy

efficiency, to consider the impact of e-infrastructure

and prepare policies now that will ensure we have

the necessary resources to perform science.

6. Establish a high-level, inter-ministerial

group on a global level to plan for data

infrastructure

It makes no sense for one country or region to act

alone. We urge the European Commission to identify

a group of international representatives who could

meet regularly to discuss the global governance of

scientific e-infrastructure. It should also host the first

such meeting.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

e all experience it: a rising tide of information, sweeping across our

professions, our families, our globe. We create it, transmit it, store it,

receive it, consume it – and then, often, reprocess it to start the cycle

all over again. It gives us power unprecedented in human history to understand

and control our world. But, equally, it challenges our institutions, upsets our

work habits and imposes unpredictable stresses upon our lives and societies.

Science is both producer and consumer of this data– and we urgently call on our

political leaders to grasp the opportunities it creates. Success can create

economic growth and a fairer, happier society. Failure will undermine Europe’s

competitiveness and endanger social progress. Knowledge is power; Europe

must manage the digital assets its researchers generate.

Science has a pivotal role in this phenomenon, and this report focuses on the

infrastructure needed to manage scientific data. Our purpose is to provide a

vision and action plan.

Why the focus on scientific data?

For starters, science is a cause of this data wave. Scientific discovery led to the

microprocessors, optical fibres and storage media with which we create, move

and store the data. And the continuing process of scientific discovery – in all

disciplines from astronomy to economics – is generating a growing share of that

new data. In one day, a high-throughput DNA-sequencing machine can read

about 26 billion characters of the human genetic code. That translates into 9

terabytes – or 9 trillion data units – in the course of one year; alongside it is a

wealth of related information that can be 20 times more voluminous. The total

data flow: more than 20 new US Libraries of Congress each and every year. That

is from one specialised instrument, in one scientific sub-discipline; enlarge that

picture across all of science, across the world, and you start to see the dimension

of the opportunity and challenge presented.

Most importantly, however, our focus is on scientific data because, when the

information is so abundant, the very nature of research starts to change. A

I. Riding the wave

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

feedback loop between researchers and research results changes the pace and

direction of discovery. The “virtual lab” is already real, with the ability to

undertake experiments on large instruments in other continents remotely in real

time. Researchers with widely different backgrounds - from the humanities and

social sciences to the physical, biological and engineering sciences – can

collaborate on the same set of data from different perspectives. Indeed, we begin

to see what some

have called a “fourth paradigm” of science – beyond

observation, theory and simulation, and into a new realm of exploration driven

by mining new insights from vast, diverse data sets. For the first time, large-scale

and complex “whole body” solutions become possible for some of society’s

Grand Challenges of energy and water supply, global warming, and healthcare.

Just how will we train people to work in this environment? What tools will we

need to move, store, preserve and mine these data? How to share them? How to

understand them, if you are in a different scientific discipline than that in which

they were created? As a researcher, how will you know the data you access on

another continent are accurate, uncorrupted and unbiased? What if those data

include personal details – individual health records, financial information or

Internet habits? These are just a few of the profound policy questions posed by

this new age of data-intensive science.

Nowhere in the world are these questions adequately addressed. But we believe

Europe has a special responsibility to lead, rather than to react, in this domain.

The European Research Area – despite its oft-noted difficulties – remains today

one of the top three scientific powers of the world, and if measured by the

number of published scientific papers alone, it out-produces the US and Japan; it

thus contributes more than its fair share to the scientific data tide. But that also

means it has unique skills to address the challenges, through the strength of its

best research institutions, the diversity of its technical talent, and the unique

ability of its researchers to collaborate across borders, industries and disciplines.

Throughout human history, the interrelation between science and the

technology for recording it has been deep and productive. In the ninth century,

the spread of paper underpinned the Golden Age of Islamic science, as Greek

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

and Roman works of science were translated and then superseded. From the

15th century onward, the printing press permitted scholarship to travel far and

wide – so a Copernicus could more easily influence a Galileo. In just the past 60

years we have seen information and communications technologies applied to

such diverse fields as reaching the moon, harnessing nuclear energy and

beginning to control cancer.

In this report we are not trying to second-guess the future; it will certainly be

different from anything we can imagine now. But what we can do is to push for

the difficult policy questions to be addressed, so that important options are not

closed off and the science done today will be available to researchers tomorrow.

We point to a pathway that is ‘technology-neutral’ – based on concepts broad

enough to embrace whatever new forms of information and communications

technologies we develop over the next generation. This requires developing

principles for interoperability (technical, semantic, legal, and ethical), verification

and reliability – at local, regional and global scale. It requires new incentives for

sharing and protecting data of different types, whether that data is precious and

guarded or abundant and open. And it requires a framework to review all these

principles at regular intervals.

The European Union has an important, coordinating role in achieving this vision

– through its Digital Agenda, its Framework Programme and the policies

embodied in its European Research Area initiatives. Equally, there is the

opportunity for the EU institutions to lead in creating a common, world-wide

vision. The EU Competitiveness Council of late 2009

called on the European

Commission to address the issue of e-infrastructure for science, and this High

Level Group is part of that effort. As we publish this report, the product of six

months of collective thought and research, we now call on the EU institutions to

move beyond study and into action.

We are on the verge of a great new leap in scientific capability, fuelled by data.

We have a vision of how Europe could benefit rather than suffer, lead rather than

follow. But we urge speed. We must learn to ride the data wave.

Keep constantly in

mind in how many

things you yourself

have witnessed

changes already.

The universe is

change, life is

understanding.

Marcus Aurelius,

121-180

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

“We humans have built a creativity machine. It’s the sum of three

things: a few hundred million computers, a communication system

connecting those computers, and some millions of human beings

using those computers and communications”

Vernor Vinge

e live in the Information Age; and nowhere is that name more apt than

in science and technology. Technical information in all forms, whether

statistics, images, formulae or know-how in the broadest sense of the

term, has already transformed our view of the world – and much more is yet to

come. A few examples, to sketch out the possibilities ahead:

■ Currently, about 2.5 petabytes – more than a million, billion data units – are

stored away each year for mammogrammes in the US alone.

World-wide,

some estimate, medical images of all kinds will soon amount to 30% of all

data storage.

These could be a goldmine of data for epidemiological and

drug research, if made accessible in appropriately anonymised form to

researchers.

■ ‘Smart meters’ for electricity consumption, now being installed in many EU

countries, produce the equivalent of one CD-ROM of data for each household

every year. Scale that up to 100 million households, and you have a vast

repository of data for economic and behavioural analysis of people’s energy

consumption.

■ Astronomy is a well-recognised ‘power user’ of data – but we are barely at the

start of this trend. From 2020, the Square Kilometre Array, a new international

radio telescope on the drawing board, could generate 1 petabyte of data

every 20 seconds – a fire-hose of numbers requiring unimaginable

processing power.

Yet that data will push the limits of the observable

universe out by billions of galaxies, perhaps back to the first moments after

the Big Bang.

II. Welcome to the data world

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

■ This century opened with the first “reading” of the human genome. By August

2009, digital records on more than 250 billion DNA bases, from various

species, were stored in the US government’s public GenBank database

and an

entirely new discipline of science had emerged: systems biology. This uses

computers to simulate, at the sub-molecular level, exactly how DNA, proteins

and the other chemical components of life interact – and in time, it will

transform the practice of health sciences. “Organisms function in an

integrated manner...but biologists have historically studied (them) part by

part,” said Nobel Laureate David Baltimore. Systems biology “ is a critical

science of the future that seeks to understand the integration of the pieces to

form biological systems”.

As these examples suggest, the increase in scientific data isn’t simply a question

of more information, more storage disks and more optical pipes to move it all –

though that is certainly part of it. It is more profound than that: it changes the

way we do our science, and opens entirely new fields of research.

