The goal of the semantic web is to take advantage of formalised knowledge (in languages like RDF) at the scale of the worldwide web. In particular, it is based on ontologies which define concepts used for representing knowledge on the web, e.g., for annotating a picture, specifying a web service interface or expressing the relation between two persons. As shown by many uses of semantic web resources, it is currently growing at a steady pace involving together linked data, ontologies and alignments between ontologies.
Indeed, different information sources and different actors in different contexts use different ontologies. It is thus necessary to record alignments between these ontologies [Euzenat & Shvaiko, 2013]. Similarly, an important task consists of finding links between data. This can be helped by knowing the alignments between ontologies describing them [Atencia et al., 2014].
The result is a mesh of relations which rely on each others. Moreover, data sources, ontologies and alignments change over time. It is thus very important to know how to react or anticipate this evolution.
We have designed and implemented an alignment server [1] for the semantic web [David et al., 2011] which allows for sharing alignments between ontologies. It is used, in the context of Smart cities for instance, by projects which maintain reasonable alignments. We plan to enhance it to collect, generate and maintain automatically networks of ontologies. In particular, we would like to provide it with a self-feeding mechanism able to access ontology sources, e.g., LOV [2], automatically and to generate a network of alignments between these ontologies. We also like the system to react when an ontology or a data source changes. This is by itself an exciting research topic.
In addition, such an infrastructure may be used for many purposes, such as:
The successful candidate will have to research along the lines of developing deeper this infrastructure so that it offers a constantly evolving picture of available resources.
This may involve cooperation with researchers in European (Ready4SmartCities) and National (Lindicle) projects.
On the application side, we plan to apply such an infrastructure to collect ontologies in the domain of energy management in smart cities as well as LOV integration.
References:
[Atencia et al., 2014] Manuel Atencia, Jérôme David, Jérôme Euzenat,
Data interlinking through robust linkkey extraction, in: Proc. 21st european conference on artificial intelligence (ECAI), Praha (CZ), pp15-20, 2014
[David et al., 2010] Jérôme David, Jérôme Euzenat, Ondrej
Sváb-Zamazal, Ontology similarity in the alignment space, in: Proc. 9th conference on international semantic web conference (ISWC), Shanghai (CN), Lecture notes in computer science 6496:129-144, 2010
[David et al., 2011] Jérôme David, Jérôme Euzenat, François Scharffe,
Cássia Trojahn dos Santos, The Alignment API 4.0, Semantic web journal 2(1):3-10, 2011
[Euzenat & Shvaiko, 2013] Jérôme Euzenat, Pavel Shvaiko, Ontology
matching, 2nd edition, Springer-Verlag, Heildelberg (DE), 2013
[Locoro et al., 2014] Angela Locoro, Jérôme David, Jérôme
Euzenat, Context-based matching: design of a flexible framework and experiment, Journal on data semantics 3(1):25-46, 2014
Links
Qualification: PhD or equivalent in computer science. Knowledge in semantic web technologies largely welcome.
Researched skills:
Hiring date: as soon as possible.
Place of work: The position is located at INRIA Rhône-Alpes, Montbonnot (near Grenoble, France) a main computer science research lab, in a stimulating research environment. Research will be carried out in the Exmo team under the supervision of Jérôme David and Jérôme Euzenat.
Duration: 18 months (hiring opportunities afterwards)
Salary: From 2125 EUR/month (benefits included, net before income tax), i.e., 2621 EUR/month gross.
Contact: For further information, contact Jerome:David#inria:fr or Jerome:Euzenat#inria:fr.
Procedure: Contact us. Visit INRIA's presentation (including FAQ and forms).
File: Provide Vitæ, motivation letter, 2 relevant or significant publications and reference letters.
INRIA Grenoble Rhône-Alpes Priority research themes:
Our team resort to "Internet of things: new wireless technologies, web semantics and privacy", however this new activity is also related to "Robot sharing our workspace and living space" and "Learning and distributed optimisation for large scale systems".