=Paper=
{{Paper
|id=None
|storemode=property
|title=SemScape: Visualizating Semantic Web Data Landscapes with Cytoscape 3.0
|pdfUrl=https://ceur-ws.org/Vol-952/paper_43.pdf
|volume=Vol-952
|dblpUrl=https://dblp.org/rec/conf/swat4ls/SplendianiWHD12
}}
==SemScape: Visualizating Semantic Web Data Landscapes with Cytoscape 3.0==
https://ceur-ws.org/Vol-952/paper_43.pdf
SemScape: Visualizating Semantic Web Data
Landscapes with Cytoscape 3.0
Andrea Splendiani12 , Andra Waagmeester3 , Carina Haupt4 , and Helena Deus1
1
DERI, Galway, Ireland
2
intelliLeaf ltd, Cambridge, UK
3
Maastricht University, NL
4
Bonn-Aachen Institute for Information Technology, University of Bonn, DE
Abstract. Core to the success of applying Semantic Web technologies
(SWT) towards supporting Life Sciences research is the availability of
tools that lower the entry barrier for adoption by biomedical researchers.
Researchers need to easily and intuitively exploit and query the wealth
of data that is available behind as SPARQL endpoints. Here, we present
SemScape, a semantic-web enabled plugin for the popular network biol-
ogy software Cytoscape. SemScape can be used to query any knowledge
bases with a SPARQL endpoint by leveraging familiarity with existing
software and intuitiveness of big data exploitation through a mechanism
that encapsulates the complexity of data in parametric context depen-
dent queries. We believe SemScape can provide a valuable resource both
for data consumers and data publishers.
1 Introduction
The Semantic web and linked data efforts in Life Sciences domains have produced
a large amount of structured information ready for querying. However, the entry
barrier for researchers willing to use this information on their daily tasks is too
great still, posing a particular problem for user interaction and query assembly,
especially in the Life Sciences domain. Despite the well-recognized advantages of
Linked Data and RDF formalisms in enabling the seamless aggregation of data
from multiple distributed sources, these formalisms inherently rely on a format
that sets data free from the shackles of a predefined schema.
As a side-effect, data represented in these formats is challenging to query since
users cannot rely on organized data maps made available a-priori. While on-
tologies can provide such a map, there is still a disconnect between ontologies
proposed by the semantic web communities, and the data descriptors that are
actually used in RDF representations. As such, it is difficult to find ontologies
that encompasses and arbitrary mashup of data, which is typical scenario for
the use of data published in RDF, in the Life Sciences and beyond. In the life
sciences domain, the problem is further compounded by the realization that po-
tential users of the data are typically not experts in semantic technologies, and
ease of use as well as domain oriented interfaces are even more relevant.
Hence the need for tools that provide an accessible interface to semantic web
2
knowledge bases, that can help in discovery the information structure and nav-
igate it, as well as put into context with the typical work environment of re-
searchers.
2 Results
We have developed SemScape, a plugin for the popular network biology software
Cytoscape [?], which allows user interaction and queries over remote endpoints.
Cytoscape is a network visualization and analysis tool that, while inherently
domain independent, provides links and shortcuts to typical biomedical datasets
and manipulations. It offers a plugin architecture and has a very active commu-
nity both of developers and users. SemScape is developed as plugin for the latest
version of Cytoscape, 3.0, which is released in beta at the time of this writing
and present a completely new architecture from previous versions.
SemScape offers a range of functionalities, which are derived from what was
implemented in RDFScape [?] and AGUIA [?]. However this system provides
a newer, more efficient and up to date implementation. The functionalities of
SemScape can be categorized essentially in discovery and navigation of linked
data landscapes.
Discovery functions are based on the automatic extraction of a data map (typi-
cally types and relations from a given endpoint).
Navigation functions are based on contextual menus that can be configured
by users and data publishers: when right-selecting a node, the system uses at-
tributes of the node (e.g. its type) to look into a query library for queries that
can be applied to the node. E.g.: if the node is a protein, the system may find
queries for interacting proteins. In general for each resource simple queries such
as all statements including the resource as object or subject are provided. Once
a selection is performed, results are used to expand the graph, and provenance
information is kept for each new element visualized (which in turns allow new
contextual queries to the original endpoint). In particular, queries are written
as parametric queries, and can be provided by data publisher as a package to
which the user can subscribe. For instance a pathway resource provider may
provide, together with an endpoint, a set of preconfigured queries to drive user
interaction on its knowledge base. The user can keep track of such preconfigured
packages and update them if newer versions are proposed by the data publisher.
Together with the possibility to execute and visualize generic SPARQL queries,
SemScape allow the possibility to extract and define data landscapes, graphs
visualizing the semantic links between data sets in a given context (e.g. Cancer).
3 Conclusions
SemScape is a robust plugin developed on the newer version of the widely used
network tool Cytoscape and it inherits in its design the experience of several
experiments in user interaction of the Semantic Web. We believe it will be a
3
valuable resource for Life Science researchers willing to make use of these tech-
nologies.
4 Availability
SemScape is available http://code.google.com/p/vsdlc3/ and released under the
Apache License 2.0.
5 Acknowledgments
This work was supported by the Google Summer of Code program and all de-
veloplment is by Yigang Zhou. We wish to thank Alex Pico for his support in
the GSoC program.
References
1. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N,
Schwikowski B, Ideker T: Cytoscape: a software environment for integrated
models of biomolecular interaction networks. Genome Research. 13(11) (2003)
2498–504 .
2. Splendiani A: RDFScape: Semantic Web meets Systems Biology BMC Bioin-
formatics 9(Suppl 4) (2008) S6
3. Correa MC, Deus HF,Vasconcelos AT, Hayashi Y, Ajani JA, Patnana SV,
Almeida JS: AGUIA: autonomous graphical user interface assembly for clinical
trials semantic data services. BMC Medical Informatics and Decision Making.
10:65 (2010) .