A semantic-based architecture for managing knowledge-intensive organizations: The ARISTOTELE platform

Daniele Toti, Pierluigi Del Nostro, Francesco Orciuoli, Stefano Paolozzi, Pierluigi Ritrovato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

We present the semantic-based architecture of the ARISTO-TELE platform, which is founded on the definition and development of models, methodologies, technologies and tools to support the emergence of competences and creativity within workers by self-organizing acquisition, processing and sharing of new information inside knowledge-intensi-ve organizations. ARISTOTELE's architecture relies on semantic data by means of a number of conceptual models, which define the context of interest for an enterprise via a set of concepts and relationships among them. Instances of these models are used to annotate content data, thus creating a semantic network of information that actualizes the Linked Data paradigm within the information space of an organization. In this paper we describe the building elements of the ARISTOTELE platform, the conceptual models which lie behind them and the core Linked Data Layer component responsible of managing information for the whole system. © 2013 Springer-Verlag.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages133-146
Number of pages14
Volume7652
DOIs
Publication statusPublished - 2013
EventCombined Workshops on Web Information Systems Engineering, WISE 2011 and WISE 2012 - Paphos, cyp
Duration: 28 Nov 201230 Nov 2012

Publication series

NameLECTURE NOTES IN COMPUTER SCIENCE

Conference

ConferenceCombined Workshops on Web Information Systems Engineering, WISE 2011 and WISE 2012
CityPaphos, cyp
Period28/11/1230/11/12

Keywords

  • Collaboration
  • Human Resource Management
  • Innovation
  • Knowledge Management
  • Knowledge Modeling
  • Learning
  • Semantic Enterprise architecture
  • Semantic Web
  • Training

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