Semantic infrastructure of a smart museum: toward making cultural heritage knowledge usable and creatable by visitors and professionals

Abstract

The Internet of Things (IoT) and Smart Spaces technologies enable development of new information services operating with descriptions of museum exhibits and available cultural heritage knowledge. In this paper, we introduce a smart museum concept where information services are not limited with straightforward provision of record-based description of exhibits, as it happens in traditional museum information systems. The concept is based on services with high intelligence level when additional historical sources can be used to semantically enrich the museum collection, including knowledge acquired from visitors and museum professionals. A museum becomes a cultural space where its semantic layer makes knowledge usable and creatable by visitors and professionals. Our research focus is on applying this concept to the case study of the History Museum of Petrozavodsk State University. A concept prototype is created, as a mandatory development phase of complex systems engineering, to analyze the need, feasibility, and technical approach. The concept prototype follows the smart spaces approach for IoT environments and defines design solutions for creating a semantic infrastructure that transforms a given museum into its smart variant.

Full text

Semantic Infrastructure of a Smart Museum:
Towards Making Cultural Heritage Knowledge
Usable and Creatable by Visitors and
Professionals
Dmitry Korzun1, Aleksey Varfolomeyev1, Svetlana Yalovitsyna2, and
Valentina Volokhova1
1Petrozavodsk State University, Petrozavodsk, Russia
dkorzun@cs.karelia.ru, avarf@petrsu.ru, vavolokhova@yandex.ru
2Institute of Linguistics, Literature and History, KarRC RAS, Petrozavodsk, Russia
jalov@yandex.ru
Abstract. The Internet of Things (IoT) and Smart Spaces technologies
enable development of new information services operating with descrip-
tions of museum exhibits and available cultural heritage knowledge. In
this paper, we introduce a smart museum concept where information
services are not limited with straightforward provision of record-based
description of exhibits, as it happens in traditional museum information
systems. The concept is based on services with high intelligence level
when additional historical sources can be used to semantically enrich
the museum collection, including knowledge acquired from visitors and
museum professionals. A museum becomes a cultural space where its
semantic layer makes knowledge usable and creatable by visitors and
professionals. Our research focus is on applying this concept to the case
study of the History Museum of Petrozavodsk State University. A con-
cept prototype is created, as a mandatory development phase of complex
systems engineering, to analyze the need, feasibility, and technical ap-
proach. The concept prototype follows the smart spaces approach for
IoT environments and defines design solutions for creating a semantic
infrastructure that transforms a given museum into its smart variant.
Keywords: cultural heritage, museum information system, smart mu-
seum, information service, semantic network, smart space, Internet of
Things (IoT)
1 Introduction
Many museums have already benefited from “digitalization” based on informa-
tion and communication technology (ICT). A traditional way for the digitaliza-
tion is deploying a database or even a museum information system (MIS), e.g.,
see [1, 2]. Such a system is typically used as an electronic archive or catalogue to
collect description for all exhibits (cultural heritage objects). Basic search func-
tions become available for museum personnel to read the collected descriptions

