Abstract
Decentralised data exchanges are promising alternatives to monolithic data lakes and warehouses which are typically emerging around complex service solutions. In theory, this removes some of the bottlenecks of traditional data management solutions. In practice, the road towards achieving such goal is a long way ahead. In this work, we provide an industry perspective on the implications for such work, with a focus on metadata management; the work in question draws from an in-vivo action research approach we enacted at a major German automotive company that is transitioning to an internal decentral data market. Our results provide insight into an industry perspective on the requirements for metadata management. Additionally, we propose and validate a solution design for metadata management in decentralised data exchanges based on semantic web service technology.
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Notes
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Alternatively called data owners, (data) product providers, or (data) product developers [6].
References
Catena-X: Automotive Network (2021)
Alexander, I.F., Beus-Dukic, L.: Discovering Requirements: How to Specify Products and Services. Wiley, Chichester (2009)
Dehghani, Z.: Data Mesh: Delivering Data-Driven Value at Scale, 1st edn. O’Reilly (2022)
Dibowski, H., Schmid, S.: Using knowledge graphs to manage a data lake. In: INFORMAITK 2020, Lecture Notes in Informatics (LNI), pp. 41–50 (2021)
Doan, A., Halevy, A., Ives, Z.: Principles of Data Integration, 1st edn. Elsevier, Waltham, MA (2012)
Driessen, S., Monsieur, G., Van Den Heuvel, W.: Data market design: a systematic literature review. IEEE Access 10, 33123–33153 (2022). https://doi.org/10.1109/access.2022.3161478
Eichler, R., Giebler, C., Gröger, C., Hoos, E., Schwarz, H., Mitschang, B.: Enterprise-wide metadata management: an industry case on the current state and challenges. In: Business Information Systems (July), pp. 269–279 (2021). https://doi.org/10.52825/bis.v1i.47
Fernandez, R.C., Subramaniam, P., Franklin, M.J.: Data market platforms: trading data assets to solve data problems. Proc. VLDB Endow. 13(12), 2150–8097 (2020)
Goedgebuure, A.: Data mesh: systematic gray literature study, reference architecture, and cloud-based instantiation at ASML (2022). https://stefan-driessen.github.io/publication/data-mesh-systematic-grey-literature-study/
Hevner, A., Chatterjee, S.: Design Research in Information Systems: Theory and Practice, vol. 28. Springer, NY (2010). https://doi.org/10.1007/978-1-4419-5653-8
Hooshmand, Y., Resch, J., Wischnewski, P., Patil, P.: From a monolithic PLM landscape to a federated domain and data mesh. Proc. Design Soc. 2, 713–722 (2022)
Koutroumpis, P., Leiponen, A., Thomas, L.: The (unfulfilled) potential of data marketplaces. ETLA Working Papers 2420(53) (2017). http://pub.etla.fi/ETLA-Working-Papers-53.pdf%0Apub.etla.fi/ETLA-Working-Papers-53.pd
Koutroumpis, P., Leiponen, A., Thomas, L.D.W.: Markets for data. Ind. Corp. Chang. 29(3), 645–660 (2020). https://doi.org/10.1093/icc/dtaa002
Lauesen, S.: Software Requirements-Styles and Techniques. Pearson Education (2002)
Loukiala, A., Joutsenlahti, J.-P., Raatikainen, M., Mikkonen, T., Lehtonen, T.: Migrating from a centralized data warehouse to a decentralized data platform architecture. In: Ardito, L., Jedlitschka, A., Morisio, M., Torchiano, M. (eds.) PROFES 2021. LNCS, vol. 13126, pp. 36–48. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-91452-3_3
Narayan, S.: Products over projects (2018). https://martinfowler.com/articles/products-over-projects.html
Newman, S.: Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith. O’Reilly (2020). https://www.oreilly.com/library/view/monolith-to-microservices/9781492047834/
O’Neil, B.T.: Failure rates for analytics, AI, and big data projects = 85% - yikes! (2019)
Otto, B., Steinbuß, S., Teuscher, A., Lohmann, S.: IDSA reference architecture model. International Data Spaces Association (April) (2019). https://internationaldataspaces.org/download/16630/
Roman, D., et al.: The euBusinessGraph ontology: a lightweight ontology for harmonizing basic company information. Semantic Web 13(1), 41–68 (2021). https://doi.org/10.3233/sw-210424
Spiekermann, M., Tebernum, D., Wenzel, S., Otto, B.: A metadata model for data goods. In: MKWI 2018 - Multikonferenz Wirtschaftsinformatik 2018-March, pp. 326–337 (2018)
Stach, C., Bräcker, J., Eichler, R., Giebler, C., Mitschang, B.: Demand-driven data provisioning in data lakes. In: Association for Computing Machinery, vol. 1 (2021). https://doi.org/10.1145/3487664.3487784
Strengholt, P.: ABN AMRO’s data and integration mesh (2020). https://www.linkedin.com/pulse/abn-amros-data-integration-mesh-piethein-strengholt/
Sweller, J.: Cognitive load during problem solving: effects on learning. Cogn. Sci. 12(2), 257–285 (1988). https://doi.org/10.1016/0364-0213(88)90023-7
Dehghani, Z.: How to move beyond a monothilitic data lake to a distributed data mesh (2019). https://martinfowler.com/articles/data-monolith-to-mesh.html
W3C: Semantic web - leading the web to its full potential (2015)
Wieringa, R.J.: Design Science Methodology for Information Systems and Software Engineering. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-43839-8
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Driessen, S., Monsieur, G., van den Heuvel, WJ. (2023). Data Product Metadata Management: An Industrial Perspective. In: Troya, J., et al. Service-Oriented Computing – ICSOC 2022 Workshops. ICSOC 2022. Lecture Notes in Computer Science, vol 13821. Springer, Cham. https://doi.org/10.1007/978-3-031-26507-5_19
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