And these new fields require, from the start, an international effort. One current

project, 1000 Genomes

, is comparing the complete DNA sequences of more

than 1,000 individuals from around the world to define what makes us different

from one another – an inquiry with at least as many humanistic as scientific

overtones. Geographical information systems, popularised in Google Maps, are

changing the way we study economic, agricultural and demographic trends

world-wide. And the global Internet offers an extraordinary new tool for

behavioural research. Epidemiologists have studied the frequency with which

people search online for keywords such as ‘flu’, as a way to monitor disease

spread. Other researchers, trying to understand how people would react to

pandemic alerts, have looked at the way online gamers in ‘World of Warcraft’

congregate around the digital equivalent of disaster zones, as a clue to new

disease-control strategies.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

But it is not just what is studied, but also who studies it and how, that is affected

by the data tide. For the first time in two centuries of growing

professionalisation in science, new ICT tools allow the increasing involvement of

amateurs; there are simply too many observations required for the professionals

to do it all on their own. An example is GalaxyZoo, a Web portal through which

amateurs help astronomers explore the Universe.

Biodiversity monitoring

depends to a large extent on the power of observations by tens of thousands of

volunteers who send their notes on species in defined areas to a central data

repository.

For instance, the Swedish Species Gateway provides a navigable

visual interface linked to geographical information systems.

These examples

represent an important social and political trend. Empowering informed ‘citizen-

scientists’ will also empower science.

Where will this lead? Consider five diverse scenarios that we believe to be

entirely possible in coming decades.

Right: In Grenoble, the

European Synchrotron

Radiation Facility is a super-

microscope studying

anything from the

propagation of cracks in

steel to the surface proteins

on the influenza virus. In the

decade to 2007, its annual

data output rose more than

a hundred-fold. And it is just

one of about 50

synchrotrons world-wide.

Left: After a long, slow rise

since 1986, the volume of

earth-observation data

from the European Space

Agency’s satellites passed

three petabytes in 2007 –

three million, billion bytes.

The projection for 2020: A

seven-fold rise.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Scenario I: Science and data management

Marie is working in a genomics project linking

twelve large labs over four continents. The task of

data management is intense. A group from China is

preparing to feed its data into the consortium’s

processing pipeline. At the same time, the project’s

accounting system shows two research efforts

elsewhere are behind schedule due to a microscope

producing sub-standard data; the data flow from

that machine is automatically blocked from the

system. Some of Marie’s graduate students,

meanwhile, are trying to verify recently published

results from a competing group of researchers - but

their own lab equipment is different, so the work-

plan needs to be modified. Next issue: A meeting

with lawyers over a dispute between two of the

research consortium’s members. There is an

argument over who controls what data before and

after processing of the group’s research results. Until

it is settled, the data bank is holding all the files in

escrow.

Scenario II: Science and the citizen

Carlos likes bugs. He watches them the way a bird-

lover tracks Canada geese – and he feeds his

observations into a system for professionals to

analyse. Out walking in a field one day, he spots

something interesting – an insect species in an

unexpected place. He queries the remote database

for any relevant information that could explain it,

and then checks in with his fellow amateurs. Their

hypothesis: The insect may have changed its food

preference to a different plant species. But why?

Carlos posts his observation; and in the coming

days other enthusiasts are watching for a similar

anomaly. The system automatically analyses their

observations, asks them more questions, and

checks for incorrect information. It also looks for

correlations with other databases – weather

patterns, soil conditions, maps of flora distribution.

This wealth of observation allows a professional

entomologist to test his hypothesis on ‘preferred

attractors in chaotic ecological processes.’ Carlos is

acknowledged in the resulting open-access

publication.

S C E N A R I O S O F T H E F U T U R E

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Scenario III: Science and the data set

Anneli has a grant under which she is allowed free

access to 10 years of measurements by the global

cell-phone sensor network, stored in cross-

continental archives. This network uses the

miniature sensors standard in cell phones to

monitor local temperature, air quality, wind speed,

light intensity, noise levels and other parameters –

and links it to GPS information. The information is all

kept in regional archives, with open interfaces so

researchers can query them uniformly. With her

team, Anneli wants to investigate correlations

between the environment and the spread of illness

– and for the disease information, she is looking at

anonymised, geo-tagged messages sent by people

mentioning the disease. She intends to clean the

resulting data set and make it publicly available via

her university’s institutional repository. From there, it

could become the scientific equivalent of a Top-40

song – played by others around the world. Her

chances for tenure rise.

Scenario IV: Science and the student

Roger is working on an international PhD. It’s a

relatively new programme, in which a student

applies to become a member of an international

team working on a big problem that affects all

people. His group is comparing many forms of non-

verbal communications between cultures. It has

several hundred members and his university tutor

is one of the nodal points contributing expertise in

‘synergistic communication between biological

components.’ Others in the network are using

archaeological evidence to study communications

between ancient Mesopotamian and Hellenic

cultures; some are studying computer-computer

interactions between different systems; yet more

are studying communications in refugee camps.

Each node contributes to the whole. Results are

communicated as they happen, and there are daily,

virtual-presence planning sessions. Roger had to

sign a contract not to misuse data or contribute

anything that is not for the common good – such as

externally sourced information that he has not

thoroughly checked for provenance.

S C E N A R I O S O F T H E F U T U R E

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Are these five scenarios fantastical? Not at all. There are already hundreds of

projects, in the EU and elsewhere, that are precursors to the features described in

these scenarios.

For example:

■ The European Space Agency, recognising the importance of its satellite data

for climate-change research, has launched a Long-Term Data Preservation

programme that merges all earth observation data from across Europe

. At

the same time, the EU’s GENESI-DR project is creating a grid-based computing

system for accessing and processing the huge amount of earth observation

data which will become available. Both use fundamental results from the

CASPAR EU project on how to preserve digitally encoded information.

■ Humanities researchers are creating CLARIN, a system to establish an

integrated and interoperable research infrastructure of language resources

and tools. In doing so, they are already tackling proper data management as a

key dimension of the system for the scholarly community.

■ Astronomers around the world are creating the International Virtual

Observatory to allow researchers everywhere to access and use data from

hundreds of astronomical data sources. Also to be included are results of

computer modelling and simulation – for it is not just raw observations that

are the business of modern astronomy, but also the models built from them.

■ As part of Framework Programme 7, the European Commission and EU

member-states are investing in a broad range of e-infrastructure projects. The

GEANT research-data network, for instance, connects over 40 million users,

8,000 institutions and 40 countries.

Other projects provide access to

cooperative grid-computing platforms, develop supercomputing capacity,

and lay the groundwork for the access and preservation of scientific

information.

So, if this be dreaming, it is done with eyes wide open. But there remain many

challenges to address, as well.

Scenario V: Science and data-sharing

incentives

Hans, rooting in the basement one day, finds an

old laptop with a video of Grandpa on a boat. He

is a young man in the video, wearing a diving

costume. In the background is a marvellous

beach. The video goes on to show underwater

scenes with bizarre fish and colourful coral. The

video is entertaining – but where was it made?

Hans can get the answer in a few minutes. He

goes online to a centralised mapping service, to

which he uploads parts of the video. The service

has smart pattern-matching algorithms, using

huge reference collections. Soon, different

mapping probabilities for the video fragments

are returned, pointing out the most probable

area where the video could have been made: The

Maldives, before global warming drowned them.

This is a bit of personal trivia for Hans, but a new

data set for science. So there is a price for the

service: Hans must let his video fragments stay in

the central database, enriching it further and

making it even more useful – for professional

scientists, too.

The future of e-infrastructure for scientific data is

bright - and already, extensive work is underway

to make it a reality.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

ertainly, creating a scientific world based on e-infrastructures will not be

easy. For starters, it is technically difficult. The scale and complexity of

this global scientific asset – with all its sensors, instruments, workstations

and networks – are truly massive. There are many planning pitfalls, common to

all large infrastructure projects. There can be ‘choke points’: technical or

industrial problems that, if unrecognised, stop the show. People can get locked

into sub-optimal technologies; think of the QWERTY/AZERTY computer

keyboard, with its inefficient but now immutable layout. Gateways, originally

created to join disparate systems, can later become barriers to progress in

themselves. Short-term funding decisions can undermine the system’s longer-

term development. What works best for a local user could hamper global

functions.