as fixed records. The collection storage and management functions in MIS are
also performed by museum professionals.
Museum visitors cannot directly operate with MIS or its access is very lim-
ited. Fortunately, the progress in IoT technology has already leaded that some
museums provide exhibits equipped with IoT-enabled digital equipment, e.g.,
see [3–5]. An exhibit becomes able to describe itself to nearby visitors. Exhibits
are transformed into IoT smart objects, where such an object is defined [6–8]
as acting autonomously to make own decisions, sensing the environment, com-
municating with other objects, accessing resources of the existing Internet, and
interacting with human.
In particular, a new concept of smart cultural environments is discussed
in [9]. The use of IoT-enabled location-based services makes possible shortening
the information distance between objects in cultural spaces and their visitors.
Rethinking of cultural spaces (from the point of view of their design and services
they can provide) for improving visitors experience and cultural knowledge dif-
fusion through IoT is presented in [4]. Based on IoT-enabled sensors deployed
in the cultural space, any object can be “dressed” of its context and juxtaposed
into it. The sensors observe the environment and support the people enjoyment
process, establishing multiple connections among the end-users through which
convey information, stories and multimedia content.
The idealistic case, when each museum exhibit is transformed to a full-valued
decision-making entity in the IoT sense, is still far from the today’s reality. More-
over, some exhibits are non-physical but informational objects (e.g., a photo or
audio interview, see more examples in [4]). In this paper, we introduce our con-
cept of a smart museum, which involves both physical and information exhibits.
Our study follows the smart spaces approach to make fusion of the physical and
information worlds in a given local IoT environment [8]. The aim is to transform
a museum to a collaborative work environment where cultural heritage knowl-
edge becomes usable and creatable by visitors and professionals themselves.
In our smart museum concept, services are not limited with local description
of a given exhibit. They become services of high intelligence level since they
are able to take into account additional historical sources to semantically enrich
the museum exhibit descriptions collection. The sources are from MIS, from
exhibits themselves as well as from museum visitors and professionals. A smart
museum becomes a service-oriented system constructed on the top of MIS and
augmented with other information sources. Importantly that it can access local
non-MIS resources from the local surrounding (e.g., from museum visitors and
personnel) and from the global Internet. The users are explicitly involved in
the process of knowledge use and creation, as it happens in social self-adaptive
applications [10]. Furthermore, the concept follows the generic vision of context-
aware pervasive systems [11], when the system can interact with users through
devices sensitive to the environment (e.g., mobile phones).
We apply this concept to the case study of the History Museum of Petroza-
vodsk State University. As the result, a concept prototype is created, which
represents a mandatory development step of complex systems engineering. The

concept prototype is a result of joint efforts of experts from software engineering
and museology. This theoretical work aims at analysis of the need, feasibility,
and technical approach. The concept prototype is further required for guiding the
implementation of and experimentation with a proof-of-the-concept prototype.
The concept prototype defines design solutions for creating a semantic infras-
tructure that transforms a given museum into its smart variant. The architec-
tural design is smart spaces based. Many agents run on local digital equipment
of the museum, remote server machines located somewhere in the Internet, and
personal mobile device carried by the users. The agents cooperatively construct
a semantic network based on information and its semantic relations acquired
from available sources. The service construction is reduced to search and analy-
sis in this semantic network. The museum becomes a smart space where many
sources are integrated and interrelated on the semantic layer, making a possibil-
ity to construct over this semantic network new information services with high
intelligence level. The effectiveness of this way of concept elaboration for smart
spaces-based applications was previously demonstrated on other case studies,
see our works [8, 12] and references therein.
The rest of the paper is organized as follows. Section 2 analyzes existing
approaches to development of information services for museums. Section 3 in-
troduces the smart museum concept. Section 4 considers a selected case study
of the History Museum of Petrozavodsk State University to apply the proposed
concept. Section 5 describes our concept prototype consisting of design solutions
for creating smart spaces-based semantic infrastructure in a smart museum. Sec-
tion 6 discusses the feasibility of the proposed concept in respect to the selected
case study. Finally, Section 7 concludes the paper.
2 Museum Information Services: Related Work Analysis
and Service Intelligence Level
Since the 1960th a lot of efforts have been made in the area of digital museums,
which are based on development and deployment of museum databases or MIS.
Such a MIS primarily aims at collections management involving the development,
storage, and preservation of collections and cultural heritage, e.g., see a historical
review in [2]. The goal of collections management is to track all information
related to and about the cultural objects (exhibits) and to ensure the long-term
safety and sustainability of those objects within the museum’s care.
When a museum tracks all information on its exhibits then a specific type of
digital services can be provided to the museum personnel as well as to museum
visitors. In general, this type of services is called “information services” since
they provide information to users [8]. An information service has the following
two distinctive characteristics.
1. Provided information (not data) is meaningful in a such a way that it can
be interpretable by the user in accordance with the user’s needs and current
situation.

2. Provided information is subject to appropriate exposition (visualization)
aiming at effective perception and interpretation by the user.
A traditional MIS limits the scope of information services with basic collec-
tion management and search functions. The typical role of MIS is an electronic
archive or catalogue, which is administered by museum personnel. First, a lot of
efforts is still needed for a user to find the needed information meaningful for a
given analysis problem, since the semantics are not reflected explicitly in MIS.
Second, museum visitors do not act as proper users; at most they can straight-
forwardly browse the content, e.g., on the museum web site or using multimedia
machines in the museum.
Therefore, a MIS as such provides too basic information services, which sup-
port no explicit intelligence in searching and processing the collected descriptions
and other content related to exhibits. Let us further consider existing extensions
of these basic information services, which are now often called as “smart ser-
vices”, emphasizing the introduction of a certain service intelligence level into
the service construction and delivery.
The progress in mobile and web ICT has leaded to a popular class of MISes,
each is formed by on-site personalized services for museum visitors. A visitor has
a personal mobile device (e.g., smartphone) and can access relevant information
about surrounding exhibits. The information flow is unidirectional: from digital
cultural heritage to visitors. In this case, services do not support collaborative
activity and knowledge creation. In particular, users of SMARTMUSEUM sys-
tem [13] can receive explanatory description and multimedia content associated
with individual objects. The system recommends objects on the basis of a user
profile and context information (e.g., the physical location and motivation of
the user). The system can retrieve information about a given object and related
content from the Web. A user accesses both the recommendations and related
content. In addition, the system enables on-site video streaming for content to
which video is attached, along with speech synthesis.
The on-site visit boundaries of cultural heritage experience at the museum
can be extended to assist the visitors during pre-visit planning, to provide rel-
evant information to the visitors during the visit (as in the SMARTMUSEUM
system above), and to follow up with post visit memories and reflections. In
particular, a generic integrative framework is discussed in [1] for supporting the
pre, during, and post visit phases in a personalized manner and in the settings
of an actual museum. Interestingly that this framework supports services with
feedback, e.g., visitors can leave posts on exhibits (to read by other visitors)
or participate in ranking an exhibit (collaborative activity). This service model
follows the style of social networking, i.e., involving people into the process [10].
More interactive scenarios for museum visitors to access cultural heritage
knowledge employ the advances of IoT technology [3, 5]. A museum can be
thought a system of smart objects (cooperatively) assisting museum visitors.
For instance, an interactive museum exhibition design made up of tangible smart
replicas is proposed in [14]. Such replicas provide digital content to visitors, in-
troducing an additional information layer to complement the traditional, factual

knowledge about objects in a museum. In addition to enhancing interaction be-
tween visitors and cultural heritage objects, IoT devices can support interaction
between visitors and museum professionals [15], including collaborative activity
based on social networks.
The IoT technology enables cultural objects to interact with people, environ-
ments, other objects, and transmitting the related information to users through
multimedia facilities [4]. Using sensors any object can be “dressed” of its con-
text and juxtaposed into it. The sensors observe the environment and support
the people enjoyment process, establishing multiple connections among the end-
users through which convey information, stories and multimedia content. The
use of IoT-enabled location-based services makes possible shortening the infor-
mation distance between objects in cultural spaces and their visitors [9]. Some
other cases studies of creating smart museums are considered in the following
works. DALICA [16] is an agent-based system for outdoor cultural-heritage sce-
narios when sensors send information about nearby points of interest. SMART
VILLA [17] is based on a set of mobile applets to access cultural heritage ar-
eas of particular interest, in which different objects of artistic interest can be
interfaced in a proper virtual way without affecting the historical environment.
The system is related to particular sites (SMART BIBLIO for ancient books,
SMART ROOM for particular rooms, and SMART GARDEN for surrounding
historical gardens).
The need of semantic integration of available cultural heritage knowledge has
been already understood [18, 19]. This kind of knowledge cannot be straight-
forwardly duplicated or explicitly presented in a centralized database-oriented
information system. The semantic integration means a mediation layer when
knowledge is derived based on a distributed set of multiple data sources, includ-
ing such Internet services as DBpedia [20]. In particular, a system for semantic
publishing, enrichment, search, and visualization of cultural heritage data is pre-
sented in [21]. As the initial step, the virtual gallery of the Russian Museum was
used as a main data source with transformation and representation based on
CIDOC-CRM Ontology and with data enrichment using DBpedia.
The above analysis of related work and existing ICT advances for digital
museums leads us to the consideration of the following research directions in
development of smart museum services (i.e., with certain intelligence level).
Layered functionality: Museum information services follow a layered structure
of functions, where each layer reflects the next service intelligence level.
Multisource information: MIS is not the only information source. Construction
of a smart service inevitably involves information that can be found in the
Internet or even be provided by the users themselves.
Human involvement: Users are involved in the museum process not only as ser-
vice consumers but also as information providers and even as an element to
perform service construction, individually or in collaboration.
The functional layers for museum information services can be defined as follows.
1. Description of exhibits is delegated to the exhibits themselves [13, 1], i.e.,
explanatory information expanses from a centralized MIS to the edges.

2. Exhibits are transformed into IoT smart objects [3, 15]. In addition to the
advanced self-explanatory function they are able to complement their local
knowledge with Internet resources, including web services and social net-
working activity).
3. Information about exhibits and other sources of historical data is semanti-
cally enriched and integrated [21,18]. This semantically integrated corpus of
historical knowledge is applied for learning (visitors), exposition construction
(museum personnel), and historical analysis (professionals).
This layered structure provides a base for our smart museum concept. In
contrast to the existing research, our study focuses on the 3rd layer of above.
Effective use of such a semantically integrated corpus of historical knowledge
cannot be straightforwardly implemented. A concept elaboration phase from
systems engineering is needed to understand what kind of added-value services
characterize a smart museum. This smart museum concept is applied to the case
study of the History Museum of Petrozavodsk State University, resulting in a
concept prototype, which are used to analyze the need, feasibility, and technical
approach for creating this class of smart museums.
3 Smart Museum Concept: Enhancing a Museum
Information System
The smart museum concept considers a smart museum as a system where three
classes of information sources can be introduced, in addition to the basic collec-
tion of cultural heritage object descriptions in MIS, see Figure 1. First, museum
personnel provide expert historical knowledge related to and about the exhibits.
Second, museum visitors themselves are sources of individual (and possibly sub-
jective) information, which can be valuable for services, similarly as it happens
in social networks. Third, the today’s Internet provides a lot of historical sources,
Fig. 1. Possible historical information sources to advance information services of a
museum, in addition to the primary MIS

Fig. 2. The smart museum concept: layered function structure of information services
on top of traditional MIS
e.g., such a universal resource as DBpedia [20] or many existing web resources
specific to certain domains. The introduced semantic layer is responsible for in-
tegration of all these sources along with the content in MIS, as we shall describe
in Section 5.
The smart museum concept clarifies the generic definition of a museum in-
formation service. To support effective interpretation and visualization, the fol-
lowing properties are used.
–Provided information is a result of search and reasoning over the multiple
information sources.
–Provided information includes explicit representation of the semantics.
–Provided information acts as assistance or recommendation.
Figure 2 illustrates the proposed smart museum concept. It defines a func-
tional structure of a smart museum. Information services focus on applying the
knowledge that is collected and virtually integrated in such a museum from
multiple sources.
In the layered functionality, the three layers, each defines the next service
intelligence level, were proposed in Section 2. Layer 1 expanses available infor-
mation to many system elements targeting the museum edges: the information
appears close to the studied object, e.g., directly on the studied exhibits. Layer 2
enables IoT-aware information exchange when both users and exhibits are in-
volved in the process. Layer 3 provides the highest intelligence level when services
create new knowledge.

