Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review

Anastasija Nikiforova; Nina Rizun; Magdalena Ciesielska; Charalampos Harris Alexopoulos; Andrea Miletić

doi:10.1007/978-3-031-41138-0_14

Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review

Abstrakt

Open government data (OGD) is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles, but also be of value, i.e., of interest for reuse by the end-user. This refers to the notion of “high-value dataset” (HVD), recognized by the European Data Portal as a key trend in the OGD area in 2022. While there is progress in this direction, e.g., the Open Data Directive, incl. identifying 6 key categories, a list of HVDs and arrangements for their publication and re-use, they can be seen as “core” / “base” datasets aimed at increasing interoperability of public sector data with a high priority, contributing to the development of a more mature OGD initiative. Depending on the specifics of a region and country - geographical location, social, environmental, economic issues, cultural characteristics, (under)developed sectors and market specificities, more datasets can be recognized as of high value for a particular country. However, there is no standardized approach to assist chief data officers in this, and there is a clear lack of conceptualizations for the determination of HVD and systematic oversight. In this paper, we present a systematic review of existing literature on HVD determination, which is expected to form an initial knowledge base for this process, including used approaches and indicators to de-termine them, data, stakeholders

Cytowania

6

CrossRef
0

Web of Science
8

Scopus

Autorzy (5)

Anastasija Nikiforova Dr
- University of Tartu, Narva Mnt 18, 51009, Tartu, Estonia
Nina Rizun dr
Magdalena Ciesielska dr inż.
Charalampos Harris Alexopoulos Dr.
- University of the Aegean, 83200, Karlovassi, Samos, Greece
Andrea Miletić
- University of Zagreb, Savska Cesta 144A, 10000, Zagreb, Croatia

Cytuj jako

Pełna treść

pełna treść publikacji nie jest dostępna w portalu

pełna treść artykułu zobacz w serwisie zewnętrznym otwiera się w nowej karcie

Słowa kluczowe

OPEN GOVERNMENT DATA, HIGH-VALUE DATA, OPEN DATA, PUBLIC VALUE, PUBLIC ADMINISTRATION, STAKEHOLDER, OPEN DATA ECOSYSTEM

Informacje szczegółowe

Kategoria:

Publikacja monograficzna

Typ:

rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym

Język:

angielski

Rok wydania:

2023

Opis bibliograficzny:

Nikiforova A., Rizun N., Ciesielska M., Alexopoulos C. H., Miletić A.: Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review// / : , 2023,

DOI: