A Framework for Enterprise Context Analysis Based on Semantic Principles

Miguel Ferro-Beca1, Joao Sarraipa1, Carlos Agostinho1, Fernando Gigante2, Maria Jose-Nunez2 and Ricardo Jardim-Goncalves1

  1. Centre of Technology and Systems, CTS, UNINOVA
    2829-516 Caparica, Portugal
    {mfb, jfss, ca, rg}@uninova.pt
  2. AIDIMA- Institute of Technology for Furniture and Related Industry, Benjamín Franklin, 13. Parque Tecnológico
    46980 Paterna, Valencia, Spain
    {mjnunez, fgigante}@aidima.es

Abstract

Context analysis can be a daunting task given the vast amounts of information available and the work required to filter through all of it. Additionally, the process of performing context analysis on a specific company, although it may be done following a specific methodology, it is not a science which set in stone. Different approaches are possible, and the availability of new data sources, ranging from sensor data to web analytics data, can certainly enrich the process. However, there is a need for tools and methods, which can assist in tapping into these new data sources and extract relevant information that can assist enterprises in their context analysis process. The present paper proposes a framework that can assist in obtaining, filtering and processing relevant data from a variety of sources and in performing the necessary processing and reasoning to assist in performing a proper context analysis.

Key words

Sensing Enterprise, Semantic, Linked Data, Blueprints

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS150105037F

Publication information

Volume 12, Issue 3 (August 2015)
Special Issue on Collaborative e-Communities
Year of Publication: 2015
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable in PDF
Portable Document Format

How to cite

Ferro-Beca, M., Sarraipa, J., Agostinho, C., Gigante, F., Jose-Nunez, M., Jardim-Goncalves, R.: A Framework for Enterprise Context Analysis Based on Semantic Principles. Computer Science and Information Systems, Vol. 12, No. 3, 931–960. (2015)