Now let us describe some generic application problems that are solved reg-
ularly in many museums. Solutions to them can be effectively supported based
on the proposed smart museum concept.
1. Visitors learning: This primary activity of a museum visitor is supported
by providing appropriate information assistance and recommendation. The
visitor observes descriptions of surrounding exhibits as well as their relation
to other cultural heritage objects and historical facts.
2. Exposition construction: Museum personnel is supported with recommen-
dations on selection of exhibits based on their correspondence to the given
topic and the expected visitors’ interests.
3. Historical analysis: Finding facts based on a set of considered objects and
their relations. The problem is both for museum personnel (as professional
historians) and for museum visitors (as active learning entities). An im-
portant case is finding hidden knowledge when the user is provided with
uncertain (possible) facts which needs further analysis by human.
In the smart museum concept, a museum becomes a cultural space where
visitors and professionals solve, either individually or collaboratively, the above
application problems. Smart (information) services are constructed within this
space supporting the users to perceive, exchange, and create knowledge. As in
many smart spaces applications [12], the constructed services enable a collabo-
rative work environment where various cultural heritage study processes can be
effectively realized in a given museum exposition room.
Finally, the smart museum concept defines the following mechanisms that
provide the basis for service construction in a smart museum. These mechanisms
implements the semantic layer (see Figure 1 above).
1. Adding descriptions related to or about the exhibits by the users. The goal is
annotation of exhibits, enriching the museum collection with basic semantic
information. First, this information describes facts readable when the ex-
hibit is studied. Second, it potentially contains (hidden) relations with other
exhibits as well as with derived facts about collected exhibits.
2. Semantic information linking of exhibits in the museum collection. The goal
is to create a semantic network on top of the museum collection, i.e., forming
a kind of knowledge corpus, which can be further used for effective search
and analysis. Based on the ontology modeling methods, this meta-model
has the form of a semantic network with nodes representing exhibits, associ-
ated events, persons, and other historical objects. Links represent semantic
relations, even subjective or short-term, allowing interpretation as certain
historical facts.
3. Personalized access to the museum collection and its semantics. The goal is
to open the knowledge corpus to the users based on their needs and interests.
Information services are constructed using search and analysis of the created
semantic network, where the search and analysis take the user profile into
account. Notably that the user can infer the semantic network because of
the previous two mechanisms.

Fig. 3. Exposition room of the History Museum of Petrozavodsk State University,
https://petrsu.ru/structure/585/muzejistoriipetrgu
4 Case Study: The History Museum of Petrozavodsk
State University
The History Museum of Petrozavodsk State University (PetrSU) is a typical
small museum oriented to everyday life history. The museum has existed since
1987 and collects sources on the university history for period from 1931 to 2016.
The MIS collects descriptions of more than 10 thousand exhibits, including phys-
ical exhibits as well as such information objects (virtual exhibits) as photos and
interviews (speech or video records). In this section, we explain the main points
of our smart museum concept based on the History Museum of PetrSU.
The following properties make this museum a good case study for the pro-
posed smart museum concept, as it is visually supported in Figure 3.
–The thematic orientation to everyday life history is interesting almost for
any visitor. Even non-professionals can provide valuable information about
exhibits, since a visitor is more or less related to events of the PetrSU history.
–The physical space for expositions is spatially limited, so its effective ICT-
enabled use is needed. The exposition room is equipped with multimedia
devices First, they show digitalized exhibits and their descriptions to aug-
ment or even partially replace physical installation. Second, the exposition
room provides a comfortable environment where people can collaboratively
work using the multimedia devices and personal mobile devices as digital
windows to the museum collection and its study process.
–Due to the university domain, the museum visitors are typically experienced
in ICT such that they are interested to participate in the innovative learn-
ing style, including the use of their personal mobile devices and personal
involvement in to the museum collection study process.

