=Paper=
{{Paper
|id=Vol-1741/jist2016pd_paper4
|storemode=property
|title=SPARQL Builder: Constructing SPARQL Query by Traversing Class-Class Relationships for Life Science Databases
|pdfUrl=https://ceur-ws.org/Vol-1741/jist2016pd_paper4.pdf
|volume=Vol-1741
|authors=Atsuko Yamaguchi,Kouji Kozaki,Kai Lenz,Yasunori Yamamoto,Hiroshi Masuya,Norio Kobayashi
|dblpUrl=https://dblp.org/rec/conf/jist/YamaguchiKLYMK16a
}}
==SPARQL Builder: Constructing SPARQL Query by Traversing Class-Class Relationships for Life Science Databases==
https://ceur-ws.org/Vol-1741/jist2016pd_paper4.pdf
SPARQL Builder: Constructing SPARQL Query
by Traversing Class–Class Relationships for Life
Science Databases
Atsuko Yamaguchi1 , Kouji Kozaki2 , Kai Lenz3 , Yasunori Yamamoto1 ,
Hiroshi Masuya4,3 , and Norio Kobayashi3,4,5
1
Database Center for Life Science (DBCLS),
Research Organization of Information and Systems,
178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871 Japan
{atsuko,yy}@dbcls.rois.ac.jp
2
The Institute of Scientific and Industrial Research (ISIR), Osaka University,
8-1 Mihogaoka, Ibaraki, Osaka, 567-0047 Japan
kozaki@ei.sanken.osaka-u.ac.jp
3
Advanced Center for Computing and Communication (ACCC), RIKEN,
2-1 Hirosawa, Wako, Saitama, 351-0198 Japan
{kai.lenz, norio.kobayashi}@riken.jp
4
RIKEN BioResource Center (BRC),
3-1-1, Koyadai,Tsukuba, Ibaraki, 305-0074 Japan
hmasuya@brc.riken.jp
5
RIKEN CLST-JEOL Collaboration Center,
6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan
Abstract. Linked Open Data (LOD), a powerful mechanism for linking
different datasets published on the World Wide Web, is expected to in-
crease the value of data through mashups of various datasets on the Web.
One of the important requirements for LOD is to be able to find a path of
resources connecting two given classes. Because each class contains many
instances, inspecting all of the paths or combinations of the instances re-
sults in an explosive increase of computational complexity. To solve this
problem, we have proposed an efficient method that obtains and prior-
itizes a comprehensive set of connections over resources by traversing
class–class relationships of interest. Based on the method, we developed
a system for constructing a SPARQL query named SPARQL Builder. We
showcase how to generate a SPARQL query according to user’s interest
by using the SPARQL Builder system.
Keywords: linked data, class–class relationships, data integration
1 Introduction
In order to efficiently use databases published as Linked Open Data (LOD),
the users need to be allowed to obtain data in the flexible way according to
their interests. An important case is to find paths of links between instances
(resources) whose types are given two classes for integrative data analysis with
semantics. These paths can be obtained by retrieving chains of properties (links)
which connect instances of classes. In other words, these paths can be obtained
by traversing paths of class–class relationships over the LOD.
Therefore, based on class–class relationships, we have been developping a
system named SPARQL Builder to obtain data from LOD flexibly, by assisting
users in writing SPARQL queries to the SPARQL endpoints. To realize our ap-
proach, we should develop the following two techniques: 1) a method to collect
profiles related to class–class relations through SPARQL endpoints of RDF data-
sets: This is implemented as SPARQL Builder Metadata (SBM), which describes
comprehensive metadata including not only class definitions but also statistics
such as the number of instances while it is not supported existing metadata. 2) a
method to obtain chains of properties and classes by computing paths on labeled
multigraph named class graph: This enables an efficient method to compute path
and a measure to remove paths of classes with no instance path are proposed.
Related application includes Visor[1], which enables users to browse RDF
datasets in the light of class–class relationships. However, Visor doesn’t provide a
method to find an end-to-end path through multiple resources. Although another
related work is RelFinder [2] which computes paths between resources in LOD, it
is not based on class–class relationships but on instance–instance relationships.
