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On timescales beyond the life of a research project, a core task in the curation of digital research data is the migration of data and metadata to new storage media, new hardware, and software systems. These migrations are necessitated by ageing software systems, ageing hardware systems, and the rise of new technologies in data management. Using th...
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• Metadata plays an essential role in the long-term preservation, reuse, and interoperability of data. Nevertheless, creating useful metadata can be sufficiently difficult and weakly enough incentivized that many datasets may be accompanied by little or no metadata. One key challenge is, therefore, how to make metadata creation easier and more valu...
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... The original data curation continuum concept has been well accepted and used across a range of settings: institutional repositories (Salo, 2008) environmental data (Baker, 2009) the sciences (Kowalczyk and Shanker, 2011), geosciences (Klump, Huber and Diepenbroek, 2016;Klump, Ulbricht and Conze, 2015), data staging repositories (Dietrich, 2010), and research data system design (Wehle, Wiebelt and Suchodoletz, 2017). ...
... For designing its institutional research data infrastructure, the Helmholtz Centre Potsdam German Research Centre for Geosciences (GFZ) in Potsdam, Germany, adopted a variation of the data curation continuum model (Klump, Ulbricht and Conze, 2015). The model was used to delineate domains and functions of the project specifc data management portals and the generic institutional data access portal, which all used the same institutional data storage infrastructure (Ulbricht, Elger, Bertelmann and Klump, 2016). ...
The Data Curation Continuum was developed as a way of thinking about data repository infrastructure. Since its original development over a decade ago, a number of things have changed in the data infrastructure domain. This paper revisits the thinking behind the original data curation continuum and updates it to respond to changes in research objects, storage models, and the repository landscape in general.
... Moreover, these standards have to be modified or adjusted according to the specific requirements of considered data [8]. Hence, most research data repositories or services apply or are in compliance with one or several existing standards that are common for their discipline or that meet the requirements of their data and data providers, as presented in a study by [9] or such as [10][11][12][13][14]. Likewise some data repositories apply multi-level approaches for data documentation [15]. ...
... It is also an experience of other repositories, which support cross-disciplinary data that available metadata standards do not meet the requirements [10][11][12]14]. Sometimes there is no one fits all metadata standard or schema available. ...
This paper presents an approach to manage metadata of (research) data from the interdisciplinary, long-term, DFG-funded, collaborative research project ‘Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation’. In this framework, a data repository, the so-called TR32DB project database, was established in 2008 with the aim to manage the resulting data of the involved scientists. The data documentation with accurate, extensive metadata has been a key task. Consequently, a standardized, interoperable, multi-level metadata schema has been designed and implemented to ensure a proper documentation and publication of all project data (e.g. data, publication, reports), as well as to facilitate data search, exchange and re-use. A user-friendly web-interface was designed for a simple metadata input and search.
... The strategy to migrate these data into a modern repository has been evaluated in a paper by Klump et al. (2015). ...
The Continental Deep Drilling Program of Germany (in German: Kontinentales Tiefbohrprogramm der Bundesrepublik Deutschland, abbreviated as KTB) was a scientific drilling project near the town of Windischeschenbach, Bavaria. The KTB Depth Laboratory comprises two 9.1 km and 4 km deep, water-filled boreholes in crystalline basement rocks just 200 meters apart from each other. Available equipment such as cables, winches, geophysical borehole tools as well as workshops and office infrastructure allows for in-situ tests and experiments at different pressure and temperature conditions. The two stable wells are large-diameter steel-cased and have been geophysically monitored in detail since 1996.
... The curation policy of GFZ Data Services is based on a separation of concerns between research project and memory institution (e.g., library). In this concept, the data curation continuum from data generation through data storage to data access is divided into four "Domains of Responsibility" [14,15]. These "Domains of Responsibility" in research data management help to delineate the responsibilities of the actors involved. ...
... We collect research articles, datasets and associated metadata with the web-based The curation policy of GFZ Data Services is based on a separation of concerns between research project and memory institution (e.g., library). In this concept, the data curation continuum from data generation through data storage to data access is divided into four "Domains of Responsibility" [14,15]. These "Domains of Responsibility" in research data management help to delineate the responsibilities of the actors involved. ...
... GFZ Data Services operate in the "Persistent" and "Access" domains and work with researchers to transfer their data into the "Persistent" domain for publication and archiving. More detail on how we implemented the curation domains based on eSciDoc can be found in Klump et al. (2015) [14]. ...
The GFZ German Research Centre for Geosciences is the national laboratory for Geosciences in Germany. As part of the Helmholtz Association, providing and maintaining large-scale scientific infrastructures are an essential part of GFZ activities. This includes the generation of significant volumes and numbers of research data, which subsequently become source materials for data publications. The development and maintenance of data systems is a key component of GFZ Data Services to support state-of-the-art research. A challenge lies not only in the diversity of scientific subjects and communities, but also in different types and manifestations of how data are managed by research groups and individual scientists. The data repository of GFZ Data Services provides a flexible IT infrastructure for data storage and publication, including minting of digital object identifiers (DOI). It was built as a modular system of several independent software components linked together through Application Programming Interfaces (APIs) provided by the eSciDoc framework. Principal application software are panMetaDocs for data management and DOIDB for logging and moderating data publications activities. Wherever possible, existing software solutions were integrated or adapted. A summary of our experiences made in operating this service is given. Data are described through comprehensive landing pages and supplementary documents, like journal articles or data reports, thus augmenting the scientific usability of the service.
Database maintenance and migration are critical but under‐supported activities in libraries, archives, museums (LAMs), and other scholarly spaces. Existing guidelines for digital curation rarely account for the maintenance needed to keep digital curation infrastructures functioning over time. Though many case studies have been published describing individual instances of migration, there has been little generalizable research done in this area. Thus, it is challenging to understand overall trends or best practices in this space. We bridge this gap by conducting an integrative literature review of papers describing database migrations and maintenance in LAMs and other scholarly contexts. By qualitatively coding 75 articles from 58 publication venues, we identify common motivations for database migrations and maintenance actions. We find that databases are migrated to support changing user needs as well as to ward off technological obsolescence; we also find that common challenges include schema crosswalking and a need for data cleaning. Practitioners describe community collaboration as key in surmounting these challenges. Through this integrative review, we build a base for further best practices development and identify a need to better model database curation as part of the digital curation lifecycle.
