Skip to main content

Data Management Experiences and Best Practices from the Perspective of a Plant Research Institute

  • Conference paper
Data Integration in the Life Sciences (DILS 2014)

Abstract

Research in life sciences faces increasing amounts of cross-domain data, also kown as “big data”. This has notable effects on IT-departments and the dry lab desk alike. In this paper, we report on experiences from a decade of data management in a plant research institute. We explain the switch from personally managed files and heterogeneous information systems towards a centrally organised storage management. In particular, we discuss lessons that were learned within the last decade of productive research, data generation and software development from the perspective of a modern plant research institute and present the results of a strategic realignment of the data management infrastructure. Finally, we summarise the challenges which were solved and the questions which are still open.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 34.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 44.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Arend, D., Lange, M., Colmsee, C., Flemming, S., Chen, J., Scholz, U.: The e!DAL JAVA-API: Store, Share and Cite Primary Data in Life Sciences. In: IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Philadelphia, U.S.A., October 4-7, pp. 511–515 (2012)

    Google Scholar 

  2. Colmsee, C., Mascher, M., Czauderna, T., Hartmann, A., Schlüter, U., Zellerhoff, N., Schmitz, J., Bräutigam, A., Pick, T.R., Alter, P., Gahrtz, M., Witt, S., Fernie, A., Börnke, F., Fahnenstich, H., Bucher, M., Dresselhaus, T., Weber, A.P.M., Schreiber, F., Scholz, U., Sonnewald, U.: OPTIMAS-DW: A comprehensive transcriptomics, metabolomics, ionomics, proteomics and phenomics data resource for maize. BMC Plant Biology 12(1), e245 (2012)

    Google Scholar 

  3. Colmsee, C., Keller, E.R.J., Zanke, C., Senula, A., Funke, T., Oppermann, M., Weise, S., Scholz, U.: The Garlic and Shallot Core Collection image database of IPK presenting two vegetatively maintained crops in the Federal ex situ Genebank for Agricultural and Horticultural Crops at Gatersleben, Germany. Genetic Resources and Crop Evolution 59(7), 1407–1415 (2012)

    Article  Google Scholar 

  4. DataCite Consortium: DataCite, http://datacite.org/ (accessed January 2014)

  5. Grbavac, I., Koepler, O., Dohmeyer-Fischer, S., Fels, G., Sens, I., Brase, J.: Embedded infrastructure for primary data in chemistry. Journal of Cheminformatics 2(suppl. 1), P8 (2010)

    Google Scholar 

  6. Knüpffer, H., Ochsmann, J., Biermann, N.: The “Mansfeld Database” in its national and international context. Schriften zu Genetischen Ressourcen 22, 32–34 (2003)

    Google Scholar 

  7. Kuenne, C., Grosse, I., Matthies, I., Scholz, U., Sretenovic-Rajicic, T., Stein, N., Stephanik, A., Steuernagel, B., Weise, S.: Using Data Warehouse Technology in Crop Plant Bioinformatics. Journal of Integrative Bioinformatics 4(1), e88 (2007)

    Google Scholar 

  8. Künne, C., Lange, M., Funke, T., Miehe, H., Grosse, I., Scholz, U.: CR–EST: a resource for crop ESTs. Nucleic Acids Research 33(suppl.1), D619–D621 (2005)

    Google Scholar 

  9. Neuroth, H., Oßwald, A., Scheffel, R., Strathmann, S., Huth, K.: nestor Handbuch: Eine kleine Enzyklopädie der digitalen Langzeitarchivierung, Version 2.3 (2010), http://nestor.sub.uni-goettingen.de/handbuch/index.php (accessed January 2014)

  10. Schadt, E.E., Linderman, M.D., Sorenson, J., Lee, L., Nolan, G.P.: Computational solutions to large-scale data management and analysis. Nature Reviews Genetics 11(9), 647–657 (2010)

    Article  Google Scholar 

  11. Schreiber, F., Colmsee, C., Czauderna, T., Grafahrend-Belau, E., Hartmann, A., Junker, A., Junker, B.H., Klapperstück, M., Scholz, U., Weise, S.: MetaCrop 2.0: managing and exploring information about crop plant metabolism. Nucleic Acids Research 40(D1), D1173–D1177 (2012)

    Google Scholar 

  12. Swedlow, J.R., Zanetti, G., Best, C.: Channeling the data deluge. Nat. Methods 8(6), 463–465 (2011)

    Article  Google Scholar 

  13. Thaller, M.: Das Digitale Archiv NRW in der Praxis. Verlag Dr. Kovac (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Arend, D. et al. (2014). Data Management Experiences and Best Practices from the Perspective of a Plant Research Institute. In: Galhardas, H., Rahm, E. (eds) Data Integration in the Life Sciences. DILS 2014. Lecture Notes in Computer Science(), vol 8574. Springer, Cham. https://doi.org/10.1007/978-3-319-08590-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08590-6_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08589-0

  • Online ISBN: 978-3-319-08590-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics