Nothing Special   »   [go: up one dir, main page]

Skip to main content

Industrial Data Sharing with Data Access Policy

  • Conference paper
  • First Online:
Cooperative Design, Visualization, and Engineering (CDVE 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10451))

  • 1296 Accesses

Abstract

In current industrial settings, data is dispersed on numerous devices, systems and locations without integration and sharing capabilities. With this work, we present a framework for the integration of various data sources within an industrial setting, based on a mediating data hub. Within the data hub, data sources and sinks for this industrial application are equipped with data usage policies to restrict and enable usage and consumption of data for shared analytics. We identify such policies, their requirements and rationale. This work addresses an industrial setting, with manufacturing data being the primary use-case. Requirements for these policies are identified from existing use-cases and expert domain knowledge. The requirements are identified as reasonable via examples and exemplary implementation.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Similar content being viewed by others

References

  1. Service Plattform für die intelligente Anlagenoptimierung in der Produktion. http://projekt-sepiapro.de. Accessed 12 May 2017

  2. Allmendinger, G., Lombreglia, R.: Four strategies for the age of smart services. Harv. Bus. Rev. 83(10), 131 (2005)

    Google Scholar 

  3. Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)

    Article  MATH  Google Scholar 

  4. Breitenbücher, U., Binz, T., Fehling, C., Kopp, O., Leymann, F., Wieland, M.: Policy-aware provisioning and management of cloud applications. Int. J. Adv. Secur. 7(1&2), 15–36 (2014). http://www.iaas.uni-stuttgart.de/RUS-data/ART-2014-08%20-%20Policy-Aware%20Provisioning%20and%20Management%20of%20Cloud%20Applications.pdf

    Google Scholar 

  5. Breitenbücher, U., Binz, T., Kopp, O., Leymann, F., Wieland, M.: Policy-aware provisioning of cloud applications. In: Proceedings of 7th International Conference on Emerging Security Information, Systems and Technologies (SECURWARE 2013), pp. 86–95. Xpert Publishing Services (2013)

    Google Scholar 

  6. Dais, S.: Industrie 4.0 - Anstoß, Vision, Vorgehen, pp. 261–277. Springer, Heidelberg (2017)

    Google Scholar 

  7. Gardner, D., Toga, A.W., et al.: Towards effective and rewarding data sharing. Neuroinformatics 1(3), 289–295 (2003)

    Article  Google Scholar 

  8. Malin, B., Karp, D., Scheuermann, R.H.: Technical and policy approaches to balancing patient privacy and data sharing in clinical and translational research. J. Invest. Med. 58(1), 11–18 (2015). http://jim.bmj.com/content/58/1/11

  9. OASIS: Oasis open data protocol (odata). Technical report, OASIS (2014). http://docs.oasis-open.org/odata/odata/v4.0/os/part1-protocol/odata-v4.0-os-part1-protocol.html

  10. Sundmaeker, H., Guillemin, P., Friess, P., Woelffle, S.: Vision and challenges for realising the internet of things. In: European Commission Information Society and Media (2010)

    Google Scholar 

  11. The Apache Software Foundation: Apache Flink: Scalable Stream and Batch Data Processing. https://flink.apache.org. Accessed 12 May 2017

  12. Yu, Z., Yan, H., Cheng, T.E.: Benefits of information sharing with supply chain partnerships. Ind. Manag. Data Syst. 101(3), 114–121 (2001)

    Article  Google Scholar 

  13. Zhao, G., Rong, C., Li, J., Zhang, F., Tang, Y.: Trusted data sharing over untrusted cloud storage providers. In: 2010 IEEE 2nd International Conference on Cloud Computing Technology and Science, pp. 97–103, November 2010

    Google Scholar 

Download references

Acknowledgments

This work is partially funded by the project SePiA.Pro (01MD16013F) of the BMWi program Smart Service World.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Felix W. Baumann .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Baumann, F.W., Breitenbücher, U., Falkenthal, M., Grünert, G., Hudert, S. (2017). Industrial Data Sharing with Data Access Policy. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2017. Lecture Notes in Computer Science(), vol 10451. Springer, Cham. https://doi.org/10.1007/978-3-319-66805-5_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-66805-5_27

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66804-8

  • Online ISBN: 978-3-319-66805-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics