=Paper=
{{Paper
|id=None
|storemode=property
|title=A Linked-Data-based Search System of Educational Tools for the Web of Data
|pdfUrl=https://ceur-ws.org/Vol-709/paper14.pdf
|volume=Vol-709
|dblpUrl=https://dblp.org/rec/conf/ectel/Ruiz-Calleja10
}}
==A Linked-Data-based Search System of Educational Tools for the Web of Data==
https://ceur-ws.org/Vol-709/paper14.pdf
A Linked-Data-based search system of
educational tools for the Web of Data
Adolfo Ruiz-Calleja
School of Telecommunications Engineering, University of Valladolid
Camino del Cementerio s/n, 47011 Valladolid, Spain
adolfo@gsic.uva.es
Abstract. The number of learning situations that can be carried out in
a VLE (Virtual Learning Environment) can be improved by the integra-
tion of third-party external tools. Before the integration takes place, it is
compulsory to retrieve some information, both to select the most appro-
priate tool to support an specific situation and to be able to integrate
it in the VLE. Current tool registries have some drawbacks that make
the data retrieval difficult for the educators; among these drawbacks, the
most important one is that search engines are not able to automatically
import information from external datasets. To overcome this limitation,
this paper introduces an ongoing doctorate research that proposes the
creation of a search engine based on the Linked-Data principles.
Keywords: Linked Data, educational tools, Semantic Web, integration.
1 State of the art and problem statement
A Virtual Learning Environment (VLE) is a software system used by teachers
and students to support the realization and assessment of learning situations [7].
Some examples of VLEs with a wide adoption are Moodle1 or LAMS2 . These
VLEs typically include a set of general purpose tools, although educators com-
monly require to use a particular tool to support specific learning situations
[5]. For this reason, ongoing research on the field tries to integrate third-party
external tools in VLEs, following different approaches, as shown in [2].
A key step to enabling the integration of external tools in VLEs, or other
software environments, is facilitating the discovery of tools, providing useful in-
formation for the tool selection and its integration in the environment. When
educators are searching tools they need to make queries using educational ab-
stractions. In addition, the integration of tools should be semi-automatic, as
educators are not expected to manipulate the data needed to integrate the tool.
Finally it is convenient to have a big boundle of tools available and thus allowing
educators to choose the most appropriate one.
There are some general-purpose search engines, such as Google, that are
commonly used by teachers to discover general information. However, they are
1
http://moodle.org/
2
http://www.lamsinternational.com/
79
designed to retrieve text documents and not data about software tools; these
documents may contain a text description about software tools, but data must
be extracted out of them by a human. In order to facilitate the software tool
data retrieval, some other search engines, such as Google Gadgets3 or Yahoo!
Widgets4 , give support for searching tools, providing data about thousands of
tools. Moreover, they are commonly used by non-expert users. However, these
kind of search engines are not specialized in educational domain, so they do
not provide educational information related to the tools; in addition they are
keyword-based search systems, which are prone to obtain irrelevant results [8,
Pag. 91]. These drawbacks are overcome by OntoolSearch5 , an educational tool
search engine based on semantic technologies that use the Ontoolcole [10] ontol-
ogy to describe software tools. Nevertheless, OntoolCole only allows to express
the functional properties of the tools, and not their non-functional properties.
Therefore, OntoolSearch cannot provide the information for integration of tools.
Another important drawback that is common to all the aforementioned search
systems is that they are not able to automatically import information from third-
party external repositories. These search systems can only take information from
their own internal registry, which behaves as a independent data silo. Thus, each
search system is only able to provide the information that has been explicitly
described in its internal registry, even if there is more relevant information in an-
other dataset freely accessible through the Web. Moreover, a software tool may
be described in a search system internal registry but it may have been updated
in another external data source, so a teacher that uses this search system will
get out-of-date information.
2 Proposed approach
The most important problem that this doctorate research work is trying to solve
is how to create an educational tool search engine able to automatically collect
information from third-party external data repositories. Obviously, the problem
of integrating external data does not only affect to the educational domain; it
is a very important problem to solve related to the information retrievement
and data management. The Linked Data [3] approach is a recent proposal that
is expected to facilitate the automatic access to the information published in
external repositories.