In the Museum a visitor appears in an unusual cultural space. More than
10 digital displays of various sizes with changing images of photographs, doc-
uments, newspaper articles from different eras of more than 75-year PetrSU
history. Transformable table makes it easy to change the Museum space, making
it comfortable for different forms of collaborative work activities. Some displays
show video and audio interviews with the teachers of the University in differ-
ent years. Exhibits presented on windows show everyday life history of teachers,
researchers, and students. Some exhibits, despite their advanced age, can be ex-
perienced directly in the room. Old movies about PetrSU life in the 1970s and
1980s provide the necessary historical atmosphere.
The History Museum of PetrSU has own MIS, which is primarily used for
museum collections accounting in accordance with the national museum rules.
For each exhibit a record is stored with a fixed set of fields for description.
Basic browsing and search operations are supported, including web access to the
collected descriptions.
This MIS cannot be used straightforwardly for constructing information ser-
vices with high intelligence level. For instance, let the museum prepare an ex-
position on the university rectors. Although all rectors can be found by a basic
search query in the MIS, the relation of the rectors to many interesting exhibits
is hidden. Some of these exhibits are worth to be included into the prepared ex-
position. As an example, the exposition of rector K.D. Mitropolsky can benefit
from many newspaper articles published during the PetrSU evacuation 1942–
1944 from Petrozavodsk to Syktyvkar. Some articles are not, however, include
explicitly the rector’s name, and additional semantic analysis is needed to select
appropriate articles to the exposition.
Based on the proposed smart museum concept, such services need the se-
mantic layer. On the latter a semantic network is created using content from the
MIS and other appropriate sources of historical information. The role of Inter-
net sources is this case is minor since the most valuable information can provide
experts and those people who participated in the events related to the exhibits.
Consider a semantic network for the History Museum of PetrSU. The nodes
corresponds to exhibits and to other historical entities (e.g., persons, geograph-
ical points, buildings, events). Let us call “a historical object” (or an object
for short). Types of links between objects can be very various and a link name
describes semantics. One of the simplest link types is object occurrence in the
description of another object:
object Ais referred by object B
Based on generic application problems from Section 3 we consider the fol-
lowing scenarios, for which the use of smart services is effective in the History
Museum of PetrSU.
1. Visitors learning: A museum visitor augments the semantic network based
on her/his individual knowledge.
2. Exposition construction: A museum expert creates an exposition based on
profiles of the expected visitor.

3. Historical analysis: A historian analyzes the existing museum collection in
order to enrich the collection with more historical knowledge.
The considered instance of the visitors learning problem is characterized by
the feedback from visitors. The corresponding smart service follows the “now
and here” style when the visitor observes some objects (e.g., on a display in the
Museum) and can directly provide descriptions for them or even can describe
relations between the objects. For an example, the visitor observes a photo show-
ing a group of people. The visitor then identifies some persons on the photo and
provides their names. The latter, in turn, either are already represented as ob-
jects in the semantic network or new objects for the persons are added to the
semantic network.
The considered instance of the exposition construction problem is charac-
terized by personalization. The corresponding smart service analyzes the given
user profiles and make recommendation which exhibits can be within of these
visitors’ interest. For an example, if the visitors are from France then exhibits
on cooperation between PetrSU and France are recommended. In particular,
agreements with organizations in La Rochelle can be selected since this city in
France is a sister city of Petrozavodsk. Similarly, photos of visiting PetrSU by
delegations from La Rochelle can be included to the exposition.
The considered instance of the historical analysis problem is characterized by
new knowledge derivation. In historical studies, it is important to find (a) hidden
facts and (b) points of lack of knowledge. Smart museum service can provide
assistance a historian in the solving process.
In case (a), the corresponding smart service finds a fact that some objects
are related (e.g., there are connected by some paths in the semantic network).
Clarification of this fact is the responsibility of the historian. In particular, she/he
can make interview with persons related to this fact and the derived information
can be included into the semantic network. In case (b), the corresponding smart
service finds that there is a group of similar but low related or described objects.
In particular, a set of similar photos can be found where the represented persons
or environment have no rich description. Importantly that cases (a) and (b) can
also be interesting to visitors when the smart service finds hidden facts or points
of lack of knowledge in personalized manner. This way, the service involves the
visitor to the museum collection enrichment process.
5 Semantic Integration and Knowledge Processing
Infrastructure
The smart museum concept can be realized following the smart spaces ap-
proach [8]. A particular open source platform is Smart-M3 [22, 12], where M3
stands for multi-device, multi-vendor, and multi-domain. Using Smart-M3 a soft-
ware infrastructure can be developed that implements the semantic layer of a
smart museum. In this section, we describe high-level design solutions that con-
stitute a concept prototype of software infrastructure.

