Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-11-18 Cooperative journals: 《数据智能（英文）》
van Vlijmen, Herman
Mons, Albert
Waalkens, Arne
Franke, Wouter
Baak, Arie
Ruiter, Gerbrand
Kirkpatrick, Christine
Santos, Luiz Olavo Bonino da Silva
Meerman, Bert
Jellema, Renger
Arts, Derk
Kersloot, Martijn
Knijnenburg, Sebastiaan
Lusher, Scott
Verbeeck, Rudi
Neefs, Jean-Marc
Abstract：
The industry sector is a very large producer and consumer of data, and many companies traditionally focused on production or manufacturing are now relying on the analysis of large amounts of data to develop new products and services. As many of the data sources needed are distributed and outside the company, FAIR data will have a major impact, both by reducing the existing internal data silos and by enabling the efficient integration with external (public and commercial) data. Many companies are still in the early phases of internal data ”FAIRification”, providing opportunities for SMEs and academics to apply and develop their expertise on FAIR data in collaborations and public-private partnerships. For a global Internet of FAIR Data & Services to thrive, also involving industry, professional tools and services are essential. FAIR metrics and certifications on individuals, data, organizations, and software, must ensure that data producers and consumers have independent quality metrics on their data. In this opinion article we reflect on some industry specific challenges of FAIR implementation to be dealt with when choices are made regarding ”Industry GOing FAIR”.
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