Abstract
Data Ecosystems are socio-technical complex networks in which actors interact and collaborate with each other to find, archive, publish, consume, or reuse data as well as to foster innovation, create value, and support new businesses. While the Data Ecosystem field is thus arguably gaining in importance, research on this subject is still in its early stages of development. Up until now, not many academic papers related to Data Ecosystems have been published. Furthermore, to the best of our knowledge, there has been no systematic review of the literature on Data Ecosystems. In this study, we provide an overview of the current literature on Data Ecosystems by conducting a systematic mapping study. This study is intended to function as a snapshot of the research in the field and by doing so identifies the different definitions of Data Ecosystem and analyzes the evolution of Data Ecosystem research. The studies selected have been classified into categories related to the study method, contribution, research topic, and ecosystem domains. Finally, we analyze how Data Ecosystems are structured and organized, and what benefits can be expected from Data Ecosystems and what their limitations are.
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International Digital Government Research Conference.
International Conference on Theory and Practice of Electronic Governance.
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This paper was partially supported by funds from the following Brazilian funding agencies: the Pernambuco State Science and Technology Support Foundation (FACEPE) and the National Institute of Science and Technology for Software Engineering (INES). Marcelo Iury also thanks the National Committee of Technological and Scientific Development (CNPq) and the Coordination for the Improvement of Higher Level Personnel (CAPES), for granting him a PhD fellowship. The authors would also like to thank the colleagues of the Aladin research group for their input to this study.
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S. Oliveira, M.I., Barros Lima, G.d.F. & Farias Lóscio, B. Investigations into Data Ecosystems: a systematic mapping study. Knowl Inf Syst 61, 589–630 (2019). https://doi.org/10.1007/s10115-018-1323-6
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DOI: https://doi.org/10.1007/s10115-018-1323-6