Experience

Open Fiscal Datasets, Common Issues, and Recommendations

verfasst von

Fathoni A. Musyaffa, Christiane Engels, Maria Esther Vidal, Fabrizio Orlandi, Sören Auer

Abstract

Public administrations are continuously publishing open data, increasing the amount of government open data over time. The published data includes budgets and spending as part of fiscal data; publishing these data is an important part of transparent and accountable governance. However, open fiscal data should also meet open data publication guidelines. When requirements in data guidelines are not met, effective data analysis over published datasets cannot be performed effectively. In this article, we present Open Fiscal Data Publication (OFDP), a framework to assess the quality of open fiscal datasets. We also present an extensive open fiscal data assessment and common data quality issues found; additionally, open fiscal data publishing guidelines are presented. We studied and surveyed main quality factors for open fiscal datasets. Moreover, the collected quality factors have been scored according to the results of a questionnaire to score quality factors within the OFDP assessment framework. We gather and comprehensively analyze a representative set of 77 fiscal datasets from several public administrations across different regions at different levels (e.g., supranational, national, municipality). We characterize quality issues commonly arising in these datasets. Our assessment shows that there are many quality factors in fiscal data publication that still need to be taken care of so that the data can be analyzed effectively. Our proposed guidelines allow for publishing open fiscal data where these quality issues are avoided.

Organisationseinheit(en)

Fachgebiet Data Science and Digital Libraries

Externe Organisation(en)

Rheinische Friedrich-Wilhelms-Universität Bonn
Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme (IAIS)
Universidad Simon Bolivar

Typ

Artikel

Journal

Journal of Data and Information Quality

Band

9

Anzahl der Seiten

10

ISSN

1936-1955

Publikationsdatum

12.04.2018

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Information systems, Informationssysteme und -management

Ziele für nachhaltige Entwicklung

SDG 11 – Nachhaltige Städte und Gemeinschaften

Elektronische Version(en)

https://doi.org/10.1145/3190576 (Zugang: Geschlossen)