Goal and Risk Analysis in the Development of Information Systems for the Web of Data

Nome: Márcio Louzada de FreitasTipo: Dissertação de mestrado acadêmicoData de publicação: 12/12/2018Orientador:

Nomeordem decrescente Papel
Vítor Estêvão Silva Souza Orientador


Nomeordem decrescente Papel
Monalessa Perini Barcellos Examinador Interno
Vítor Estêvão Silva Souza Orientador

Resumo: Linked Data is a set of data published on the World Wide Web in an interconnected
fashion, whose contents can be processed by machines, forming a Web of Data. Published
data and their interconnections are described by means of vocabularies, i.e., schemas that
describe the existing entities and the relationship between them. Moreover, such data
can refer to several domains, such as Geographic, Media, Social Media, Governmental,
Libraries and Education, Life Sciences and so on.
The publication of Linked Data on the Web 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. In this context, tasks such as functional and nonfunctional
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 of the published data (i.e., a domain ontology).
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. The
use of GORE (Goal-Oriented Requirements Engineering) modeling languages, such as
iStar, can be employed in requirements elicitation, as well as help identify actors, agents
and roles, and to model their goals, tasks and resources, aiming at the development of
information systems which are integrated with the Web of Data. Also, 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. Our proposal
aims to present tool support for the creation of goal and risk models, helps the process of
choosing vocabulary through best practices and suggests a catalog of goals, risks, tasks
and resources related to Linked Data.
GRALD combines two existing approaches. On the Web Engineering side, the FrameWeb-
LD approach aids developers on publishing the data from Web-based Information Systems
as Linked Data, connecting it to vocabularies that can be specified on UML-based diagrams
during architectural design. On the Requirements Engineering side, the RISCOSS approach
seeks to align business goals and risks in the adoption of Open Source systems. We adapted
the latter so it can be applied to the adoption of Linked Data. GRALD seeks to establish
a synergy between these two approaches.Acesso ao documento

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