Skip to main content
SpringerLink
Log in

Open Data Infrastructure for Research and Development

  • Chapter
  • First Online:
Data Science Landscape

Part of the book series: Studies in Big Data ((SBD,volume 38))

Abstract

Open data are the idea originated from philosophy that certain data should be freely available for everyone to use, reuse, and republish as they wish, without restrictions from copyright, patents or other mechanisms of control. The intent of the open data movement is on the same lines as that of other “open” movements such as open source, open content, and open access. Open data have caught attention of research community, government, industry across the world, due to its huge potential to bring constructive changes in the socioeconomic and scientific domain by developing and disseminating information within a vibrant mixed ecosystem comprising of research and developer community, government bodies, business houses, and hybrid solutions of various forms fueled by the sharp elevation of information and communications technologies (ICT) and digital governance. Open data along with data analytics service give a huge opportunity for development and innovation in citizen service delivery. Open data have also formed a part of core strategy of businesses across the world, big or small, digital or non-digital. Research community has also highlighted the potential of data for research and development. Reuse of research data can enable its analysis from a different perspective; processing the data in combination with other related datasets may provide a different perspective of the research findings.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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. Bechhofer, S., De Roure, D., Gamble, M., Goble, C., & Buchan, I. (2010). Research objects: Towards exchange and reuse of digital knowledge.

    Google Scholar 

  2. Borgman, C. L. (2012). The conundrum of sharing research data. Journal of the Association for Information Science and Technology, 63(6), 1059–1078.

    Google Scholar 

  3. Boulton, G. (2014). The open data imperative. Insights, 27(2).

    Google Scholar 

  4. Bowers, S., McPhillips, T., Wu, M., & Ludäscher, B. (2007, June). Project histories: Managing data provenance across collection-oriented scientific workflow runs. In International Conference on Data Integration in the Life Sciences (pp. 122–138). Berlin: Springer.

    Google Scholar 

  5. Buddenbohm, S., Cretin, N., Dijk, E., Gaiffe, B., De Jong, M., & Minel, J. L., et al. (2016). State of the art report on open access publishing of research data in the humanities. Doctoral dissertation, DARIAH.

    Google Scholar 

  6. Childs, S., McLeod, J., Lomas, E., & Cook, G. (2014). Opening research data: Issues and opportunities. Records Management Journal, 24(2), 142–162.

    Article  Google Scholar 

  7. Conradie, P., & Choenni, S. (2012, October). Exploring process barriers to release public sector information in local government. In Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance (pp. 5–13). ACM.

    Google Scholar 

  8. Davies, T., & Frank, M. (2013, May). ‘There’s no such thing as raw data’: Exploring the socio-technical life of a government dataset. In Proceedings of the 5th Annual ACM Web Science Conference (pp. 75–78). ACM.

    Google Scholar 

  9. Estermann, B. (2014). Diffusion of open data and crowdsourcing among heritage institutions: Results of a pilot survey in Switzerland. Journal of theoretical and applied electronic commerce research, 9(3), 15–31.

    Article  Google Scholar 

  10. Fox, X. M. P., Beaulieu, S. E., Fu, L., Di Stefano, M., & West, P. (2016). Documenting provenance for reproducible marine ecosystem assessment in open science. Oceanographic and Marine Cross-Domain Data Management for Sustainable Development, 100.

    Google Scholar 

  11. Gurstein, M. B. (2011). Open data: Empowering the empowered or effective data use for everyone? First Monday, 16(2).

    Google Scholar 

  12. Hester, J. R. (2014). Closing the data gap: Creating an open data environment. Radiation Physics and Chemistry, 95, 59–61.

    Article  Google Scholar 

  13. Himmelreicher, R. K., & Stegmann, M. (2008). New possibilities for socio-economic research through longitudinal data from the research data centre of the German federal pension insurance (FDZ-RV). Schmollers Jahrbuch, 128(4), 647–660.

    Article  Google Scholar 

  14. Hrynaszkiewicz, I. (2011). The need and drive for open data in biomedical publishing. Serials, 24(1).

    Google Scholar 

  15. Janssen, K. (2011). The influence of the PSI directive on open government data: An overview of recent developments. Government Information Quarterly, 28(4), 446–456.

    Article  Google Scholar 

  16. Janssen, S., Porter, C. H., Moore, A. D., Athanasiadis, I. N., Foster, I., & Jones, J. W., et al. (2015). Towards a new generation of agricultural system models, data, and knowledge products: Building an open web-based approach to agricultural data, system modeling and decision support. AgMIP. Towards a New Generation of Agricultural System Models, Data, and Knowledge Products, 91.

    Google Scholar 

  17. Kidwell, M. C., Lazarević, L. B., Baranski, E., Hardwicke, T. E., Piechowski, S., Falkenberg, L. S., … & Errington, T. M. (2016). Badges to acknowledge open practices: A simple, low-cost, effective method for increasing transparency. PLoS Biology, 14(5), e1002456.

