AN EVENT-DRIVEN CARTOGRAPHIC APPROACH TO MODELLING SOFTWARE ENGINEERING KNOWLEDGE

Ernest Cachia, Mark Micallef

2011

Abstract

This paper proposes an event-based cartographic approach to managing software engineering knowledge that goes beyond the typical yellow-pages paradigm. After proposing a way of modelling knowledge assets, persons in an organisation and various relationships between these elements as a graph, the authors go on to demonstrate how this approach can be useful. Since the model is represented by a mathematical structure, established techniques from graph theory can be used for interesting analysis such as detecting knowledge risks, modelling staff turnover scenarios and identifying people who have similar knowledge to each other. The proposed approach uses an event-driven paradigm which infers the strength of knowledge relationships based on individuals’ participation in each knowledge asset’s life cycle.

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Paper Citation


in Harvard Style

Cachia E. and Micallef M. (2011). AN EVENT-DRIVEN CARTOGRAPHIC APPROACH TO MODELLING SOFTWARE ENGINEERING KNOWLEDGE . In Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2011) ISBN 978-989-8425-81-2, pages 18-27. DOI: 10.5220/0003630400180027

in Bibtex Style

@conference{kmis11,
author={Ernest Cachia and Mark Micallef},
title={AN EVENT-DRIVEN CARTOGRAPHIC APPROACH TO MODELLING SOFTWARE ENGINEERING KNOWLEDGE},
booktitle={Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2011)},
year={2011},
pages={18-27},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003630400180027},
isbn={978-989-8425-81-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2011)
TI - AN EVENT-DRIVEN CARTOGRAPHIC APPROACH TO MODELLING SOFTWARE ENGINEERING KNOWLEDGE
SN - 978-989-8425-81-2
AU - Cachia E.
AU - Micallef M.
PY - 2011
SP - 18
EP - 27
DO - 10.5220/0003630400180027