The list of pitfalls is long. Success requires careful, coordinated and agile

planning, on a global as well as EU level. E-infrastructure for science is one area

where fragmentation of effort is more than inconvenient or inefficient; it is

inimical. But the technical issues are only the beginning of the challenges to be

overcome. Consider:

■ How will we preserve the data? As we all have seen, the media in which we

store information change constantly – from magnetic coils, to tape, to disk,

to USB key, to ‘cloud’ storage, and so on in an endless chain of invention and

obsolescence. What will be the point of storing all this scientific data if, a

century from now, it has degraded, been corrupted, or is simply too difficult

for anyone but a well-equipped expert to use?

■ How will we protect the integrity of the data? Even today, it is easy for a

determined individual to alter or corrupt digital data (think of the constant

controversy over Wikipedia entries.) As the data tide rises higher, how will we

detect unauthorised alterations? Should every researcher, and indeed every

citizen, have access to the data repositories? Should there be different levels

of access allowed?

■ How will we convey the context and provenance of the data? Given the

emerging trend to make all publicly funded research data publicly available,

just how will users from a wide range of backgrounds understand and query

III. Facing up to the challenges

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

the data they are accessing, and recognise the special circumstances under

which it was collected? Already, in medical research, potentially fatal errors

can arise by researchers inadvertently misinterpreting the drug-trial data

collected by others; so-called ‘meta-analysis,’ to manage such complexities, is

far from a certain science.

■ How will we pay for all this? What new funding and business models will we

need, so that everyone – researchers, enterprises, citizens – have adequate

incentive to contribute to the data infrastructure? What kinds of data, under

what circumstances, should be free?

■ How will we protect the privacy of individuals linked to the data? We have

already seen how easy it is for supposedly safeguarded data – whether tax

files or health records – to be lost or misused. On one hand, access to this data

is vital to researchers studying the economy or public health. On the other

hand, carelessness in handling the data compromises our safety and security.

How will we resolve this paradox?

Many of these issues involve trust. Data-intensive science operates at a distance

and in a distributed way, often among people who have never met, never

spoken, and, sometimes, never communicated directly in any form whatsoever.

They must share results, opinions and data as if they were in the same room. But

in truth, they have no real way of knowing for sure if, on the other end of the line,

they will find man or machine, collaborator or competitor, reliable partner or

con-artist, careful archivist or data slob. And those problems concern merely the

scientific community; what about when we add a wider population? Many fields

require the public to cooperate in supplying data (wittingly or not). How will we

judge the reliability and authenticity of data that moves from a personal archive

into a common scientific repository? If science is to advance, all these questions

of trust must be answered by the infrastructure, itself.

In dealing with many of these issues, we believe a few broad principles arise:

Data as infrastructure

Our stock of intangible knowledge, expanding at today’s hyper-speeds, needs to

be thought of as a new kind of asset in itself, that serves all. As such, it requires

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

professional analysis and engineering. Its contents are heterogeneous –

different data formats, value and uses. There is tremendous value in having the

data made seamlessly available, to use, reuse and recombine to support the

creation of new knowledge. And the data must be available to whomever,

whenever and wherever needed, yet still be protected if necessary by a range of

constraints including by-attribution licenses, commercial license, time

embargos, or institutional affiliation.

A data pyramid (below) suggests the complex data ecology. At the bottom of

the pyramid lie the most abundant, transient forms of data – billions of personal

data files across the planet, on private disks and storage services, of obvious

value only to the few who create or use them. At the top of the pyramid is

patrimonial data – high-value, irreplaceable data of importance to an entire

nation or society, redundantly stored in national or international trusted

archives. In the middle is cyclic data – a mid-range of data created and used in a

specific task, community or region. The new data infrastructure must cope with

all these data classes.

Source: Adapted from Francine Berman, UC San Diego, in Communications of the ACM.

Respositories/

Facilities

National- and

international-scale

respositories,

libraries, archives

“Regional” - scale

libraries and

targeted data

archives and

centers

Private

respositories

Digital Data

Collections

Reference,

nationally and

internationally

important,

irreplaceable

data collections

Key research and

community data

collections

Personal data

collections

Societal

Value

Patrimonial Data

Community

Value

Cyclic Data

Individual

Value

Transient Data

The data pyramid - a hierarchy of rising value and permanence

Increasing

constituency

Increasing

value

Increasing

trust

decreasing

risk of loss

or damage

Increasing

responsibility

Increasing

stability

Increasing

infrastructure

aramid - a hieryrta phe daT

eencerefR

tionsollecC

taigital DaD

alue

ermanencalue and py of rising vchar

Value

ocietalS

tional- andNa

acilitiesF

ories/osit

Resp

tionsollecc

taersonal daP

tions ollecc

tay daommunitc

ch andesearKey r

tions

ollec

ctions

ta cda

eableeplacrir

,ttanimpor

tionallynaertin

tionally andna

, in C

Comm

iegoan Derman, UC S

ancine B

rancine B

om F

ed fr

dapt

ted fr

e: A

our

t DaansienrT

alue

Value

ndividualI

clic Da

yclic Da

alue

Value

yommunitC

trimonial DaaP

alue

Value

CM.

ations of the Aunicomm

iesorespositr

evatirP

ers tenc

es andchivar

taed dagettar

ies and arlibr

- scale ”ionaleg“R

eschiv, ariesarlibr

,iesorespositr

tional-scalenaert

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Interoperability

Diversity is a dominant feature of scientific information – diversity of data

formats and types, but also of the people and communities that generate and

use the data. Even within the same scientific community, there are different

points of view, different ways of analysing, sharing and handling data. There is

also diversity in how the data are stored, categorised and mapped. There is

diversity in who can access what kinds of data, and how – from tightly protected

military satellite images to freely accessible Google Earth views. And as science

advances, diversity is bound to increase.

Achieving an interoperable data infrastructure in the midst of such

heterogeneity is a significant challenge. None of the potential benefits of the

scientific data wave will be harnessed unless – given the proper access rights – it

is easy and cheap to rummage through relevant data files anywhere in the world,

in any field. An epidemiologist in Geneva studying the latest flu virus will benefit

greatly from being able to tap easily into DNA databases in London of 1918

Spanish Flu victims – and the epidemiologist’s work should be accessible to a

public health official in Hong Kong, a systems biologist in San Diego and a

medical historian in Boston. That’s all possible today, but with great effort, skill,

cost and time. A leap forward in interoperability will change that.

Incentives

How can we get researchers – or individuals – to contribute to the global data

set? Only if the data infrastructure becomes representative of the work of all

researchers will it be useful; and for that, a great many scientists and citizens will

have to decide it is worth their while to share their data, within the constraints

they set. To start with, this will require that they trust the system to preserve,

protect and manage access to their data; an incentive can be the hope of gain

from others’ data, without fear of losing their own data. But for more valuable

information, more direct incentives will be needed – from career advancement,

to reputation to cash. Devising the right incentives will force changes in how our

universities are governed and companies organised. This is social engineering,

not to be undertaken haphazardly.

Financial models

All of this costs money – so who pays, and how? To a considerable extent,

scientific e-infrastructure represents a public good. It is vital that governments

and taxpayers step in to provide the critical funding in those instances. Our data

future will look bleak if the public sector under-invests. Of course, there is private

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

■ Open deposit, allowing user-community centres to store data easily

■ Bit-stream preservation, ensuring that data authenticity will be guaranteed

for a specified number of years

■ Format and content migration, executing CPU-intensive transformations on

large data sets at the command of the communities

■ Persistent identification, allowing data centres to register a huge amount of

markers to track the origins and characteristics of the information

■ Metadata support to allow effective management, use and understanding

■ Maintaining proper access rights as the basis of all trust

■ A variety of access and curation services that will vary between scientific

disciplines and over time

■ Execution services that allow a large group of researchers to operate on the

stored date

■ High reliability, so researchers can count on its availability

■ Regular quality assessment to ensure adherence to all agreements

■ Distributed and collaborative authentication, authorisation and accounting

■ A high degree of interoperability at format and semantic level

Adapted from the PARADE White Paper at http://www.csc.fi/english/pages/parade/

Scientific e-infrastructure – a wish list

The ideal data

infrastructure for

science will have a

long list of

technical

characteristics.

