TY - CHAP
T1 - Data Platforms for Data Spaces
AU - Anjomshoaa, Amin
AU - Elvira, Santiago Cáceres
AU - Wolff, Christian
AU - Pérez baún, Juan Carlos
AU - Karvounis, Manos
AU - Mellia, Marco
AU - Athanasiou, Spiros
AU - Katsifodimos, Asterios
AU - Garatzogianni, Alexandra
AU - Trügler, Andreas
AU - Serrano, Martin
AU - Zappa, Achille
AU - Glikman, Yury
AU - Tuikka, Tuomo
AU - Curry, Edward
PY - 2022/9/9
Y1 - 2022/9/9
N2 - In our societies, there is a growing demand for the production and use of more data. Data is reaching the point that is driving all the social and economic activities in every industry sector. Technology is not going to be a barrier anymore; however, where there is large deployment of technology, the production of data creates a growing demand for better data-driven services, and at the same time the benefits of the production of the data are at large an impulse for a global data economy, Data has become the business’s most valuable asset. In order to achieve its full value and help data-driven organizations to gain competitive advantages, we need effective and reliable ecosystems that support the cross-border flow of data. To this end, data ecosystems are the key enablers of data sharing and reuse within or across organizations. Data ecosystems need to tackle the various fundamental challenges of data management, including technical and nontechnical aspects (e.g., legal and ethical concerns). This chapter explores the Big Data value ecosystems and provides a detailed overview of several data platform implementations as best-effort approaches for sharing and trading industrial and personal data. We also introduce several key enabling technologies for implementing data platforms. The chapter concludes with common challenges encountered by data platform projects and details best practices to address these challenges.
AB - In our societies, there is a growing demand for the production and use of more data. Data is reaching the point that is driving all the social and economic activities in every industry sector. Technology is not going to be a barrier anymore; however, where there is large deployment of technology, the production of data creates a growing demand for better data-driven services, and at the same time the benefits of the production of the data are at large an impulse for a global data economy, Data has become the business’s most valuable asset. In order to achieve its full value and help data-driven organizations to gain competitive advantages, we need effective and reliable ecosystems that support the cross-border flow of data. To this end, data ecosystems are the key enablers of data sharing and reuse within or across organizations. Data ecosystems need to tackle the various fundamental challenges of data management, including technical and nontechnical aspects (e.g., legal and ethical concerns). This chapter explores the Big Data value ecosystems and provides a detailed overview of several data platform implementations as best-effort approaches for sharing and trading industrial and personal data. We also introduce several key enabling technologies for implementing data platforms. The chapter concludes with common challenges encountered by data platform projects and details best practices to address these challenges.
U2 - 10.1007/978-3-030-98636-0_3
DO - 10.1007/978-3-030-98636-0_3
M3 - Chapter or book article
SN - 978-3-030-98635-3
SP - 43
EP - 64
BT - Data Spaces
PB - Springer
ER -