Linked Data is a methodology for publishing data in the Semantic Web [4].
Its key idea is to identify concepts (both data and meta-data) with URIs and
reuse URIs defined by external data providers. Following this approach, when
two repositories have information referred to the same entity, they will use the
same URI to define it and thus a software agent could automatically retrieve
the information related to a concept published in different data registries. This
proposal has been widely adopted and many data providers are linking their
3
http://desktop.google.com/plugins/
4
http://widgets.yahoo.com/
5
http://gsic.uva.es/ontoolsearch
80
datasets according to these principles, building the Web of Data, which is moti-
vated by the Linking Open Data Project6 .
In the Web of Data there are several interlinked data repositories with infor-
mation from multiple domains. Even if none of them provide specific information
about educational tools, there are some data repositories where useful informa-
tion of software tools is registered. One of these datasets is DBpedia7 , where
up-to-date structured information extracted from Wikipedia is freely available.
A key step to solve the proposed research question is to design a search system
able to extract structured data from different sources from the Web of Data, such
as Dbpedia, and automatically relate the data to the system internal vocabulary.
Note that the data extraction from each dataset will not be ad-hoc implemented
because, as different data sources are linked, a single software agent can extract
information from several datasets.
However, there is no data registry in the Web of Data that describes software
tools contemplating their educational capabilities, nor there is any that give
details about how to integrate them in a VLE. So that, the support of searching
tools using educational abstractions will be limited. In order to solve this problem
a search engine is proposed; this search engine will have a collection of adaptors
that will allow to automatically extract data from different sources. Moreover,
in order to complete the description of software tools , teachers can publish their
educational capabilities and technical users can give details of how to integrate
them in a learning environment. This way, a new interlinked dataset will be
created, containing information with a specific purpose and reusing information
from multiple previously available data repositories.
3 Methodology
In order to design, develop and evaluate an educational tool search system, the
doctorate research is being iteratively performed according to the methodology
in engineering [1], following the next steps:
1. Research problem definition. The first stage consists on the definition of a
relevant research problem after exploring the literature. The problem stated
is how to retrieve useful information for the selection of learning tools and
their integration in VLEs.
2. Solution proposal. The second stage tries to overcome the problem found
with a solution proposal. A software that supports the information retrieval
from third-party external data sources, as well as the publication of ed-
ucational information following the Linked Data principles is the current
proposal for the problem.
3. Solution design and development. This stage consists on the design of the
solution proposed in the previous stage and also implies the development of
a prototype. Therefore, a prototype of the architecture, including the search
6
http://linkeddata.org
7
http://dbpedia.org/About
81
engine and some adaptors will be developed. Moreover, the integration of
the prototype in at least a VLE will be carried out.
4. Solution assessment. The last stage shows that the solution overcomes the
problems that were detected in the first stage of this methodology. In this
context, the system should be able to automatically retrieve and integrate
information from different sources and to registry educational information
about the tools following the Linked Data principles.
The whole picture of the research proposal is represented in Figure 1.
Fig. 1. Doctorate research schema.
4 Results already reached
Doctorate research has been working on some of the partial objectives described
in Section 2. Specifically, previous work has focussed on the detection of the
information requirements for the tool integration in VLEs and in the design of
the search engine architecture.
In order to detect the information that should be provided by the system,
some real examples were studied where a tool is published by a tool provider,
found and selected by a teacher and later on integrated in a VLE. Furthermore,
an analysis of the literature was carried out. Out of this review the tool informa-
tion requirements were established: the description of the tool should contem-
plate both functional, technological and administrative parameters of the tool.
82
Once the information requirements were analyzed, an ontology was design in or-
der to define a vocabulary that can be used by the search system to describe the
learning tools. This ontology reuses other conceptualizations that can be found
in the literature; for example, Ontoolcole [10] is used to define the educational
concepts related to the tools while Dublin Core [6] provides the vocabulary of
the administrative domain. Nonetheless, a conceptualization for describing the
technical parameters has been specifically defined since there was not found any
ontology that defines the needed concepts.