Here are some

suggestions.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

gain as well. When a government laboratory contributes its raw research data to

the global e-infrastructure, it is certainly saving private users the expense of

running those experiments on their own. Equally, when a private company

contributes its own files to the system, it also helps the public researchers. It is

important to devise funding mechanisms that enable all to contribute as well as

to benefit, through an increased return on investment.

These issues can be resolved. We have experience of past changes in how we

store, share and manage valuable assets. As the technology of food and

transport evolved, society moved from self-supporting farmers to town markets,

and from markets to a range of supermarkets and specialty shops. In finance, we

moved from private hoards to communal banks to international markets. The

same path from individual control to international exchange must be trodden

by data – indeed, it is already happening.

It is important to devise funding mechanisms that

enable all to contribute as well as to benefit,

through an increased return on investment.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Collection How can we make sure that data are collected together with the information necessary to re-

use them?

Trust How can we make informed judgements about whether certain data are authentic and can be

trusted?

How can we judge which repositories we can trust? How can appropriate access and use of

resources be granted or controlled?

Usability How can we move to a situation where non-specialists can overcome the high barriers to their

being able to start sensible work on unfamiliar data, perhaps using intelligent automated tools

for an initial investigation?

Interoperability How can we implement interoperability within disciplines and move to an overarching multi-

disciplinary way of understanding and using data?

How can we find unfamiliar but relevant data resources beyond simple keyword searches, but

involving a deeper probing into the data?

How can automated tools find the information needed to tackle unfamiliar data?

Diversity How do we overcome the problems of diversity – heterogeneity of data, but also of

backgrounds and data-sharing cultures in the scientific community?

How do we deal with the diversity of data repositories and access rules – within or between

disciplines, and within or across national borders?

Security How can we guarantee data integrity?

How can we avoid data poisoning by individuals or groups intending to bias them in

theirinterest?

How can we react in the case of security breaches to limit their impact?

Scientific e-infrastructure – some challenges to overcome

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Education and training How can the citizen make these benefits available for sensible investigations, and how can they

be safeguarded from fakes?

How can scientific e-infrastructure foster and increase popular interest and trust in science?

How can we foster the training of more data scientists and data librarians, as important

professions in their own right?

Data publication and access How can data producers be rewarded for publishing data?

How can we know who has deposited what data and who is re-using them – or who has the

right to access data which are restricted in some way?

How do we deal with the various ‘filters’ that different disciplines use when choosing and

describing data? What about differences in these attitudes within disciplines, or from one time

to another?

Commercial exploitation How can the infrastructure benefit from commercial developments in data management?

How can the revenue-generating expertise of the commercial world be brought into play for

the long-term sustainability of these resources?

New social paradigms How can we learn from the wisdom of crowds about what and whom to trust, while avoiding

being misled by concerted campaigns of deceit?

Preservation and Sustainability How can we be sure that the important information we collect will be usable and

understandable in the future; in particular how can we fund our information resources in the

long term?

How can we share the costs and efforts required for sustainability?

How can we decide what to preserve?

Scientific e-infrastructure – some challenges to overcome continued

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

he creation of scientific e-infrastructure is a means, not an end. It is a

means to new science, new solutions and new progress in society. We

cannot predict what the world will be like in 2030, but we can state some

broad principles of what it should be like if scientific e-infrastructure is by then

the major contributor to society, the economy and science that we expect it to

be. All of these principles – our vision - point in the direction of an infrastructure

that supports seamless access, use, reuse, and trust of data. It suggests a future in

which the data infrastructure becomes invisible, and the data themselves have

become infrastructure – a valuable asset, on which science, technology, the

economy and society can advance. We will know we are well on our way to

realising this vision when we see the following milestones achieved:

1. All stakeholders, from scientists to national authorities to the

general public, are aware of the critical importance of conserving

and sharing reliable data produced during the scientific process.

This may sound obvious – but it is by no means so.

Today we see the relative

priorities of society in constant flux on the Internet and other electronic media. In

a world of limited resources, how urgent is a packet of scientific data compared to

home videos? How much is it worth to create reliable back-up and storage

systems for what may seem today like transient chat messages, but could

tomorrow become vital behavioural or epidemiological data? Thus, the first task is

simply to get the message out that scientific e-infrastructure is important to

society.

Expected impact: The intellectual capital of Europe is used to generate

economic and scientific advances now, and that capital is safely preserved for

further exploitation by future generations.

Risk of Inaction: Resources for funding take a back seat to more pressing

concerns, and data decays through neglect. When critical data – whether about

climate, new medicines or historic monuments – are needed later on, it will be

too late.

IV. A vision for 2030

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

2. Researchers and practitioners from any discipline are able to find,

access and process the data they need. They can be confident in

their ability to use and understand data, and they can evaluate

the degree to which that data can be trusted.

Expected impact: Researchers can today access online sources, but it is a small

fraction of all data produced. In future, the breadth and depth of data available

to them will grow dramatically, whether their discipline is demographics, ocean

chemistry, high-energy physics or astronomy. Scientists’ efficiency and

productivity will rise because they know they can access, use, reuse and trust the

data they find. Inspiration or serendipity can lead to unexpected results. Cross-

fertilisation of ideas and disciplines will produce novel solutions, and promote

greater understanding of complex problems.

Risk of Inaction: As the volume and diversity of scientific data increase, and as

research becomes more multi-disciplinary, researchers struggle to understand

and correlate data – especially if from another field. They may not find the data at

all. Or if they find it, they are not sure it is what it claims to be. As a result,

researchers become increasingly isolated, narrow specialists; wide-ranging,

serendipitous results become more difficult.

3. Producers of data benefit from opening it to broad access, and

prefer to deposit their data with confidence in reliable

repositories. A framework of repositories is guided by

international standards, to ensure they are trustworthy.

Expected impact: Researchers are rewarded, by enhanced professional

reputation at the very least, for making their data available to others. Confidence

that their data cannot be corrupted or lost reassures them to share even more.

Data sharing, with appropriate access control, is the rule, not the exception. Data

are peer-reviewed by the community of researchers re-using and re-validating

them. The outcome: A data-rich society with information that can be used for

new and unexpected purposes.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Risk of Inaction: Information stays hidden. The researcher who created it in the

hope it can yield more publications or patents in the future holds on to it. Other

researchers who need that information are unable to get at it, or waste time re-

creating it. The outcome: A world of fragmented data sources – in fact, a world

much like today.

4. Public funding rises, because funding bodies have confidence that

their investments in research are paying back extra dividends to

society, through increased use and re-use of publicly generated

data.

Expected impact: Research productivity rises, through easy access and re-use of

data. Funders take a strategic view of the value of data – and plan investments

logically and consistently. R&D activity grows globally. New and unexpected

solutions emerge to our major societal challenges.

Risk of Inaction: The public sector unnecessarily spends money on producing

data over and over again, because they are lost or cannot be found. Data that are

of the greatest value to the public (of a “public goods” nature) are a special loss.

Researchers overlook important insights, because they cannot access or

understand potentially vital data from others around the world. Opportunities for

progress and prosperity are missed. Investment slows.

5. The innovative power of industry and enterprise is harnessed by

clear and efficient arrangements for exchange of data between

private and public sectors, allowing appropriate returns to both.

Expected impact: Data generated for one purpose are re-used for others, and the

pace of innovation – social and technological – rises. Commercial research capability

is strengthened by public research, and broad expertise is harnessed to the benefit

of all. Mobility and cross-fertilisation between the commercial and academic sectors

increase, amplifying the impact of innovation and new discoveries. New companies,

jobs and fortunes result. European industry is more competitive.

