Challenges and Governance Solutions for Data Science Services based on Open Data and APIs
| Autor: | Timo Lehtonen, Juha-Pekka Joutsenlahti, Elina Kettunen, Mikko Raatikainen, Tommi Mikkonen |
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| Přispěvatelé: | Empirical Software Engineering research group, Department of Computer Science |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Application programming interface Computer science media_common.quotation_subject Corporate governance education Business model 113 Computer and information sciences Data science Domain (software engineering) Software Engineering (cs.SE) Open data Computer Science - Software Engineering Quality (business) Experience report media_common |
| Zdroj: | WAIN@ICSE |
| Popis: | Increasingly common open data and open application programming interfaces (APIs) together with the progress of data science -- such as artificial intelligence (AI) and especially machine learning (ML) -- create opportunities to build novel services by combining data from different sources. In this experience report, we describe our firsthand experiences on open data and in the domain of marine traffic in Finland and Sweden and identified technological opportunities for novel services. We enumerate five challenges that we have encountered with the application of open data: relevant data, historical data, licensing, runtime quality, and API evolution. These challenges affect both business model and technical implementation. We discuss how these challenges could be alleviated by better governance practices for provided open APIs and data. 2021 IEEE/ACM 1st Workshop on AI Engineering - Software Engineering for AI (WAIN) of 43rd International Conference on Software Engineering (ICSE) |
| Databáze: | OpenAIRE |
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