As far as the search engine design concerns, the proposed architecture, which
is based on papers such as [9], is shown in Figure 2. The search engine has a cen-
tral manager that collects the query made by the teacher through its interface
and coordinates the data retrievement. The central manager sends the query
using a common language, define by the abovementioned ontology, to several
adaptors (two in the example of the Figure 2), which mediate in the data ex-
change between the manager and the external data sources. Finally, there is an
educational data registry, which contains educational data about software tools
and enriches the information about tools provided by external data repositories.
Fig. 2. Current version of the search engine architecture.
5 Conclusions and future work
The present paper shows an ongoing doctorate research work. A research ques-
tion was detected, which consists on the design of an educational tool search
engine able to automatically collect information from external data repositories.
The proposed approach to solve this problem is based on the Linked Data prin-
83
ciples because it is a recent trend that allows software agents to automatically
retrieve information from the Web of Data.
This approach overcomes the detected problems in current educational tool
search systems, such as OntoolSearch: firstly, it is possible to find educational
tools that were not specifically described in the system’s data source; secondly,
data maintenance will be facilitated, as the system is able to automatically
import up-to-date information; finally, the publication of educational tool infor-
mation will be easier, since it will be possible to reuse the data retrieved from
external registries, so it will only be necessary to registry the tools educational
aspects. In addition, all the information created by the system will be published
and will be freely available on the Web, so it could be reused by other people
for some other educational applications.
Future work will focus on the implementation of the search system described
in Section 4, taking into account the proposed architecture and the designed
ontology. In addition, the integration of the search system in at least a VLE will
be an interesting task to be carried out.
References
1. W.R. Adrion. Research methodology in software engineering: summary of the
Dagstuhl workshop on future directions on software engineering. SIGSoft Software
Engineering Notes, 18(1):36–37, January 1993.
2. C. Alario Hoyos, J.I. Asensio Pérez, M.L. Bote Lorenzo, E. Gómez Sánchez,
G. Vega Gorgojo, and A. Ruiz Calleja. Integration of external tools in virtual
learning environments: main design issues and alternatives. In Proceedings of 10th
International Conference on Advanced Learning Technologies (ICALT), Sousse,
Túnez, July 2010.
3. T. Berners-Lee. Linked Data - Design Issues, July 2007. URL =
http://www.w3.org/DesignIssues/LinkedData.html, última visita junio de 2010.
4. T. Berners-Lee, J. Hendler, and O. Lassila. The semantic web. Scientific American,
284(5):34–43, 2001.
5. Miguel L. Bote-Lorenzo, Eduardo Gómez-Sánchez, Guillermo Vega-Gorgojo, Yan-
nis A. Dimitriadis, Juan I. Asensio-Pérez, and Iván M. Jorrı́n-Abellán. Gridcole: A
tailorable grid service based system that supports scripted collaborative learning.
Computers & Education, 51(1):155 – 172, 2008.
6. DCMI Usage Board. DCMI metadata terms. Specification, DCMI, January 2008.
URL = http://dublincore.org/documents/dcmi-terms/, last visited July 2010.
7. P. Dillenbourg. Virtual learning environments. In Learning in the New Millen-
nium: Building New Education Strategies for Schools. EUN Conference Workshop
on Virtual Learning Environments, Rhodes, Greece, 2000.
8. D. Fensel. Ontologies: A Silver Bullet for Knowledge Management and Electronic
Commerce. Springer-Verlag, Berlin, Germany, second edition, 2004.
9. W. Meng, C. Yu, and K.L. Liu. Building efficient and effective metasearch engines.
ACM Computing Surveys (CSUR), 34(1):48–89, 2002.
10. G. Vega-Gorgojo, M. L. Bote-Lorenzo, E. Gómez-Sánchez, J. I. Asensio-Pérez,
Y. A. Dimitriadis, and I. M. Jorrı́n-Abellán. Ontoolcole: Supporting educators
in the semantic search of CSCL tools. Journal of Universal Computer Science
(JUCS), 14(1):27–58, 2008.
84