Risk of Inaction: Suspicion and adversarial attitudes develop between private

and public sectors. A vicious circle sets in of ivory-tower academics and under-

investing industrialists. Europe’s competitiveness suffers.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

6. The public has access to and can make creative use of the huge

amount of data available; it can also contribute to the data store

and enrich it. Citizens can be adequately educated and prepared

to benefit from this abundance of information.

Expected impact: Citizens can share and contribute to the scientific process. They

understand the benefits and risks of new technologies better, and more rational

political decisions emerge. The young are inspired by an ambition for new

discoveries, and join the ranks of scientists and engineers in far-greater numbers.

Risk of Inaction: Citizens feel increasingly distrustful of and isolated from

science, and resistant to technology. They are easily misled by pseudo-science

and political demagogy. The supply of engineers and scientists is inadequate to

society’s needs.

7. Policy makers are able to make decisions based on solid

evidence, and can monitor the impacts of these decisions.

Government becomes more trustworthy.

Expected impact: Policy decisions improve, and public confidence in the entire

political process rises. It is possible to correct policy mistakes, whether economic

or social, in real time. People gain confidence in government, and political

participation rises.

Risk of Inaction: Ill-informed political decisions lead to bad results, and our

economic, environmental and social problems mount. Citizens lose confidence

in their leaders. An impenetrable wall of data separates the governors from the

governed.

8. Global governance promotes international trust and

interoperability.

Expected impact: Citizens have access to the world’s store of information

without unnecessary boundaries. A framework for global interoperability

maintains a common, public space for scientific data. This instils trust and

ensures that the best minds can make use of information no matter where they

are. World trade grows, and societies prosper.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Risk of Inaction: The divide between the information-rich and the information-

poor grows. Some of the best minds are isolated, and new ideas go

un-exploited. The world is a poorer place.

Who benefits from scientific e-infrastructure

Beneficiaries Benefits

Citizens Appreciate the results and benefits arising from research

and feel more confident in how their tax money is spent

Find their own answers to important questions, based on

real evidence

Pass on knowledge and experience to others, and make a

contribution to the knowledge society beyond their

immediate circle and life-spans

Funders and Make evidence-based decisions

Policy Makers

Eliminate unnecessary duplication of work

Get greater return on investment

Researchers Have all data and tools easily available, increasing

productivity

Cross disciplinary boundaries, gaining new insights and

producing new solutions

‘Stand on the shoulders of giants’

Enterprise and Use the best available

Industry information for R&D, increasing productivity

Create new knowledge, markets and job opportunities

Provide a strong industrial and economic base for

European prosperity

Increase opportunities for mobility and knowledge

exchange

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

V. A call to action

he scientific and social benefits of our vision are numerous. But there are

many other practical reasons to act. ICT is one of the main engines of

economic growth. It is to our age what paved highways, national railroads

and inter-continental telegraphs were to earlier generations. Yet in Europe, the

industry underpinning this vital economic activity has had many difficulties.

And, as the European Competiveness Council has noted, “the ICT impact on

productivity growth is lower in the EU than in major trading partners.”

concerted European effort to build e-infrastructures for science will stimulate

market demand for ICT. It will pull the best from ICT researchers, engineers and

industrialists, spurring growth and jobs. And it will pave the digital highways

that European science will need.

There is a clear role for government in all this. We urge our leaders to take into

consideration the following:

■ A good framework for the governance of data will be a source of strength in

the most knowledge-intensive industries, fostering the growth of companies,

goods, and services with the highest value-added. Those regions of the

world that lead this policy debate, and develop the technologies and

industry to support it, will gain competitive advantage.

■ Scientific e-infrastructure is essential if we are to address the Grand

Challenges of today. Understanding climate change, finding alternative

energy sources, and preserving the health of an ageing population are all

fiendishly complex, cross-disciplinary problems that require high-

performance data storage, smart analytics, transmission and mining to solve.

■ Social cohesion will depend in part on how fairly and openly knowledge and

information flow within our region and between the public and private

sector. If information is power in the knowledge economy, governments

must ensure that the benefits are appropriately distributed. Governments

must work effectively through public-private partnerships to develop

e-infrastructure.

■ International collaboration is essential; there is no such thing as a purely local

or national network anymore. We must collaborate in global architectures

and governance for e-infrastructure, and we must share costs and

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

technologies for archiving, networking and managing data across the globe.

With this preamble, we offer a short-list of action by various EU institutions. Of

course, we recognise there has already been much work done in the field. The

Commission has funded several projects to develop distributed computing

environments, databases for discipline-specific content, and libraries for new

types of online communications. There has been much debate – from the

Commission, the Council and the Parliament – about the need to speed

development of scientific e-infrastructure. And we note that many other public

bodies have begun considering these matters: For instance, the group reporting

to the US Office of Science and Technology Policy recently published its own

agenda and recommendations for ensuring long-term access to digital

information.

But more, urgent, concrete action is needed from all parties, we

believe. First steps include:

1. Develop an international framework for a Collaborative Data

Infrastructure

The emerging infrastructure for scientific data must be flexible but reliable,

secure yet open, local and global, affordable yet high-performance. Obviously,

this is a tall order – and there is no one technology that we know today or can

imagine tomorrow to achieve it all. Thus, what is needed is a broad, conceptual

framework for how different companies, institutes, universities, governments

and individuals would interact with the system – what types of data, privileges,

authentication or performance metrics should be planned. This framework

would ensure the trustworthiness of data, provide for its curation, and permit an

easy interchange among the generators and users of data. For the sake of

illustration, we outline below the broadest building blocks of such a framework.

The Commission has funded several projects to

develop distributed computing environments,

databases for discipline-specific content, and

libraries for new types of online communications.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

This Collaborative Data Infrastructure is a map to be filled in by thousands of

different actors across the globe and over many years. But we call upon the

European Commission to accelerate efforts to make this map. And it should

consider requiring that all relevant EU research projects should, when it comes

to considering their data management, fit into such a framework.

2. Earmark additional funds for scientific e-infrastructure

This is expensive. And as e-infrastructure for scientific data has a public

dimension, so it should also have appropriate public funding. There are several

possible funding sources – including some ideally suited for major infrastructure

projects of this sort. The EU’s Structural Funds are already used to build new

schools, roads, industrial parks and other key infrastructure, targeted at those

regions of Europe most in need. Already, a portion of these Structural Funds are

earmarked for research and innovation. This need, for data generation and

maintenance, cuts across that part of the budget – and all EU programmes,

innovation-related or not. We call upon the European Council to increase the

amount spent specifically on e-infrastructure for scientific data.

The Collaborative Data Infrastructure - a framework for the future

ata

enerators

Community Support Services

sers

Trust

Data Curation

Common Data Services

User funcionalities, data

capture & transfer, virtual

research environments

Data discovery & navigation

workow generation,

nnotation, interpretability

Persistant storage,

identication, authenticity,

workow execution, mining

nfrta Ie Dativaorollabhe CT

ner

a Da

or the futurk forwamee - a frturucastrnfr

ers

ch enesearr

e & trcaptur

ser funcionalitiesU

eor the futur

ts onmenvirch en

tual

, vir

r, vir

ansfe & tr

ta, daser funcionalities

ommunit

tio

ust

ta C

ion, in

w ekoorw

tion, authenticaiden

t stersistanP

nnota

w generkoorw

ota discDa

vicerta S

mmon Da

vicert Sory Suppommunit

ecution, miningxw e

,yticittion, authen

,ageort st

tabilitprerttion, in

tion,aw gener

tionvigay & naerv

This gure suggests, in the

broadest possible terms,

ow dierent actors, data

ypes and services should

interrelate in a global e-

infrastructure for science.

ata generators and users

gather, capture, transfer

and process data - often,

across the globe, in virtual

research environments.

They draw upon support

services in their specic

scientic communities -

tools to help them nd

remote data, work with it,

annotate it or interpret it.

