The ExpertFinder Initiative

Emanuele Della Valle	CEFRIEL, Italy
Dario Cerizza	CEFRIEL, Italy
Irene Celino	CEFRIEL, Italy

Abstract:

Abstract:
In this paper we propose that there are several ways that Expert-finder can be developed and applied successfully to foster communication and coordination among different, distributed teams during emergency relief operations, irrespective of their affiliation and denomination, and take this first workshop call for papers as an opportunity to invite interested parties in the humanitarian technology community to take part and collaborate in future effort to harmonise conceptual and semantic references as a step towards resolution of conflicts and imperfect communication flow

Tereza Iofciu	L3S Research Center
Jörg Diederich	L3S Research Center
Peter Dolog	Aalborg University
Wolf-Tilo Balke	L3S Research Center

Abstract:

Aidan Hogan	DERI, National University of Ireland, Galway
Andreas Harth	DERI, National University of Ireland, Galway

Abstract:
We provide a benchmark dataset for expert finding within the computer science domain. We show how large isolated data graphs from disparate structured data sources can be combined to form one, large, well-linked RDF graph and implement these methods to achieve our dataset. Such a graph lends itself to links analysis and thus opens up possibilities for analysis by expert finding techniques.

Irene Celino	CEFRIEL, Italy
Francesco Corcoglioniti	CEFRIEL, Italy
Emanuele Della Valle	CEFRIEL, Italy

Abstract:

Delroy Cameron	University of Georgia
Boanerges Aleman-Meza	University of Georgia
Ismailcem Budak Arpinar	University of Georgia

Abstract:
We present ideas for determining the expertise of researchers across various areas of computer science and for finding relevant experts/reviewers in a peer-review setting. We explain how Semantic Web techniques for data collection and data representation using ontologies can be used in addressing this specific "ExpertFinder" problem

John G. Breslin	DERI, National University of Ireland, Galway
Uldis Bojars	DERI, National University of Ireland, Galway
Boanerges Aleman-Meza	University of Georgia
Harold Boley	National Research Council, Canada University of New Brunswick
Malgorzata Mochol	Free University of Berlin, Germany
Lyndon J. B. Nixon	Free University of Berlin, Germany
Axel Polleres	Universidad Rey Juan Carlos, Madrid, Spain
Anna V. Zhdanova	Surrey University

Abstract:
This position paper on expert finding presents a conceptual framework for the reuse and interlinking of existing, well-established vocabularies in the Semantic Web. Such a framework can be used to connect people with people, based on joint or complementing interests (e.g. the need to develop specific new or existing skills for upcoming projects). Driven by a requirement to find experts using the profiles of people in social networks and using the content they create in online communities, we are exploring the usage of vocabularies in these domains that have already gained considerable momentum and that have suitable concepts for this application area. We will present the relevant properties of the FOAF ontology for matching people and their skills in social networks, then detail the SIOC project and methods for identifying relevant discussion topics / individuals, and finally we will outline a combinatory scenario that will allow people to find individuals with the desired expertise in a particular domain of interest.

Simone Braun	Universität Karlsruhe
Andreas Schmidt	Universität Karlsruhe

Abstract:
Expert finding goes beyond identifying and locating experts. We see expert finding embedded into informal learning activities where personal and social context plays a decisive role (e.g. looking for colleagues to ask for help). That means on social context level, we need social relationship models describing not only objective but also subjective opinions about relationships' quality. On personal context level, we need shared competence models describing experts and the purpose of interacting with them. With this approach we make expert finding competency- and socially-aware.

Uldis Bojars	DERI, National University of Ireland, Galway
John G. Breslin	DERI, National University of Ireland, Galway

Abstract:
This paper explores the ResumeRDF ontology [1][2] and its potential application to the tasks of ExpertFinder initiative, including describing people's resumes and skill sets. We consider DOAC [3] as another ontology which can be used skill information, compare their characteristics and describe directions for future development. Second part of this paper looks at discovery of skill information on the Semantic Web which becomes important as soon as skill information starts to get published.

Abstract:
We present our activity lines in connection with the ExpertFinder initiative