2 SPARQL Builder
We have been developing a prac-
tical LOD search tool named
SPARQL Builder for the life-
science data analysis (http://
www.sparqlbuilder.org/). This
tool provides an interactive GUI
that allows users who are not fa-
miliar with SPARQL language to
generate SPARQL queries without
knowledge of SPARQL and RDF
data schema [3]. Overview of sys-
tem architecture is shown in Fig 1.
SPARQL Builder manages SBM
generated by accessing SPARQL
endpoints in advance (1). When Fig. 1. Overview of the SPARQL Builder sys-
a user access to the SPARQL tem.
Builder system via a web browser
as a GUI, SPARQL Builder ob-
tains a list of classes by analysing SBM (2) and displays the list on the user’s web
browser (3). Then, when the user selects ”input” and ”output” classes, SPARQL
Builder constructs class paths by traversing the class graph constructed using
information described in SBM (4) and draw them on the web browser. Using
this GUI, users can explore datasets as their interest by specifying classes. If a
user interested in the interrelationships between molecular pathways and pro-
teins, he should do at first is to select Protein as input class and Pathway as
output class. Then, SPARQL Builder shows all possible paths involves pathways
in which proteins that catalyses chemical reactions constitutes. These paths has
sequentially connected two relationships as the form of ”Protein -(left/right)-
BiochemicalReaction -(pathwayComponnt)- Pathway”. When he select one of
the class paths, SPARQL Builder create a SPARQL query which can use to re-
trieve data his interest. SPARQL Builder is used for support service to generate
SPARQL queries for 38 SPARQL endpoints as of July 2016.
3 SPARQL Builder Metadata
SPARQL Builder Metadata (SBM), is a summary of RDF datasets provided via
a SPARQL endpoint. SBM is defined as an extension of VoID (https://www.w3.
org/TR/void/) and SPARQL 1.1 service description (https://www.w3.org/TR/
sparql11-service-description/) with our original vocabulary whose name
space is sbm:. SBM contains statistic summary data called “graph summary” for
default graph and each named graph provided by the SPARQL endpoint. Graph
summary is an extension of VoID vocabulary related to void:Dataset class
with detailed statistical parameters as follows: A property partition is a subset
of RDF dataset associated with a property. In addition to original VoID prop-
erties, three properties sbm:subjectClasses, sbm:objectClasses, and sbm:
objectDatatypes to describe numbers of classes and datatypes are used. A
class relation is a distinct pair of a subject class and an object class/datatype,
where subject class and object class/datatype are the class of subject instances
and class/datatype of object instances/literals in all triples associated with the
concerned property partition. sbm:classRelation property is introduced to de-
scribe each class relation with properties sbm:subjectClass, sbm:objectClass,
and sbm:objectDatatype as our original extension and properties VoID vocab-
ulary.
4 Class Graph
To compute paths between two classes efficiently, we employed a specialized
graph whose nodes and edges correspond to classes and the class–class relations
with predicates, respectively. We call the graph class graph. A class graph can be
constructed from SBM efficiently because SBM includes a list of all the classes
and a list of all the class–class relationships. Given a class graph, an undirected
path on the graph is called as a class path. Note that a class path is not always
simple path because the same classes may appear twice or more in the path with
different properties. Class paths between two classes can be found in practically
short time using algorithm written in [4] although a class graph is a labeled
multi-edge graph and a class path is not simple.
5 Conclusion
We introduced SPARQL Builder which enables practical LOD data searching in
a SPARQL endpoint. Although the system originally was designed for biological
databases, the technologies used in the system including SBM and class graphs
are applicable to another domain. Therefore, our future work includes expand-
ing our application into multiple domains and evaluate the generalities of our
approach. In addition, we will consider to expand class paths into more general
types of subgraphs on class graph, to support more styles of SPARQL queries.
In addition, supporting federated search also remains as future work.
Acknowledgments This work was supported by JSPS KAKENHI Grant Num-
ber 25280081, 24120002 and the National Bioscience Database Center (NBDC)
of the Japan Science and Technology Agency (JST).
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