The support services,

specic to each scientic

domain and provided by

institutes or companies,

draw on a broad set of

common data services that

cut across the global

system; these include

systems to store and

identify data, authenticate

it, execute tasks, and mine it

for unexpected insights. At

every layer in the system,

there are appropriate

provisions to curate data -

and to ensure its

trustworthiness.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

3. Develop and use new ways to measure data value, and reward

those who contribute it

Who contributes the most or best to the data commons? Who uses the most?

What is the most valuable kind of data – and to whom? How efficiently is the

data infrastructure being used and maintained? These are all measurement

questions. At present, we have lots of different ways of answering them – but we

need better, more universal metrics. If we had them, funding agencies would

know what they are getting for their money – who is using it wisely. Researchers

would know the most efficient pathways to get whatever information they are

seeking. Companies would be able to charge more easily for their services. We

urge the European Commission to lead the study of how to create meaningful

metrics, in collaboration with the ‘power users’ in industry and academia, and in

cooperation with international bodies.

4. Train a new generation of data scientists, and broaden public

understanding

Achieving all this requires a change of culture – a new way of thinking about

when you share information, how you describe or annotate it for re-use, when

you hide it or protect it, when you charge for it or give it away. It requires new

knowledge about how researchers use and re-use information, in different

disciplines and countries. We urge that the European Commission promote, and

the member-states adopt, new policies to foster the development of advanced-

degree programmes at our major universities for this emerging field of data

science. We also urge the member-states to include data management and

governance considerations in the curricula of their secondary schools, as part of

the IT familiarisation programmes that are becoming common in European

education.

5. Create incentives for green technologies in the data

infrastructure

Computers burn energy – vast quantities of it. Data centres absorb about 2% of

world electricity production. Computer assembly also consumes precious

minerals, lots of fresh water and adds to CO2 production. Clearly, as hardware

components multiply into the trillions, environmental constraints will tighten. So

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

the ICT industry must be incentivised to change its production and distribution

methods, to go greener. But the issue goes beyond hardware. When a researcher

makes a copy of a data set, he or she consumes resources – virtual though the

action may seem. Indeed, basic information theory tells us, whenever we bring

order to information we are adding to its energy. This fact must be understood,

and factored into our broader environmental policies. We urge the European

institutions, as they review plans for CO2 management and energy efficiency, to

consider the impact of e-infrastructure and prepare policies now that will ensure

we have the necessary resources to perform science.

6. Establish a high-level, inter-ministerial group on a global level to

plan for data infrastructure

As stated previously, it makes no sense for one country or region to act alone.

Interoperability requires that there be reciprocal agreements between

governments – the digital equivalent of trade treaties. There must also be

agreement that all countries contribute, according to their usage and needs, to

the global effort; free riders can endanger the system. We urge the European

Commission to identify a group of international representatives who could meet

regularly to discuss the global governance of scientific e-infrastructure. It should

also host the first such meeting.

There are many other actions we believe essential to the development of

e-infrastructure for science; we detail more in the Annex, and provide a list of

potential ‘show-stoppers’ that will need attention. We believe that we all

benefit from a far-seeing, collaborative and open approach to science and the

e-infrastructure to support it. We urge action now.

We believe that we all benefit from a far-seeing,

collaborative and open approach to science and the

e-infrastructure to support it. We urge action now.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

A N N E X

The 2030 Vision – and the recommendations

All stakeholders, from scientists to national

authorities to the general public, are aware of

the critical importance of conserving and

sharing reliable data produced during the

scientific process.

All member states ought to publish their policies

and implementation plans on the conservation and

sharing of scientific data, aiming at a coordinated

European approach.

Legal issues are worked out so that they encourage,

and not impede, global data sharing.

The scientific community is supported to provide its

data and metadata for re-use.

Every funded science project includes a fixed

budget percentage for compulsory conservation

and distribution of data, spent depending on the

project context.

Data form an infrastructure, and are an asset for

future science and the economy.

Vision Summary Recommendations Impact if achieved

Researchers and practitioners from any

discipline are able to find, access and process

the data they need. They can be confident in

their ability to use and understand data, and

they can evaluate the degree to which that data

can be trusted.

Create a robust, reliable, flexible, green, evolvable data

framework with appropriate governance and long-term

funding schemes to key services such as Persistent

Identification and registries of metadata.

Propose a directive demanding that data

descriptions and provenance are associated with

public (and other) data.

Create a directive to set up a unified authentication

and authorisation system.

Set Grand Challenges to aggregate domains.

Provide “forums” to define strategies at disciplinary and

cross-disciplinary levels for metadata definition.

Work closely with real users and build according to

their requirements.

Dramatic progress in the efficiency of the scientific

process, and rapid advances in our understanding

of our complex world, enabling the best brains to

thrive wherever they are.

Producers of data benefit from opening it to

broad access, and prefer to deposit their data

with confidence in reliable repositories. A

framework of repositories is guided by

international standards, to ensure they are

trustworthy.

Propose reliable metrics to assess the quality and

impact of datasets. All agencies should recognise

high quality data publication in career

advancement.

Create instruments so long-term (rolling) EU and

national funding is available for the maintenance

and curation of significant datasets.

Help create and support international audit and

certification processes.

Link funding of repositories at EU and national

level to their evaluation.

Create the discipline of data scientist, to ensure

curation and quality in all aspects of the system.

Data-rich society with information that can be

used for new and unexpected purposes.

Trustworthy information is useable now and for

future generations.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Vision Summary Recommendations Impact if achieved

Public funding rises, because funding bodies

have confidence that their investments in

research are paying back extra dividends to

society, through increased use and re-use of

publicly generated data.

EU and national agencies mandate that data

management plans be created.

Funders have a strategic view of the value of data

produced.

The innovative power of industry and

enterprise is harnessed by clear and efficient

arrangements for exchange of data between

private and public sectors, allowing

appropriate returns to both.

Use the power of EU-wide procurement to

stimulate more commercial offerings and

partnerships.

Create better collaborative models and incentives

for the private sector to invest and work with

science for the benefit of all.

Create improved mobility and exchange

opportunities.

Commercial expertise is harnessed to the public

benefit in a healthy economy.

The public has access to and can make creative

use of the huge amount of data available to

them; it can also contribute to it and enrich it.

Citizens can be adequately educated and

prepared to benefit from this abundance of

information.

Create non-specialist as well as specialist data

access, visualisation, mining and research

environments.

Create annotation services to collect views and

derived results.

Create data recommender systems.

Embed data science in all training and academic

qualifications.

Integrate into gaming and social networks.

Citizens get a better awareness of and confidence

in sciences, and can play an active role in evidence-

based decision making and can question

statements made in the media.

Global governance promotes international

trust and interoperability

Member states should publish their strategy,

and resources, for implementation, by 2015.

Create a European framework for certification

for those coming up to an appropriate level of

interoperability.

Create a “scientific Davos” meeting to bring

commercial and scientific domains together.

We avoid fragmentation of data and resources.

Policy makers are able to make decisions

based on solid evidence, and can monitor

the impacts of these decisions. Government

becomes more trustworthy.

Propose a directive to ensure that public data is

available (with security where applicable).

Policy decisions are evidence-based to bridge

the gap between society and decision-making,

and increase public confidence in political

decisions.

R I D I N G THE WAV E How Europe can gain from the rising tide of scientific data

Impediments What we could do to overcome them

What could jeopardise the vision?

A N N E X

Lack of long term investment in critical components Identify new funding mechanisms

such as persistent identification Identify new sources of funding

Identify risks and benefits associated with digitally encoded information

Lack of preparation Ensure the required research is done in advance

Lack of willingness to co-operate across disciplines/ funders/ nations Apply subsidiarity principle so we do not step on researchers’ toes

Take advantage of growing need of integration: within and across disciplines

Lack of published data Provide ways for data producers to benefit from publishing their data

Lack of trust Need ways of managing reputations

Need ways of auditing and certifying repositories

Need quality, impact, and trust metrics for datasets

Not enough data experts Need to train data scientists and to make researchers aware of the importance of

sharing their data

The infrastructure is not used Work closely with real users and build according to their requirements

Make data use interesting – for example integrating into games

Use “data recommender” systems i.e. “you may also be interested in...”

Too complex to work Do not aim for a single top down system

Ensure effective governance and maintenance system (c.f. IETF)

Lack of coherent data description allowing re-use of data Provide “forums” to define strategies at disciplinary and cross-disciplinary levels

for metadata definition

Chair: John Wood, Secretary General of

the Association of Commonwealth

Universities

Thomas Andersson, Professor of

Economics and former President,

Jönköping University; Senior Advisor,

Science, Technology and Innovation,

Sultanate of Oman

Achim Bachem, Chairman, Board of

Directors, Forschungszentrum Jülich

GmbH

Christoph Best, European

Bioinformatics Institute, Cambridge

(UK)/Google UK Ltd, London (from

September 2010).

Françoise Genova, Director, Strasbourg

astronomical Data Centre; Observatoire

Astronomique de Strasbourg, Université

de Strasbourg/CNRS

Diego R. Lopez, RedIRIS

Wouter Los, Faculty of Science at the

University of Amsterdam; Coordinator of

preparatory project LifeWatch

biodiversity research infrastructure; Vice

Chair Governing Board of GBIF

Monica Marinucci, Director, Oracle

Public Sector, Education and Research

Business Unit

Laurent Romary, INRIA and Humboldt

University

Herbert Van de Sompel, Staff Scientist,

Los Alamos National Laboratory

Jens Vigen, Head Librarian, European

Organization for Nuclear Research, CERN

Peter Wittenburg, Technical Director,

Max Planck Institute for Psycholinguistics

Rapporteur: David Giaretta, STFC and

Alliance for Permanent Access

Report Text: Richard L. Hudson,

Science|Business

REFERENCES

ey, Tony; Stewart Tansley and Kristin Tolle, Eds. “The Fourth Paradigm:

Data-Intensive Scientific Discovery.” Microsoft Research. Redmond, Wash:

2009. PDF at

ttp://research.microsoft.com/enus/collaboration/fourthparadigm/

Council of the European Union. “The future of ICT research, innovation and

nfrastructures - Adoption of Council Conclusions.” 25 November 2009.

Vinge, V. “The Creativity Machine”. Nature, Vol. 440. March 2006.

Hey, A.F.G. and A.E.Trefethen, in Grid Computing: Making the Global

Infrastructure a Reality, F. Berman, G.C. Fox, A.J.G. Hey, Eds. Wiley, Hoboken,

J, 2003.

Beyea, Jan. “The Smart Electricity Grid and Scientific Research,” Science

328: 979, 21 May 2010.

“The Square Kilometre Array: Factsheet for Scientists and Engineers.” SKA

Program Development Office, April 2010.

http://www.skatelescope.org/PDF/100420_SKA_Factsheet-Scientists-

Engineers.pdf

National Centre for Biotechnology Information. “What is GenBank?”

http://www.ncbi.nlm.nih.gov/genbank/

Institute for Systems Biology. “Systems biology – the 21

century science.”

http://www.systemsbiology.org.

The 1000 Genomes Project. http://www.1000genomes.org/

Lofgren, Eric T. and Nina H. Fefferman. “The untapped potential of virtual

game worlds to shed light on real world epidemics.” The Lancet Infectious

Diseases, VII:9 (625 – 629), September 2007.

http://www.galaxyzoo.org/

Irwin, A. “Constructing the Scientific Citizen: Science & Democracy in the

Biosciences,” Public Understanding of Science vol.10, pp.1-18 (2001).

http://www.artportalen.se

http://earth.esa.int/gscb/ltdp

http://www.geant.net

Survey results from the PARSE.Insight project (http://www.parse-

insight.eu/) show the lack of awareness of preservation and reluctance to

share data.

Council of the European Union. Ibid.

Blue Ribbon Task Force on Sustainable Digital Preservation and Access.

Sustainable Economics for a Digital Planet: Ensuring Long-Term Access to

Digital Information.” February 2010.

http://brtf.sdsc.edu/biblio/BRTF_Final_Report.pdf

For the ‘Data Pyramid’ graphic on page 18, the HLG wishes to acknowledge:

Berman, F. 2008. “Got data? A guide to data preservation in the information

age.” Communications of the ACM 51, 12 (Dec. 2008), 50-56.

http://doi.acm.org/10.1145/1409360.1409376

About the High Level Group

The High Level Expert Group on Scientific Data was charged by the European

Commission’s Directorate-General for Information Society and Media to prepare

a “vision 2030” for the evolution of e-infrastructure to scientific data.

The HLG wishes to acknowledge the following individuals for their invaluable

contribution to the discussions: Mirko Albani, Peter Doorn, Fabrizio Gagliardi,

Daron Green, István Kenesei, Puneet Kishor, Kimmo Koski, Norbert Lossau,Linda Miller,

Bernd Panzer-Steindel, Günter Stock, Ilkka Tuomi.

Design: Design4Science Ltd. Illustrations: Fletcher Ward Design

The High Level Expert

Group on Scientific Data

was charged by the

European Commission’s

Directorate-General for

Information Society and

Media to prepare

a “vision 2030” for

the evolution of

e-infrastructure for

scientific data.

After meetings and

consultations from

December 2009 through

June 2010, the group

presents its outlook and

recommendations.

Big Data Management in Scientific Data Infrastructure

Article

Feb 2021

Kavana Raghunatha

The technology and scientific sector are among the most revolving sectors in the world. Advancements in these sectors are inevitable, and the benefits are usually massive. A recent technological advancement is referred to as big data that has become an area of focus in both the tech-world and the scientific sector. This paper aims to discuss the challenges big data possesses on both current and future scientific data infrastructure. The paper contains an intense analysis of big data's features and properties such as nature, velocity, veracity, value, and variety. The paper uses several scientific communities as references to obtain a definition of the requirements of management, access, and security protocols for data. The research defines a model of scientific data lifecycle management that comprises the phases and specifics of data management in e-science. It also recommends a new generic scientific data infrastructure model referred to as the architecture model. This model's significance is to provide a foundation for developing interoperable data while using the best technological advancements. Lastly, the research gives an overview of how the proposed models can be integrated with the use of cloud-based infrastructure and propose big data's main infrastructure components.

Data Science for Geoscience: Recent Progress and Future Trends from the Perspective of a Data Life Cycle

Preprint

Full-text available

May 2021

Xiaogang Ma

Reference Exascale Architecture (Extended Version)

Article

Full-text available

Jan 2020

Medical images modality classification using discrete Bayesian Networks

Article

Apr 2016
COMPUT VIS IMAGE UND

In this paper we propose a complete pipeline for medical image modality classification focused on the application of discrete Bayesian network classifiers. Modality refers to the categorization of biomedical images from the literature according to a previously defined set of image types, such as X-ray, graph or gene sequence. We describe an extensive pipeline starting with feature extraction from images, data combination, pre-processing and a range of different classification techniques and models. We study the expressive power of several image descriptors along with supervised discretization and feature selection to show the performance of discrete Bayesian networks compared to the usual deterministic classifiers used in image classification. We perform an exhaustive experimentation by using the ImageCLEFmed 2013 collection. This problem presents a high number of classes so we propose several hierarchical approaches. In a first set of experiments we evaluate a wide range of parameters for our pipeline along with several classification models. Finally, we perform a comparison by setting up the competition environment between our selected approaches and the best ones of the original competition. Results show that the Bayesian Network classifiers obtain very competitive results. Furthermore, the proposed approach is stable and it can be applied to other problems that present inherent hierarchical structures of classes.

Open Data in Global Environmental Research: The Belmont Forum's Open Data Survey

Article

Full-text available

Jan 2016
PLOS ONE

This paper presents the findings of the Belmont Forum's survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users' perceptions of the term "open data", expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing.

