Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Abstract

Companies around the globe store large quantities of data they cannot monetise. Regarding internal monetisation, they lack tools to facilitate the governance and quality assessment of their data, resulting not really knowing what data they own or it being non reliable due to its poor quality. External monetisation is usually hindered by the unavailability of trustable mechanisms to perform this exchange or enabling the company to participate in ecosystems like EU data spaces or Gaia-X.

DATAMITE is an open-source modular and multi-domain framework that focuses on monetisation through interoperability and data exchange. Its modules offer tools for enhancing data governance, quality and security, but also enabling data sharing to a collection of ecosystems like data spaces, Gaia-X, EOSC or AIoD through a plugin-based approach. It also includes a series of additional support tools to assist on data discovery, ingestion, harmonization or evaluate data fairness, among other.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ai-on-demand platform. https://www.ai4europe.eu/

  2. Ai starts with trusted data. https://www.collibra.com/

  3. Big data quality solution for batch and streaming. https://griffin.apache.org/

  4. Ckan: The world’s leading open source data management system. https://ckan.org/

  5. Data in context: Closing the data decision gap. https://www.quantexa.com/resources/closing-the-data-decision-gap/

  6. Data quality definition language (dqdl) reference. https://docs.aws.amazon.com/glue/latest/dg/dqdl.html

  7. Dataspace connector dsc. https://international-data-spaces-association.github.io/DataspaceConnector

  8. Eclipse edc connector. https://github.com/eclipse-edc/Connector

  9. The future of al is built on quality data. https://www.ataccama.com/

  10. Gaia-x. https://gaia-x.eu/gaia-x-framework

  11. Gaia-x ces. https://gaia-x.eu/news-press/gaia-x-and-catalogues

  12. Gaia-x compliance. https://compliance.gaia-x.eu

  13. Gaia-x federation services. https://www.gxfs.eu/

  14. Gaia-x registry. https://registry.gaia-x.eu

  15. Gartner glossary: Data monetisation. https://www.gartner.com/en/information-technology/glossary/data-monetization

  16. Have confidence in your data, no matter what. https://greatexpectations.io/

  17. Ids protocol. https://docs.internationaldataspaces.org/ids-knowledgebase/v/dataspace-protocol/overview/readme

  18. International data spaces: The future of the data economy is here. https://internationaldataspaces.org/

  19. The leading third-gen data catalog. https://atlan.com/

  20. Linkedin datahub. https://datahubproject.io/

  21. Oai-pmh. https://www.openarchives.org/pmh

  22. ODRL information model 2.2. https://www.w3.org/TR/odrl-model/

  23. Open source data discovery and metadata engine. https://www.amundsen.io/

  24. Openmetadata. a single place to discover, collaborate and get your data right. http://open-metadata.org

  25. Pontus-x: Streamlined interoperability across digital service ecosystems. https://portal.minimal-gaia-x.eu/

  26. Restapi. https://docs.github.com/en/rest?apiVersion=2022-11-28

  27. Simpl: Cloud-to-edge federations empowering eu data spaces. https://digital-strategy.ec.europa.eu/en/policies/simpl

  28. Turn data chaos into data clarity with ai. https://www.informatica.com/platform.html

  29. Your unified access to the European hub of research data, tools and services for innovation and education. https://eosc-portal.eu/

  30. Dataports (2019). https://dataports-project.eu

  31. Rethink data put more of your business data to work, from edge to cloud (2020). https://www.seagate.com/files/www-content/our-story/rethink-data/files/Rethink_Data_Report_2020.pdf

  32. CINECA: Mistral portal. https://www.hpc.cineca.it/projects/mistral/

  33. Di Bella, L., Katsinis, A., Laguera Gonzalez, J., Odenthal, L., Hell, M., Lozar, B.: Annual report on european smes 2022/2023. In: Scientific Analysis or Review KJ-NA-31-618-EN-N (online), Luxembourg (Luxembourg) (2023). https://doi.org/10.2760/028705

  34. eDWIN: edwin platform. https://www.edwin.gov.pl/

  35. Hat, R.: Keycloak:open source identity and access management. https://www.keycloak.org/

  36. Otto, B., Steinbuss, S., Teuscher, A., Lohmann, S.E.A.: IDS Reference Architecture Model (Version 3.0). Technical report, International Data Spaces Association (2019). https://doi.org/10.5281/zenodo.5105529

  37. Pitkänen, O., Luoma-Kyyny, J.: Rulebook for a fair data economy. Technical report. Sitra (2019). https://www.sitra.fi/en/publications/rulebook-for-a-fair-data-economy/

  38. Taylor, P.: Data growth worldwide 2010–2025 (2023). https://www.statista.com/statistics/871513/worldwide-data-created/

  39. W3C: Data on the web best practices: Data quality vocabulary (2016). https://www.w3.org/TR/vocab-dqv/

  40. W3C: Data catalog vocabulary (dcat) - version 2 (2020). https://www.w3.org/TR/vocab-dcat-2/

  41. Wilkinson, M.D., et al.: The fair guiding principles for scientific data management and stewardship. Sci. Data 3(1), 1–9 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jordi Arjona Aroca .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Aroca, J.A. et al. (2024). Boosting Data Monetisation with DATAMITE. In: Maglogiannis, I., Iliadis, L., Karydis, I., Papaleonidas, A., Chochliouros, I. (eds) Artificial Intelligence Applications and Innovations. AIAI 2024 IFIP WG 12.5 International Workshops. AIAI 2024. IFIP Advances in Information and Communication Technology, vol 715. Springer, Cham. https://doi.org/10.1007/978-3-031-63227-3_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-63227-3_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-63226-6

  • Online ISBN: 978-3-031-63227-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics