Open data quality measurement framework: Definition and application to Open Government Data

Abstract

The diffusion of Open Government Data (OGD) in recent years kept a very fast pace. However, evidence from practitioners shows that disclosing data without proper quality control may jeopardize datasets reuse and negatively affect civic participation. Current approaches to the problem in literature lack of a comprehensive theoretical framework. Moreover, most of the evaluations concentrate on open data platforms, rather than on datasets. In this work, we address these two limitations and set up a framework of indicators to measure the quality of Open Government Data on a series of data quality dimensions at most granular level of measurement. We validated the evaluation framework by applying it to compare two cases of Italian OGD datasets: an internationally recognized good example of OGD, with centralized disclosure and extensive data quality controls, and samples of OGD from decentralized data disclosure (municipalities level), with no possibility of extensive quality controls as in the former case, hence with supposed lower quality. Starting from measurements based on the quality framework, we were able to verify the difference in quality: the measures showed a few common acquired good practices and weaknesses, and a set of discriminating factors that pertain to the type of datasets and the overall approach. On the basis of this evaluation, we also provided technical and policy guidelines to overcome the weaknesses observed in the decentralized release policy, addressing specific quality aspects.

Examining open government data (OGD) usage in India through UTAUT framework

“…The basic understanding is that because OGD is an emerging phenomenon, a clear-cut definition is difficult to provide at this formative stage. Other aspects like performance appraisal and evaluation of OGD initiatives in terms of the quality of datasets have also been undertaken (for instance, Vetro et al, 2016). Among the models advanced around OGD, there are models which point out the "maturity" levels of OGD in terms of "stages" or there are models which point out the manner in which OGD may be tapped to secure collaboration and exchange among citizens and the government (for instance, Sieber and Johnson, 2015).…”

La auditoría en la gestión de la transparencia del sector público

“…A pesar de los esfuerzos de los estados de la Unión Europea en implantar la cultura de los datos abiertos que posibilite su reutilización, un estudio del portal español pone de manifiesto el bajo uso de la población de dichos datos, tal vez porque una parte de los ciudadanos no creen que las instituciones públicas ofrezcan suficiente información, o que el gobierno ofrezca aplicaciones fáciles para poder analizar e interpretar los datos (Gértrudix 2016). Uno de los factores que también puede afectar negativamente a la participación ciudadana en la reutilización de los datos abiertos de los gobiernos es la falta de control de calidad, que puede afectar a los metadatos, a suministrar datos incompletos, o a la falta de información sobre actualización de los datos (Vetrò 2016).…”

Evaluating Civic Open Data Standards

“…Open311 is generally considered in a larger context of how standards can improve citizen feedback (Offenhuber, 2015) or further private entrepreneurship and government efficiency (Suri, 2013). Research also has been directed towards the construction of standards, for example for domains like 311 municipal service calls (Nalchigar & Fox, 2014) or assess the quality of generic open data sets (Vetrò et al, 2016 (Lampland & Star, 2008). Goëta and Davies's (2016) analysed three standards of increasing complexity: the common data exchange format CSV (comma-separated values), GTFS and the international aid transparency initiative (IATI) standard.…”

“…city must meet this minimum number of datasets to be considered a part of the association). Standards that assess the quality of open government data (e.g., Vetrò et al, 2016) are conceptually distinct from standards that provide for interoperability of open data. However, the concepts of quality and interoperability, as well as metadata and possibly even certification are entangled in the empirical operations of standards.…”

“…Standards can make it easier for third party developers to create one product that serves multiple locales (Eaves, 2009;McHugh, 2013). Standardized data establish benchmarks in assessing whether governments achieve their goals in publishing open data (Davies & Perini, 2016;Vetrò et al 2016), for example in monitoring contracts and detecting corruption (Davies, Perini, & Alonso, 2013). In addition, data standards enable positive economic feedback cycles by easing accessibility to and implementation of the data and sustain innovation over time (Russell, 2014).…”