Semantic framework for mapping object-oriented model to semantic web languages
Status PubMed-not-MEDLINE Language English Country Switzerland Media electronic-ecollection
Document type Journal Article
PubMed
25762923
PubMed Central
PMC4340193
DOI
10.3389/fninf.2015.00003
Knihovny.cz E-resources
- Keywords
- EEG/ERP portal, electrophysiology, object-oriented code, ontology, semantic framework, semantic web,
- Publication type
- Journal Article MeSH
The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.
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Adida B., Birbeck M., McCarron S., Herman I. (2013). RDFa Core 1.1. Syntax and processing rules for embedding RDF through attributes, W3C Recommendation, 2nd Edn. Available online at: http://www.w3.org/TR/rdfa-core/
Antoniou G., van Harmelen F. (2004). A Semantic Web Primer (Cooperative Information Systems Series). Cambridge, MA: The MIT Press.
Apache Jena Project Team (2011). Apache Jena - A Free and Open Source Java Framework for Building Semantic Web and Linked Data Applications. Available online at: http://jena.sourceforge.net/index.html
Bauer C., King G. (2006). Java Persistence with Hibernate. Greenwich, CT: Manning Publications Co.
Beckett D. (2004). RDF/Xml Syntax Specification (Revised). W3C recommendation, W3C. Available online at: http://www.w3.org/TR/REC-rdf-syntax/
Berners-Lee T., Hendler J., Lassila O. (2001). The semantic web. Sci. Am. 284, 34–43 10.1038/scientificamerican0501-34 PubMed DOI
Berners-Lee T. (2006). Designed Issues: Linked Data. Available online at: http://www.w3.org/DesignIssues/LinkedData.html
Biller H., Neuhold E. (1977). Architecture and Models in Data Base Management Systems: Proceedings of the IFIP Working Conference on Modelling in Data Base Management Systems. Holland: Distributors for the U.S.A. and Canada, Elsevier/North Holland.
Bizer C., Seaborne A. (2004). D2RQ-treating non-RDF databases as virtual RDF graphs, in Proceedings of the 3rd International Semantic Web Conference (ISWC2004) (Hiroshima: Citeseer; ).
Bjaalie J. G., Grillner S. (2007). Global neuroinformatics: the international neuroinformatics coordinating facility. J. Neurosci. 27, 3613–3615. 10.1523/JNEUROSCI.0558-07.2007 PubMed DOI PMC
Bock C., Cook S., Rivett P., Rutt T., Seidewitz E., Selic B., et al. (2013). OMG Unified Modeling Language (OMG UML), Version 2.5. Available online at: http://www.omg.org/spec/UML/2.5/Beta2/PDF/
Brinkman R., Courtot M., Derom D., Fostel J., He Y., Lord P., et al. . (2010). Modeling biomedical experimental processes with OBI. J. Biomed. Semant. 1(Suppl. 1):S7. 10.1186/2041-1480-1-S1-S7 PubMed DOI PMC
Chandrasekaran B., Josephson J., Benjamins V. (1999). What are ontologies, and why do we need them? IEEE Intell. Syst. Appl. 14, 20–26 10.1109/5254.747902 DOI
Dean M., Schreiber G. (2004). OWL Web Ontology Language Reference. W3C recommendation, W3C. Available online at: http://www.w3.org/TR/owl-ref/
Dou D., Frishkoff G. A., Rong J., Frank R., Malony A. D., Tucker D. M. (2007). Development of neuroelectromagnetic ontologies(nemo): a framework for mining brainwave ontologies, in Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, eds Berkhin P., Caruana R., Wu X. (San Jose, CA: ACM; ), 270–279 10.1145/1281192.1281224 DOI
Ebel M., Hulin M. (2012). Combining relational and semi-structured databases for an inquiry application, in Multidisciplinary Research and Practice for Information Systems, Vol. 7465 of Lecture Notes in Computer Science, eds Quirchmayr G., Basl J., You I., Xu L., Weippl E. (Berlin; Heidelberg: Springer; ), 73–84.
Garcia S., Fourcaud-Trocm N. (2009). Openelectrophy: an electrophysiological data- and analysis-sharing framework. Front. Neuroinform. 3:14. 10.3389/neuro.11.014.2009 PubMed DOI PMC
Gardner D., Akil H., Ascoli G., Bowden D., Bug W., Donohue D., et al. . (2008). The neuroscience information framework: a data and knowledge environment for neuroscience. Neuroinformatics 6, 149–160. 10.1007/s12021-008-9024-z PubMed DOI PMC
Grewe J., Wachtler T., Benda J. (2011). A bottom-up approach to data annotation in neurophysiology. Front. Neuroinform. 5:16. 10.3389/fninf.2011.00016 PubMed DOI PMC
Gupta A., Bug W., Marenco L., Qian X., Condit C., Rangarajan A., et al. . (2008). Federated access to heterogeneous information resources in the neuroscience information framework (nif). Neuroinformatics 6, 205–217. 10.1007/s12021-008-9033-y PubMed DOI PMC
Horridge M., Bechhofer S. (2011). The owl api: a java api for owl ontologies. Semant. Web 2, 11–21. 10.3233/SW-2011-0025 PubMed DOI
JenaBean Team (2010). Jenabean - Project Hosting on Google Code. Available online at: http://code.google.com/p/jenabean/
Jezek P., Moucek R. (2011a). Semantic web in eeg/erp portal: ontology development and nif registration, in 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI), Vol. 4, (Shanghai: ), 2058–2062.
