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Semantic content negotiation for knowledge interchange among heterogeneous systems

ABG-92814 Sujet de Thèse
30/06/2020 < 25 K€ brut annuel
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École des Mines de Saint-Étienne
Saint-Étienne - Auvergne-Rhône-Alpes - France
Semantic content negotiation for knowledge interchange among heterogeneous systems
  • Informatique
Semantic Interoperability, Semantic Web, Linked Data, Content Negotiation

Description du sujet

Context

Content negotiation on the Web allows a data consumer (client) to tell a data provider (server) what it expects in terms of format, language, encoding, security [Fie14]. In return, the server provides data that meets these expectations when it can, or indicates an alternative, for example, that the same information resource is available in another format. However, even when the client's request is satisfied, this does not mean that the client is able to interpret the data correctly. For example, for the same data format, several forms, structures or schemas may exist. The customer may wish to obtain data that conforms to conventional terminology and has certain logical and structural properties.

In particular, in applications that rely on Semantic Web technologies, such as RDF and OWL, an application could expect graph-based data that conform to a specific ontology [Obr03], or that fit a certain data shape, or that is compatible with a given entailment regime [Gli13], [Zim13]. In environments such as the Web of Things, strong constraints may impose requirements on the server or client side due to processing power, bandwidth, or memory limitations [IERC15].

Objective and challenges to consider

The main challenge is to find out how clients and servers can agree on the expected (client-side) or provided (server-side) content automatically, so without the developer of the client application having to contact the server manager, or read natural language documentation. The objective of this thesis is to : (1) determine what properties the client and the server could agree on to negotiate content beyond its simple syntax; (2) define the mechanism (in terms of protocol and algorithm) allowing the client to announce its expectations and how the server reacts to these requirements; (3) consider making negotiation more flexible by introducing an external service in charge of mediation between client and server (data transformation, inference or validation system); (4) introduce a declarative formalism allowing the server to describe the logical and structural properties of its data (possibly relying on SPARQL 1.1 Service Description [Will13], Thing Description [Kab20], or various forms of content descriptions, e.g., [Thu18]).

Previous and ongoing work has been and are being conducted in extending content negotiation towards more flexibility such as [Hol98], [Sve19] or [Lef18].

References

[Fie14] R. Fielding, J. Reschke. Hypertext Transfer Protocol (HTTP/1.1): Semantics and Content (Section 5.3: Content Negotiation). RFC7231. 

[Gli13] B. Glimm, C. Ogbuji. SPARQL 1.1 Entailment Regimes. W3C Recommendation 21 March 2013 http://www.w3.org/TR/sparql11-entailment/ 2013.

[Hol98] K. Holtman, A. Mutz. Transparent Content Negotiation in HTTP, IE4TD Request for Comments RFC2295.

[Jac04] I. Jacobs, N. Walsh. Architecture of the World Wide Web, Volume One. W3C Recommendation 15 December 2004. 

[Kab20] S. Käbisch, T. Kamiya, M. McCool, V. Charpenay, M. Kovatsch. W3C. Web of Things (WoT) Thing Description. W3C Candidate Recommendation 6 November 2019. 

[Lef18] M. Lefrançois. RDF presentation and correct content conveyance for legacy services and the Web of Things. Proceedings of the 8th International Conference on the Internet of Things. 2018.

[Sve19] L. G. Svensson, R. Atkinson, N. J. Car, R. Verborgh. Content Negotiation by Profile, W3C Working Draft 26 November 2019.

[Thu18] A. S. Thuluva, D. Anicic, S. Rudolph. IoT Semantic Interoperability with Device Description Shapes. In Proc. of ESWC 2018.

[Obr03] L. Obrst. Ontologies for semantically interoperable systems. In CIKM: 366-369, 2003.

[Wil13] G. T. Williams. SPARQL 1.1 Service Description. W3C Recommendation 21 March 2013.

[Zim14] A. Zimmermann. RDF 1.1: On Semantics of RDF Datasets. W3C Working Group Note 25 February 2014 

[IERC15] IoT European Research Cluster (IERC). IoT Semantic Interoperability: research challenges, best practices, recommendations and next steps. Technical Report, 2015.

Nature du financement

Contrat doctoral

Précisions sur le financement

Bourse de l'école doctoral

Présentation établissement et labo d'accueil

École des Mines de Saint-Étienne

Mines Saint-Étienne is one of the leading engineering schools in France, training students in various fields of engineering, including computer science, management, material engineering, health care engineering. Researchers at Mines Saint-Étienne are associated with laboratories related to their field of research.

In the case of this PhD programme, the student will be associated with LIMOS (Laboratory of Informatics,
  Modelling and Optimization of the Systems), physically located in Clermont-Ferrand, but the student will be working mostly in Saint-Étienne, where part of the team is.

LIMOS is a Mixed Unit of Research (UMR 6158) in computing, and more generally in Sciences and Technologies of information and the Communication ( STIC).

The LIMOS is mainly connected with the Institute of the Sciences of the Information and their Interactions (INS2I) of the CNRS, and in a secondary way to the Institute of the Sciences of the Engineering and the Systems (INSIS). He has for academic supervision the Clermont Auvergne university and the graduate school of Mines of Saint-Étienne (EMSE), and as partner establishment the Engineer Institute SIGMA. The LIMOS is a member labex IMOBS3 and ClercVolc and federation of search in Environment FR 3467 (which groups 17 laboratories UCA and INRA of the site of Clermont-Ferrand). It is an associate member of the federation MODMAD (Mathematical MODELLING and Decision support, FED 4169) carried by University Jean Monnet of Saint-Étienne.

Profil du candidat

Master in computer Science with good theoretical and practical knowledge of Semantic Web Technologies. Programming skills.

  • Education: MSc (with distinction)
  • Specialties: Computer Science > Artificial Intelligence > { Linked Data, Semantic Web, Symbolic Artificial Intelligence }
  • Knowledge of Semantic Web Technologies is mandatory
  • Very good level in logic
  • Programming skills
  • Good interpersonal skills
  • Languages: English (French is a plus)
  • Good autonomy

Date limite de candidature

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