Process Data Infrastructure and Data Services

Article

Full-text available

Jan 2020

Due to energy limitation and high operational costs, it is likely that exascale computing will not be achieved by one or two datacentres but will require many more. A simple calculation, which aggregates the computation power of the 2017 Top500 supercomputers, can only reach 418 petaflops. Companies like Rescale, which claims 1.4 exaflops of peak computing power, describes its infrastructure as composed of 8 million servers spread across 30 datacentres. Any proposed solution to address exascale computing challenges has to take into consideration these facts and by design should aim to support the use of geographically distributed and likely independent datacentres. It should also consider, whenever possible, the co-allocation of the storage with the computation as it would take 3 years to transfer 1 exabyte on a dedicated 100 Gb Ethernet connection. This means we have to be smart about managing data more and more geographically dispersed and spread across different administrative domains. As the natural settings of the PROCESS project is to operate within the European Research Infrastructure and serve the European research communities facing exascale challenges, it is important that PROCESS architecture and solutions are well positioned within the European computing and data management landscape namely PRACE, EGI, and EUDAT. In this paper we propose a scalable and programmable data infrastructure that is easy to deploy and can be tuned to support various data-intensive scientific applications.

Geo-Data Science: Leveraging Geoscience Research with Geoinformatics, Semantics and Open Data

Article

Full-text available

Mar 2019

Xiaogang Ma

The resources and technologies from the cyberinfrastructure are moving geoscience research forward into an intelligent stage. The cyberinfrastructure environment enabled by the World Wide Web, the Open Data initiatives and the data analysis technologies lays out the platform for data science applications in various disciplines, including geoscience. In this new era, what skills should geoscientists know and what actions can they take to foster new research topics? Are there already successful stories of data science in geoscience and what are the experiences? Can data science bring new insights to geoscience, and can data science benefit from the achievements in geoscience? There is no certain answer to most of those questions yet. Instead, we can use those guiding questions to review the recent progress and extend our thoughts for future work. This paper will introduce a few key concepts in the overlapped field between computer science, data science and geoscience, summarize several successful case studies, and present a perspective on the future work of geo-data science.

Roles and responsibilities: Libraries, librarians and data.

Article

Full-text available

Jan 2012

Sheila Corrall

Reviews opportunities and challenges for libraries and librarians in the research data arena, with reference to published reports and case studies of emerging practice, supplemented by evidence from university and library websites. Looks at connections between research data management (RDM) and established library roles and responsibilities to explore whether RDM represents an incremental step in professional practice or a paradigm shift in collection development and service delivery requiring fundamental rethinking of roles, responsibilities, and competencies to create “next-generation librarianship,” drawing on experiences and opinions of practitioners in the field. Also discusses professional education and continuing development needs for library engagement with research data, referring particularly to initiatives in the USA.

ICSU and the Challanges of Data and Information Management for International Science

Article

Full-text available

Feb 2013
Data Sci J

The International Council for Science (ICSU) vision explicitly recognises the value of data and information to science and particularly emphasises the urgent requirement for universal and equitable access to high quality scientific data and information. A universal public domain for scientific data and information will be transformative for both science and society. Over the last several years, two ad-hoc ICSU committees, the Strategic Committee on Information and Data (SCID) and the Strategic Coordinating Committee on Information and Data (SCCID), produced key reports that make 5 and 14 recommendations respectively aimed at improving universal and equitable access to data and information for science and providing direction for key international scientific bodies, such as the Committee on Data for Science and Technology (CODATA) as well as a newly ratified (by ICSU in 2008) formation of the World Data System. This contribution outlines the framing context for both committees based on the changed world scene for scientific data conduct in the 21st century. We include details on the relevant recommendations and important consequences for the worldwide community of data providers and consumers, ultimately leading to a conclusion, and avenues for advancement that must be carried to the many thousands of data scientists world-wide.

Researcher's Willingness to Submit Data for Data Sharing: A Case Study on a Data Archive for Psychology

Article

Full-text available

Dec 2013
Data Sci J

Data sharing has gained importance in scientific communities because scientific associations and funding organizations require long term preservation and dissemination of data. To support psychology researchers in data archiving and data sharing, the Leibniz Institute for Psychology Information developed an archiving facility for psychological research data in Germany: PsychData. In this paper we report different types of data requests that were sent to researchers with the aim of building up a sustainable data archive. Resulting response rates were rather low, however, comparable to those published by other authors. Possible reasons for the reluctance of researchers to submit data are discussed.

The Smart Electricity Grid and Scientific Research

Article

Full-text available

May 2010
SCIENCE

Jan Beyea

So-called “smart” meters and appliances have the potential to save energy, to shave peak electricity usage, and to reduce risks of blackouts (1–6). Typical smart meter designs include periodic transmission of current, phase, and frequency data from the user to the electricity distribution company. Utilities will use the data in billing calculations under time-of-day pricing, for load-management research, to provide customer feedback, and/or to adjust customer appliances.

Constructing the Scientific Citizen: Science and Democracy in the Biosciences

Article

Jan 2001

Alan Irwin

The relationship between science policy and public opinion has become a lively topic in the UK—especially with regard to the BSE crisis and genetically modified foods. A number of governmental publications have recently advocated greater public dialogue and engagement. In this general context, the paper explores the configuration of scientific citizenship and of the scientific citizen within policy and consultation processes. Building upon a detailed examination of one important social experiment—the Public Consultation on Developments in the Biosciences—the social construction of both science and public consultation is considered. With particular attention to the framing of issues for public debate, the constitution of audience and the construction of citizenship, the paper argues the need to move beyond mere sloganizing over science and democracy. The discussion concludes with a presentation of competing technologies of community and an assessment of their significance for the future practice of scientific citizenship.

Grid Computing: Making The Global Infrastructure a Reality

Book

May 2003

The untapped potential of virtual game worlds to shed light on real world epidemics

Article

Oct 2007
LANCET INFECT DIS

Simulation models are of increasing importance within the field of applied epidemiology. However, very little can be done to validate such models or to tailor their use to incorporate important human behaviours. In a recent incident in the virtual world of online gaming, the accidental inclusion of a disease-like phenomenon provided an excellent example of the potential of such systems to alleviate these modelling constraints. We discuss this incident and how appropriate exploitation of these gaming systems could greatly advance the capabilities of applied simulation modelling in infectious disease research.

Sustainable Economics for a Digital Planet: Ensuring Long-Term Access to Digital Information http://brtf.sdsc.edu/biblio/BRTF_Final_Report.pdf For the 'Data Pyramid' graphic on page 18, the HLG wishes to acknowledge Got data? A guide to data preservation in the information age

Jan 2009
12-50

F Berman

19 Blue Ribbon Task Force on Sustainable Digital Preservation and Access. Sustainable Economics for a Digital Planet: Ensuring Long-Term Access to Digital Information. " February 2010. http://brtf.sdsc.edu/biblio/BRTF_Final_Report.pdf For the 'Data Pyramid' graphic on page 18, the HLG wishes to acknowledge: Berman, F. 2008. " Got data? A guide to data preservation in the information age. " Communications of the ACM 51, 12 (Dec. 2008), 50-56. http://doi.acm.org/10.1145/1409360.1409376

The Creativity Machine

Mar 2006
NATURE

V Vinge

Vinge, V. "The Creativity Machine". Nature, Vol. 440. March 2006.

For the 'Data Pyramid' graphic on page 18, the HLG wishes to acknowledge: Berman, F

Dec 2008
COMMUN ACM
50-56

For the 'Data Pyramid' graphic on page 18, the HLG wishes to acknowledge: Berman, F. 2008. "Got data? A guide to data preservation in the information age. " Communications of the ACM 51, 12 (Dec. 2008), 50-56. http://doi.acm.org/10.1145/1409360.1409376

Riding the wave How Europe can gain from the rising tide of scientific data Final report of the High Level Expert Group on Scientific Data A submission to the European Commission

Abstract

Recommended publications

White Paper of the Commission of the European Communities - Strategy for a future chemical policy

ZEI Future of Europe Observer Vol. 5 No.1/2017: The Juncker Commission: Second Year Review

Book review: 'an efficient energy future: prospects for Europe and North America' for UN Economic Co...

Methods and principles for projecting future energy requirements / Economic Commission for Europe