PhD position in Semantic Web, Web of Data, Linked Data, Ontologies

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PhD position in Semantic Web, Web of Data, Linked Data, Ontologies

Ioanna Lytra

PhD studentship proposal

Within the University de Lyon (France), the University Jean Monnet is searching for a full-time PhD student on the topic: A collaborative framework for ontology and instance data co-evolution and extraction for a joint PhD with the University of Bonn.

== Essential Facts ==

Connected Intelligence team:

Enterprise Information Systems team:

The position is offered in the frame of a French-German doctoral college (SeReCo: Semantics, Reasoning and cooperation. supported by the French-German University (DFH/UFA) and involving the research teams Connected Intelligence (Saint-Étienne, France) and Enterprise Information Systems (Bonn, Germany).

The topic of the PhD covers the domains: Semantic Web, Web of Data, Linked Data, ontologies, knowledge engineering, collaborative authoring, knowledge extraction, ontology evolution.

The PhD student will spend 3 years on the topic. He/She will have the chance to visit the University of Bonn (and the Fraunhofer IAIS). A double PhD degree with the University of Bonn is planned with this position (with at least 1 semester spent in Bonn).

The gross monthly salary is about 1684€ (up to 2000€ with tutoring) including social security etc.

Low tuition fees (about 400€/year), cheap housing possibilities, and addition scholarship for the mobility to Bonn (600€/month).  

== Timeline ==

Application deadline: September 15th, 2016

PhD start: As soon as possible, depending on the administrative procedures.

== Abstract ==

Ontologies are at the heart of the Semantic Web, i.e. making data published on the Web comprehensible to intelligent added value services. Ontologies’ consensual design ensures its usefulness and wide acceptance by service developers. Collaboration of ontology engineers, domain experts from multiple disciplines, and end-users is required for defining them and populating them with instance data.

Collaborative ontology creation has been well studied, especially by our teams [1, 2, 3]. This PhD addresses the co-evolution of an ontology and its instance data. The bottleneck lies in identifying and assessing data originating from diverse sources (organisations, schemas, formats…) and managing co-evolution [4, 5]. Extensive automation of this process is desirable but still requires human collaboration and consensus, taking into account measures on data: quality, trust, data provenance. We will elaborate a generic approach covering all aspects of ontology co-evolution. It will integrate different means/techniques tailored to types of data sources (unstructured documents as well as specialized and generalist structured knowledge bases [6]), design a data model to characterize datasets, and implement methods for both automated and user-oriented collaborative processes.

We will experiment with the application of this foundational research to different fields, one of them being the field of independent music labels and artists. This field is well suited for our investigations because i) its structure and content are permanently evolving (new music genres, new albums, etc.), ii) its description has to take into account different people’s perspectives (experts, consumers), and iii) it is not yet well documented on the Web, which requires combining various data sources.

== Our references ==

[1] Maxime Lefrançois and Antoine Zimmermann, LinkedVocabularyEditor: une extension MediaWiki pour l'édition collaborative et la publication de vocabulaires liés, Demo at 26e Journées francophones d'Ingénierie des Connaissances, IC, June 2015, Rennes, France.

[2] Niklas Petersen, Lavdim Halilaj, Christoph Lange, and Sören Auer. VoCol: An Agile Methodology and Environment for Collaborative Vocabulary Development. Technical report, 2015.

[3] Niklas Petersen, Irlán Grangel-González, Gökhan Coskun, Sören Auer, Marvin Frommhold, Sebastian Tramp, Maxime Lefrançois, Antoine Zimmermann: SCORVoc: Vocabulary-Based Information Integration and Exchange in Supply Networks. International Conference on Semantic Computing ICSC 2016: 132-139

[4] Riyadh Benammar, Alain Trémeau, Pierre Maret. An Approach for Ontology Population Based on Information Extraction Techniques - Application to Cultural Heritage. OTM Conferences 2015: 397-404.

[5] Sidra Faisal, Kemele M. Endris, Saeedeh Shekarpour, Sören Auer. Co-evolution of RDF Datasets. International Conference on Web Engineering (ICWE) 2016.

[6] Antoine Zimmermann, Christophe Gravier, Julien Subercaze, Quentin Cruzille. Nell2RDF: Read the Web, and Turn it into RDF. KNOW@ LOD, 2-8. 2013.

== Eligibility and application procedure ==

Candidates must hold a MSc degree in computer science or a related field and be able to combine both theoretical and practical aspects in their work.

Fluent English communication and a passion for developing modern software solutions are fundamental requirements. Command of French or German is a plus but not required. The candidates should have experience and commitment to work in team and on the forefront of research.

Candidates will need to submit by email a CV, university transcripts, a motivation letter including a short research plan targeting the above description, two letters of recommendation, and English writing samples (e.g., prior publication or master thesis excerpt).

The Université Jean Monnet is an equal opportunities employer. Preference will be given to suitably qualified women or persons with disabilities, all other considerations being equal.

== Contact ==

Pierre Maret and Antoine Zimmermann (Laboratoire Hubert Curien, Saint-Étienne, Connected Intelligence team:

[hidden email], [hidden email]