Jezek P., Moucek R. (2011b). Transformation of object-oriented code into semantic web using java annotations, in 13th International Conference on Enterprise Information Systems (ICEIS) (4), eds Zhang R., Cordeiro J., Li X., Zhang Z., Zhang J. (Beijing: SciTePress; ), 207–210.
Jezek P., Moucek R. (2012). System for EEG/ERP data and metadata storage and management. Neural Netw. World 22, 277–290 10.14311/NNW.2012.22.016 DOI
Kalyanpur A., Pastor D. J., Battle S., Padget J. A. (2004). Automatic mapping of OWL ontologies into Java, in Proceedings of the 16th International Conference on Software Engineering & Knowledge Engineering (SEKE'2004), eds Maurer F., Ruhe G. (Banff, AB: ), 98–103.
Koide S., Aasman J., Haflich S. (2005). Owl vs. object orientated programming, in International Semantic Web Conference, Workshop1: Semantic Web Enabled Software Engineering (Galway: ).
Le Franc Y., Bandrowski A., Bruha P., Papež V., Grewe J., Moucek R., et al. (2014). Describing neurophysiology data and metadata with oen, the ontology for experimental neurophysiology. Front. Neuroinform. 8:44 10.3389/conf.fninf.2014.18.00044 DOI
Liu F., Wang J., Dillon S. T. (2007). Web information representation, extraction and reasoning based on existing programming technology, in Computational Inteligence 37, eds Jie L., Guangquan Z., Da R. (Berlin: ), 147–168.
Manola F., Miller E. (eds.). (2004). RDF Primer. W3C Recommendation. World Wide Web Consortium. Available online at: http://www.w3.org/TR/rdf-primer/
Marenco L., Wang R., Shepherd G., Miller P. (2010). The nif disco framework: facilitating automated integration of neuroscience content on the web. Neuroinformatics 8, 101–112. 10.1007/s12021-010-9068-8 PubMed DOI PMC
MicroSystems S. (2008). Annotations (The Java Tutorials, Learning the Java Language, Classes and Objects). Available online at: http://docs.oracle.com/javase/tutorial/java/annotations/
Moucek R., Bruha P., Jezek P., Mautner P., Novotny J., Papez V., et al. . (2014). Software and hardware infrastructure for research in electrophysiology. Front. Neuroinform. 8:20. 10.3389/fninf.2014.00020 PubMed DOI PMC
Neuroinformatics group, University of West Bohemia, (2014). EEG/ERP Portal (EEGBase). Available online at: http://eegdatabase.kiv.zcu.cz
Object Management Group, (2009). Ontology definition metamodel (omg) version 1.0. Technical Report formal/2009-05-01, Object Management Group.
Ohlbach H. J. (2012). Java2owl: a system for synchronising java and owl, in 4th International Conference on Knowledge Engineering and Ontology Development (KEOD), eds Filipe J., Dietz J. L. G. (Barcelona: SciTePress; ), 15–24.
Ontology for Experimental Neurophysiology Working Group. (2013). Ontology for Experimental Neurophysiology. Available online at: https://github.com/G-Node/OEN
Open Knowledge Foundation. (2014). Availability of SPARQL Endpoint. Available online at: http://sparqles.okfn.org/availability
Papailiou N., Konstantinou I., Tsoumakos D., Koziris N. (2012). H2rdf: adaptive query processing on rdf data in the cloud, in Proceedings of the 21st International Conference Companion on World Wide Web, WWW '12 Companion, (New York, NY: ACM; ), 397–400.
Po-Huan C., Chi-Chuan L., Kuo-Ming C. (2009). Integrationg semanic web and object-oriented programming for cooperative design. J. Univ. Comput. Sci. 15, 1970–1990 10.3217/jucs-015-09-1970 DOI
Prud'hommeaux E., Seaborne A. (2008). Sparql Query Language for Rdf. W3c recommendation, W3C. Available online at: http://www.w3.org/TR/rdf-sparql-query/
Scott T. (2004). Python: the good, the bad, and the not ugly: conference workshop. J. Comput. Sci. Coll. 20, 288–290. PubMed
Simsion G., Witt G. (2004). Data Modeling Essentials, 3rd Edn. Burlington, MA: Morgan Kaufmann.
Solid IT, (2014). DB Engines - Knowledge Base of Relational and NoSQL Database Management Systems.
SUN. (2006). Java Tutorial Trail: The Reflection API. SUN Microsystems. Available online at: http://java.sun.com/docs/books/tutorial/reflect/index.html
Švihla M. (2007). Transforming Relational Data into Ontology Based RDF. thesis. CTU Prague.
Teeters J., Harris K., Millman K., Olshausen B., Sommer F. (2008). Data sharing for computational neuroscience. Neuroinformatics 6, 47–55. 10.1007/s12021-008-9009-y PubMed DOI
The European Bioinformatics Institute. (2014). RDF Platform. Available online at: http://www.ebi.ac.uk/rdf/