We consider a museum exposition room as a particular case of indoor lo-
calized IoT environments [23]. The localization means that although the envi-
ronment is local (in a spatially restricted area) some remote components can be
presented, including access to the Internet or to servers in the corporate network.
The following classes of IoT-enabled devices are present.
–Public multimedia devices. For instance, they include interactive screens,
media projectors, and microphones installed in the exposition room. The
devices are primarily for service consumption by visualizing the information
to the users. In some cases, the users can use such devices for data input
and control.
–Personal mobile devices. For instance, they include smartphones, tablets,
and laptops carried individually by the users. The devices can be used for
personalized service consumption and participation in the activity.
–Server machines. They are responsible for data storage and processing func-
tions. Typically the devices are non-local, e.g., a server in the corporate
network or in the Internet.
–Smart IoT devices. They represent physical things augmenting them with
processing and communication capabilities. For instance, a physically pre-
sented exhibit is equipped with an RFID tag to provide textual description
for any close device.
–Network communication devices. They create local area networks (LAN)
such that all other participating devices can communicate locally as well as
have access to external resources (e.g., to the Internet).
In general, smart spaces provide an approach to creating service-oriented
information systems with high intelligence support in IoT environments. The
approach provides methods for semantic information sharing in the IoT environ-
ment, operation over the collected information, and cooperative service construc-
tion by all participants themselves. The participants act as service providers and
consumers. They are represented by software agents. Available digital devices
and systems can be used to run the agents, either surrounding or remote. To
support cooperation the key idea is to collect and semantically relate the in-
formation coming from all available sources. The above smart spaces properties
suit extremely well for the considered smart museum concept.
In Smart-M3, the central element is Semantic information broker (SIB). It is
deployed on a dedicated host machine of the IoT environment. SIB is responsible
for collecting information content, implementing a knowledge base with the use
of Semantic Web technologies [24]. In particular, the content is represented using
Resource Description Framework (RDF) and stored in an RDF triplestore. The
latter supports information search and processing extensions.
Having a deployed SIB, the service-oriented system is created as multi-agent.
In Smart-M3, an agent is called Knowledge Processor (KP), emphasizing the
processing role as well as allowing reduction of the autonomy level. Each KP run
on a specified device of the IoT environment. KPs directly communicates with
their SIB to access the content, i.e., agent interaction is indirect and information-
driven [25]. The RDF representation leads to interoperable information sharing.

Fig. 4. Architectural design of smart spaces based software infrastructure
In the simplest case, read and write operations allows collecting and sharing the
content (RDF triples are basic data unit). The subscription operation enables
advanced information-driven cooperation when one KP can detect changes in
the shared content.
Therefore, the design of software infrastructure consists of SIB and a set of
KPs, which follows the generic definition of software infrastructure for smart
spaces [26, 27]. As the result of asynchronous operation of many KPs on the
shared content, semantic integration and knowledge processing on top of MIS
become possible. The architectural design is shown in Figure 4.
In the considered design, the SIB is responsible for maintaining the semantic
network of a smart museum. The RDF technology of the Semantic Web provides
all necessary tool for representation and storage. The roles of participating KPs
is summarized in Table 1.
This design of software infrastructure provides enrichment of a traditional
MIS in the form of the semantic layer. This way, the mechanisms for adding
descriptions, semantic information linking, and personalized access are imple-
mented (see Section 3).
The mechanism for adding descriptions involves public multimedia devices
(e.g., interactive displays) and mobile personal devices (e.g., smartphones), using
which the user provides additional description for the objects she/he observes in
the museum.

