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Ontological support for a measurement and evaluation framework
Author(s) -
Olsina Luis,
Papa Fernanda,
Molina Hernán
Publication year - 2008
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20320
Subject(s) - computer science , viewpoints , measure (data warehouse) , ontology , metric (unit) , metadata , quality (philosophy) , data science , conceptual framework , information retrieval , knowledge management , data mining , world wide web , philosophy , epistemology , art , operations management , economics , visual arts
A common challenge faced by many software and Web organizations is to have a clear establishment of a measurement and evaluation framework for quality assurance programs. A well‐established measurement and evaluation framework might rely on a sound conceptual (ontological) base. Besides, organizations could succeed if resulting measurements and evaluations are tailored to their information needs for specific purposes, contexts, and user viewpoints. In this paper, we discuss our measurement and evaluation framework so‐called INCAMI that stands for information need , concept model , attribute , metric and indicator , which is also based on our proposal of the metrics and indicators ontology. Without appropriate metadata of metrics and indicators, it is difficult to ensure that measure and indicator values are repeatable and comparable among organization's projects. Moreover, analyses and comparisons could be performed in an inconsistent way. The present work tries to highlight about the usefulness of this framework and strategy as well as to discuss why INCAMI can be a more robust and engineered framework than others. Finally, given the aim of this special issue on aggregation operators and models, where they fit into the framework to model and compute, partial/global indicators are highlighted. © 2008 Wiley Periodicals, Inc.