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Towards a Contextual Approach to Data Quality
Open AccessFeature PaperArticle

Repository Approaches to Improving the Quality of Shared Data and Code

1
Institute for Quantitative Social Science, Harvard University, 1737 Cambridge St, Cambridge, MA 02138, USA
2
European Organization for Nuclear Research (CERN), 1, Esplanade des Particules, CH-1217 Meyrin, Switzerland
3
LMU Munich, 1, Geschwister-Scholl-Platz, 80539 Munich, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Maurizio Lenzerini
Received: 22 December 2020 / Revised: 27 January 2021 / Accepted: 28 January 2021 / Published: 3 February 2021
(This article belongs to the Special Issue Data Quality and Data Access for Research)
Sharing data and code for reuse has become increasingly important in scientific work over the past decade. However, in practice, shared data and code may be unusable, or published results obtained from them may be irreproducible. Data repository features and services contribute significantly to the quality, longevity, and reusability of datasets. This paper presents a combination of original and secondary data analysis studies focusing on computational reproducibility, data curation, and gamified design elements that can be employed to indicate and improve the quality of shared data and code. The findings of these studies are sorted into three approaches that can be valuable to data repositories, archives, and other research dissemination platforms. View Full-Text
Keywords: data quality; data repository; digital libraries; data curation; fair principles; open data; open code; gamification data quality; data repository; digital libraries; data curation; fair principles; open data; open code; gamification
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MDPI and ACS Style

Trisovic, A.; Mika, K.; Boyd, C.; Feger, S.; Crosas, M. Repository Approaches to Improving the Quality of Shared Data and Code. Data 2021, 6, 15. https://doi.org/10.3390/data6020015

AMA Style

Trisovic A, Mika K, Boyd C, Feger S, Crosas M. Repository Approaches to Improving the Quality of Shared Data and Code. Data. 2021; 6(2):15. https://doi.org/10.3390/data6020015

Chicago/Turabian Style

Trisovic, Ana; Mika, Katherine; Boyd, Ceilyn; Feger, Sebastian; Crosas, Mercè. 2021. "Repository Approaches to Improving the Quality of Shared Data and Code" Data 6, no. 2: 15. https://doi.org/10.3390/data6020015

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