Table 1. Smart-M3 KPs for the semantic layer of a smart museum.
Role Device Description
MIS
interface
Server machine Providing an interface with MIS. The primary data
flow is from MIS to SIB, i.e. for representing in the
semantic network all objects recorded in MIS.
Information
provision
Server
machine, UI
devices, Smart
IoT devices
Connecting information sources to the system. In par-
ticular, visitors and personnel can provide own infor-
mation to the semantic network. Note that MIS inter-
face KP is an instance of information provision KP.
Service
construction
Server machine Constructing services based on search and analysis of
the semantic network.
Service
delivery and
feedback
Public
multimedia
devices,
personal
mobile devices
Visualization of information from constructed services
to the user for consumption. Based on the consump-
tion result the user can respond with new information
that enriches the semantic network.
The mechanism of semantic information linking applies the RDF technology
to represent the semantic network in SIB. Semantic links can be cooperatively
established by: a) information provision KPs, b) service construction KPs, or
c) the user as service feedback.
The mechanism for personalized access is based on user profiles, which can
also be represented in the semantic network. The search and analysis become
conditional, in respect to user-defined constraints.
6 Discussion on Feasibility and Applicability
The previous section provided a concept prototype of a software infrastructure
that can be used for the selected case study of the History Museum of PetrSU.
Based on this concept prototype let us discuss in this section the feasibility of
our smart museum concept and applicability of our technical approach.
The feasibility can be analyzed based on existing proof-of-the-concept pro-
totypes and pilots of advanced museum systems.
–Museo Galileo (http://catalogue.museogalileo.it/): The virtual mu-
seum operates with a large corpus of historical knowledge, including descrip-
tions of historical objects and videos by thematic area. The user can follow
a virtual tour constructed based on her/his interests. This system shows
the efficacy of semantic relations between historical objects for information
service personalization.
–Smart Museum of Art at the University of Chicago (http://smartmuseum.
uchicago.edu/research/image-services/): The services offer high-
quality images of works in the collection for research purposes and for repro-
duction in scholarly, educational, and other publishing projects. The system
shows the efficacy of exhibition augmentation with Internet resources.

–SMARTMUSEUM project at National Museum of Fine Arts by joint efforts
of Heritage Malta and other European partners (http://heritagemalta.
org/projects/eu-funded-projects/cp-smartmuseum/): An infrastruc-
ture is provided for a museum to support the adaptation and demand-driven
access to multimedia information. The system shows the role of personal-
ization when user interest profile is subject to formalization and metadata
handling and user (personal and public) profile is subject to self-adaptive
management. On-site access to the vast repository of cultural heritage ap-
plies the user profile in ontological and semantic web searching.
The above museum systems present isolated “exercises” of using semanti-
cally integrated corpuses of historical knowledge. Nevertheless, they clearly indi-
cate the need of semantic enrichment and integration of multisource information
about exhibits and other historical data.
The applicability of our technical approach depends on the opportunities
of Smart-M3 platform for smart spaces-based application development [8]. Re-
cent work [12] demonstrates effective Smart-M3 applicability for a wide range
of application domains, including collaborative work, social networking, smart
logistic, and e-Tourism.
The e-Tourism domain is close to the considered concept of a smart museum.
Recent development on proof-of-the-concept prototypes for e-Tourism indicates
reasonable Smart-M3 applicability for the cases when: (a) many mobile users ac-
cess the services, (b) a large semantic network is needed to represent knowledge
corpus from many data sources, (c) users need information services as person-
alized recommendations, including cultural heritage- and history-oriented. The
appropriate analysis can be found in [18, 28, 19].
7 Conclusion
This paper elaborated the smart museum concept based on information services
with high intelligence level. Such services are able to provide information with
semantics beyond regular records stored in a traditional MIS. As the result, a
smart museum makes its cultural heritage knowledge usable and creatable by
both classes of the users: museum visitors and museum professionals. For the case
study we used the History Museum of Petrozavodsk State University. We intro-
duced design solutions to implement the semantic layer, enriching the collection
stored in a traditional MIS. Our concept prototype showed the benefits which
the smart museum concept can provide when the semantic layer is introduced.
Based on the concept prototype we discussed the feasibility of such semantic-
oriented information services and the applicability on the recent maturity level
of IoT and smart spaces technologies.
Acknowledgment
This work is financially supported by Russian Foundation for Humanities accord-
ing to project # 16-01-12033. The reported study was funded by the Ministry

of Education and Science of Russia within project # 2.2336.2014/K from the
project part of state research assignment.
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