Name: ARCHIMEDES ALVES DETONI

Publication date: 25/10/2019
Advisor:

Namesort descending Role
JOÃO PAULO ANDRADE ALMEIDA Advisor *

Examining board:

Namesort descending Role
JOÃO PAULO ANDRADE ALMEIDA Advisor *
MONALESSA PERINI BARCELLOS Internal Examiner *
VICTORIO ALBANI DE CARVALHO External Examiner *
VÍTOR ESTÊVÃO SILVA SOUZA Internal Examiner *

Summary: Nowadays, public and private organizations are being encouraged to improve the computerized support
to their activities. They intend to integrate their Information Systems (ISs) and to use heterogeneous
data from different sources in order to produce relevant and reliable information mainly to support their
decision activities. This challenge is intensified by the growing complexity of the organizational
architectures, which: internally require the orchestration of the interaction between various
administrative units, which must act integrated and collaboratively in distinct business processes that
cross various functional areas; and externally need to operate seamlessly with other organizations.
However, organizational ISs often do not support properly their business processes and are not able to
interoperate with external systems. It occurs because those ISs, in many cases, were developed gradually
and independently, each with its own scope, data structure, and terminology. Therefore, we can note
gaps related to the lack of integration, information sharing and adoption of common semantics between
organizational ISs. In such scenarios, the current literature has been indicating the use of ontologies as
interlanguage in order to establish a consensual conceptualization to be adopted in a given domain. Thus,
enabling interoperability between ISs and the integration of data dispersed over several sources and ISs.
For an ontology to fit the purpose of being a conceptual model capable of adequately representing a
domain, Ontology Engineering (OE) methods generally indicate the need to select and utilize knowledge
resources available in the context of the domain to be modeled. The selected knowledge resources should
facilitate the identification of relevant concepts and relationships that must be present in ontology,
thereby aiding ontology engineers to understand the problem domain. Focusing on this need, the present
work proposes the systematized use of Enterprise Architecture (EA) models as resources in OE
knowledge acquisition activities, once they are artifacts that provide a broad view of the elements which
compose organizational domains, in particular the actors, processes, ISs and their interrelationships.
Besides, EA models have increasingly being used in organizational environments to diagnose and design
interoperability solutions. The investigation of this possible synergy between the OE and EA disciplines
was started in an exploratory research that addressed a real problem of semantic interoperability into
public security domain, WHEREby EArly-OE approach was developed - Enterprise Architecture-driven
Early Ontology Engineering). Early-OE prescribes guidelines for using EA models elements as
knowledge resources to support initial OE activities in structured process-rich organizational domains,
e.g. definition of intended uses, potential users and requirements of an ontology. After being developed
in that exploratory research applied to the public security domain, the approach was evaluated in an
empirical study addressing a different domain, that of federal public budget and finances, by a group of
participants with varied degrees of experience in developing ontologies.

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