GRALD: an Approach for Goal and Risk Analysis in the Development of Information Systems for the Web of Data

  • Marcio Louzada de Freitas Universidade Federal do Espírito Santo
  • Renata Silva Souza Guizzardi Universidade Federal do Espírito Santo
  • Vítor Estêvão Silva Souza Universidade Federal do Espírito Santo

Abstract

The publication of Linked Data on the Web regarding several application domains leads to new problems related to Requirements Engineering, which needs to take into account aspects related to new ways of developing systems and delivering information integrated with the Web of Data. Tasks such as (functional and non-functional) requirements elicitation and ontology-based conceptual modeling can be applied to the development of systems that publish Linked Data, in order to obtain a better shared conceptualization (i.e., a domain ontology) of the published data. The use of vocabularies is an intrinsic activity when publishing or consuming Linked Data and their choice can be supported by the elicited requirements and domain ontology. However, it is important to assess the risk when choosing external vocabularies, as their use can lead to problems, such as misinterpretation of meanings due to poor documentation, connection timeouts due to infrastructure problems, etc. Thus, risk identification, modeling and analysis techniques can be employed, in order to identify risks and their impacts on stakeholder goals. In this work, we propose GRALD: Goals and Risks Analysis for Linked Data, an approach for modeling goals and risks for information systems for the Web of Data.

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Published
2019-09-08
How to Cite
DE FREITAS, Marcio Louzada; GUIZZARDI, Renata Silva Souza; SOUZA, Vítor Estêvão Silva. GRALD: an Approach for Goal and Risk Analysis in the Development of Information Systems for the Web of Data. Journal of Software Engineering Research and Development, [S.l.], v. 7, p. 4:1 - 4:13, sep. 2019. ISSN 2195-1721. Available at: <https://sol.sbc.org.br/journals/index.php/jserd/article/view/18>. Date accessed: 17 nov. 2019. doi: https://doi.org/10.5753/jserd.2019.18.
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Research Article