A conceptual deep dive into data ecosystems: a systematic literature review

Abstract

Data sharing in data ecosystems has gained interest as a means for innovation in industry, academia and governments. While there is an abundance of literature on data ecosystems and seminal works such as Oliveira et al. (Knowl Inf Syst 61(2):589–630, 2019) (pre-2017) offer foundational definitions of data ecosystems, recent studies still state that these remain unclear, complicating discussion and analysis of data ecosystems. Additionally, developments like the Common European Data Spaces and the International Data Space Association, which result from the European Strategy for Data, demand an updated study. This study bridges this gap through a systematic literature review on how data ecosystems have been defined in literature since 2017. We find that (1) while a generally accepted definition exists, being ”Data Ecosystems consist of a loose set of interacting actors that directly or indirectly consume, produce, or provide data and other related resources”, the broadness of this definition requires careful consideration in its application. (2) Data ecosystems originate from platform and ecosystem theory, each offering a different perspective on its functioning, contributing to contextual operationalization of data ecosystems. This results in six key concepts of data ecosystems: interconnection and interdependence, data value network, ecosystem metaphor, socio-technical, networks of human and non-human actors, self-organizing. (3) The term data ecosystem is susceptible to trends and used to repackage established concepts as innovative. Understanding these perspectives is important to ensure the success of data ecosystems in practice. This nuanced approach highlights the importance of contextualizing data ecosystems, rather than using a rigid definition.