    Google Scholar 

  18. Knowledge Exchange Homepage, http://www.knowledge-exchange.info/, last accessed 2017/08/31.

  19. Lenhart, A., Simon, M., & Graziano, M. (2001). The Internet and Education: Findings of the Pew Internet & American Life Project.

    Google Scholar 

  20. Mishra, A., Misra, D. P., Kar, A. K., Babbar, S., & Biswas, S. (2017, November). Assessment of open government data initiative—a perception driven approach. In Conference on e-Business, e-Services and e-Society (pp. 159–171). Springer, Cham.

    Google Scholar 

  21. Missier, P., Ludäscher, B., Bowers, S., Dey, S., Sarkar, A., Shrestha, B., … & Goble, C. (2010, November). Linking multiple workflow provenance traces for interoperable collaborative science. In 5th Workshop on Workflows in Support of Large-Scale Science (WORKS) (pp. 1–8). IEEE.

    Google Scholar 

  22. Moore, S. (2014). Issues in Open Research Data (p. 164). Ubiquity Press.

    Google Scholar 

  23. Nogueras-Iso, J., Zarazaga-Soria, F. J., Lacasta, J., Béjar, R., & Muro-Medrano, P. R. (2004). Metadata standard interoperability: Application in the geographic information domain. Computers, Environment and Urban Systems, 28(6), 611–634.

    Article  Google Scholar 

  24. Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., … & Contestabile, M. (2015). Promoting an open research culture. Science, 348(6242), 1422–1425.

    Google Scholar 

  25. OAPEN Homepage, http://www.oapen.org/home, last accessed 2017/08/31.

  26. Open Data Institute Homepage, http://theodi.org/, last accessed 2017/08/31.

  27. Open Knowledge Foundation Homepage, https://okfn.org/, last accessed 2017/08/31.

  28. OpenAIRE Homepage, https://www.openaire.eu/, last accessed 2017/08/31.

  29. Reichman, O. J., Jones, M. B., & Schildhauer, M. P. (2011). Challenges and opportunities of open data in ecology. Science, 331(6018), 703–705.

    Article  Google Scholar 

  30. Sawicki, D. S., & Craig, W. J. (1996). The democratization of data: Bridging the gap for community groups. Journal of the American Planning Association, 62(4), 512–523.

    Article  Google Scholar 

  31. Starr, J., Castro, E., Crosas, M., Dumontier, M., Downs, R. R., Duerr, R., … & Hourclé, J. (2015). Achieving human and machine accessibility of cited data in scholarly publications. PeerJ Computer Science, 1, e1.

    Google Scholar 

  32. Stevens, B. J. (1984). Nursing theory. Analysis, application, evaluation (2nd ed.). Boston: Little, Brown.

    Google Scholar 

  33. Tananbaum, G. (2008). Adventures in open data. Learned Publishing, 21(2), 154–156.

    Article  Google Scholar 

  34. Verma, N. (2013, August). Open data for inclusive governance. In Joint Proceedings of the Workshop on AI Problems and Approaches for Intelligent Environments and Workshop on Semantic Cities (pp. 5–5). ACM.

    Google Scholar 

  35. Verma, N., & Gupta, M. P. (2012). Open government data: More than eighty formats. Paper presented at the 9th International Conference on E-Governance (ICEG 2012), Cochin, Kerala, India.

    Google Scholar 

  36. Verma, N., & Gupta, M. P. (2013, October). Open government data: Beyond policy & portal, a study in Indian context. In Proceedings of the 7th International Conference on Theory and Practice of Electronic Governance (pp. 338–341). ACM.

    Google Scholar 

  37. Verma, N., & Gupta, M. P. (2015, November). Challenges in publishing Open Government Data: A study in Indian context. In Proceedings of the 2015 2nd International Conference on Electronic Governance and Open Society: Challenges in Eurasia (pp. 1–9). ACM.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Informatics Centre, New Delhi, India

    Neeta Verma

  2. DMS, Indian Institute of Technology, Delhi, India

    M. P. Gupta

  3. Open Government Data Project, Delhi, India

    Shubhadip Biswas

Authors
  1. Neeta Verma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. P. Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shubhadip Biswas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Neeta Verma .

Editor information

Editors and Affiliations

  1. Indian Institute of Public Administration, New Delhi, Delhi, India

    Usha Mujoo Munshi

  2. National Informatics Centre, New Delhi, Delhi, India

    Neeta Verma

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Verma, N., Gupta, M.P., Biswas, S. (2018). Open Data Infrastructure for Research and Development. In: Munshi, U., Verma, N. (eds) Data Science Landscape. Studies in Big Data, vol 38. Springer, Singapore. https://doi.org/10.1007/978-981-10-7515-5_2

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7515-5_2

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7514-8

  • Online ISBN: 978-981-10-7515-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation