MCHA SPAIDA:
    A Cooperative Query Editor with Anonymous
         Helpers using Ontology Mappings

                        Takuya Adachi1 and Naoki Fukuta2
1
    Department of Informatics, Graduate School of Integrated Science and Technology,
                                 Shizuoka University
          2
            College of Informatics, Academic Institute, Shizuoka University
                {adachi.takuya.17@,fukuta@inf.}shizuoka.ac.jp



        Abstract. In this paper, we propose our prototype system, named MCHA
        SPAIDA, that allows us for cooperatively editing SPARQL queries by the
        help of anonymous helper users without revealing the detailed meaning
        of the query. This system dynamically generates ontology mappings to
        translate a modified query by using a query and some data on an end-
        point. Ontology matching approaches have been applied to effectively
        anonymize the query to be cooperatively edited by other users without
        loss of semantic relations among data and vocabularies. To make ease of
        cooperative tracing and profiling of a query, our method will not directly
        modify the queries and given ontology mappings. Rather, our method
        tries to add a small amount of supplemental ontology mappings to effec-
        tively anonymize the meaning of original query.


Keywords: SPARQL, ontology mapping, cooperative query editing, privacy
protection, query anonymization


1     MCHA SPAIDA

To overcome the issues, we are implementing a system named MCHA SPAIDA3 ,
which is an extended version of our previously implemented system SPAIDA
for utilizing ontology mappings on SPARQL queries[1–3] which also includes
anonymous helper mechanism MCHA for cooperatively editing and sophisticat-
ing queries. Our system includes an “on-the-fly” ontology and instance matcher
to evaluate the used ontology mappings and instance mappings, suggests which
mappings will be used in the query. Furthermore, the on-the-fly matcher can
also be used to interactively add one-time mappings that could produce more
complete answer in the results of the specified query [1].
    We are implementing a prototype system as a web application with SPARQL
query editors and anonymous helpers. In order to utilize alignments as mapping
data by using ontology matching tools (e.g., Alignment API [4]) and instance
3
    A demo is available at http://whitebear.cs.inf.shizuoka.ac.jp/spaida-demo/
2       T. Adachi and N. Fukuta

matching tools (e.g., ScLink [5]), SPAIDA prepares mapping repositories to the
outside.
   Figure 1 shows an overview of our implementing system.




                  Fig. 1. An overview of our implementing system
2   Dynamic Mapping Generation
An application of the on-the-fly mapping generation mechanism is MCHA (Mapping-
based Conversion for Human-based query writing Assistance), which rather con-
vert a query to another query which targets to completely different things while
it tries to keep their attributes in the sense of complexity and structure of the
output. This allows anonymous cooperative helper editing of a query while mit-
igating the targets the original user is trying to access. In this mechanism, some
users are asked to help editing and enhancing a query of mapping-based conver-
sion of a query to a “semantically equivalent or very similar” query.
References
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