Open government data: Maturity diagnosis model aimed at quality data published on the network

Dirceu Flavio Macedo; Daniela Lucas da Silva Lemos

doi:10.1590/1808-5245.30.132617

Autores/as

Dirceu Flavio Macedo Prefeitura de Vitória https://orcid.org/0000-0003-4837-3618
Daniela Lucas da Silva Lemos Universidade Federal do Espírito Santo https://orcid.org/0000-0003-1565-7366

DOI:

https://doi.org/10.1590/1808-5245.30.132617

Palabras clave:

open government data, information organization, maturity diagnosis model, quality data, data governance

Resumen

Increased interest in open government data initiatives is a phenomenon originated from long debates about State modernization. The research focuses on understanding the challenges imposed on the public administration regarding data publishing in line with the open movement from the perspective of open data portals. Thus, the article is aimed at proposing a maturity diagnosis model for open data portals, towards the provision of in-depth, consistent, efficient and transparent government information. The methodology was divided into three phases. The first stage was a pre-test conducted on open data portals in the USA, UK, Brazil, and Ireland, motivated by research that evidenced the historical background of the open data movement, together with a current panorama of initiatives, evolution stages and challenges, which served to define the fundamental analytical dimensions to the proposition of the maturity model. In the second stage, a maturity diagnosis model was developed for open government data portals. In the third step, the model was applied and validated in the same portals as the pre-test. The results of the application of the diagnosis instrument can guide public administration in conducting a more efficient and responsible data governance, benefiting the government, the movement of open data and civil society.

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Biografía del autor/a

Dirceu Flavio Macedo, Prefeitura de Vitória

Master in Information Science, working in research in the fields of information retrieval, information and knowledge representation and data science. It is linked to the Technology and Organization of Information and Knowledge Group (TOIC/UFES Group). It also participates in the accessibility working group (GT) of W3C Brasil, where it contributes to definitions of policies, plans and manuals produced to promote accessibility on the internet. Responsible for coordinating accessibility actions, design and web information architecture in the municipal government of Vitória.

Daniela Lucas da Silva Lemos, Universidade Federal do Espírito Santo

Associate Professor and researcher at the Department of Library Science at the Federal University of Espírito Santo (UFES). PhD in Information Science from the Federal University of Minas Gerais (2014); Master in Information Science from the Federal University of Minas Gerais (2008); specialist in Strategic Information Management from the Federal University of Minas Gerais (2002); and graduated in Administration of Information Systems from the Faculty of Management Information Systems of Centro Universitário UNA (2001). She currently works as a permanent professor at the Graduate Program in Information Science at UFES. He is the leader of the research group Technology and Organization of Information and Knowledge (UFES) of CNPq, with which he coordinates the research project Acervo em Rede: digital collections of Ibram museums, a partnership with the Brazilian Institute of Museums (Ibram) and the UFES . She also participates as a research member in the Representation of Knowledge, Ontologies and Language (UFMG) and Network Intelligence Laboratory (UnB) groups, the latter being a researcher for the Tainacan project, free software for building digital deposits; in addition to a partnership in research with Fundação Getúlio Vargas (EMAp/CPDOC/Rio de Janeiro), including semantic organization projects in repositories with 3D objects. He has been dedicated to research focused on the interdisciplinary aspect between Data Science and Information Science with regard to specific contributions to improving the quality of data and metadata in digital cultural heritage collections, seeking adequate informational infrastructure for reuse, aggregation , search and retrieval of networked digital objects, including FAIR and cataloging principles, data pre-processing techniques, and machine learning.

Has experience in the areas of Information Science, including Organization and Information Processing, Knowledge Representation and Information Retrieval, presented mainly in the following subjects: Digital Repositories and Libraries, Digital Cultural Heritage, Knowledge Organization, Conceptual Modeling, Databases, Controlled Vocabularies, Ontologies, Metadata, Semantic Web, Linked Data and Semantic Annotation of Multimedia Resources on the Web. Experience in the area of Information Technology in the industrial and services segment, with emphasis on databases, software engineering and analysis, design, implementation and administration of information systems. He has 18 years of teaching experience in Higher Education Institutions, including courses in Computer Science, Engineering, Information Systems, Information Science and Librarianship.

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