Advertisement

International Journal on Digital Libraries

, Volume 11, Issue 2, pp 111–123 | Cite as

A visual digital library approach for time-oriented scientific primary data

  • Jürgen Bernard
  • Jan Brase
  • Dieter Fellner
  • Oliver Koepler
  • Jörn Kohlhammer
  • Tobias Ruppert
  • Tobias Schreck
  • Irina Sens
Article

Abstract

Digital Library support for textual and certain types of non-textual documents has significantly advanced over the last years. While Digital Library support implies many aspects along the whole library workflow model, interactive and visual retrieval allowing effective query formulation and result presentation are important functions. Recently, new kinds of non-textual documents which merit Digital Library support, but yet cannot be fully accommodated by existing Digital Library technology, have come into focus. Scientific data, as produced for example, by scientific experimentation, simulation or observation, is such a document type. In this article we report on a concept and first implementation of Digital Library functionality for supporting visual retrieval and exploration in a specific important class of scientific primary data, namely, time-oriented research data. The approach is developed in an interdisciplinary effort by experts from the library, natural sciences, and visual analytics communities. In addition to presenting the concept and to discussing relevant challenges, we present results from a first implementation of our approach as applied on a real-world scientific primary data set. We also report from initial user feedback obtained during discussions with domain experts from the earth observation sciences, indicating the usefulness of our approach.

Keywords

Visual search Content-based retrieval Time series Scientific research data Visual cluster analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Agosti, M., Berretti, S., Brettlecker, G., Bimbo, A.D., Ferro, N., Fuhr, N., Keim, D.A., Klas, C.P., Lidy, T., Milano, D., Norrie, M.C., Ranaldi, P., Rauber, A., Schek, H.J., Schreck, T., Schuldt, H., Signer, B., Springmann, M.: Delosdlms—the integrated delos digital library management system. In: DELOS Conference, pp. 36–45 (2007)Google Scholar
  2. 2.
    Agrawal, R., Faloutsos, C., Swami, A.: Efficient similarity search in sequence databases. In: Lecture Notes in Computer Science, pp. 69–69 (1993)Google Scholar
  3. 3.
    Agrawal, R., Lin, K., Sawhney, H., Shim, K.: Fast similarity search in the presence of noise, scaling, and translation in time-series databases. In: Proceedings of the International Conference on Very Large Data Bases, pp. 490–501 (1995)Google Scholar
  4. 4.
    Ahlberg, C., Shneiderman, B.: Visual information seeking: tight coupling of dynamic query filters with starfield displays. In: Proceedings of the SIGCHI conference on Human factors in computing systems: celebrating interdependence, pp. 313–317 (1994)Google Scholar
  5. 5.
    Aigner W., Miksch S., Muller W., Schumann H., Tominski C.: Visualizing time-oriented data—a systematic view. Comput. Graphics 31(3), 401–409 (2007)CrossRefGoogle Scholar
  6. 6.
    Bamboo Research Initiative: http://projectbamboo.org/. Accessed 20 May 2011
  7. 7.
    Baseline Surface Radiation Network (BSRN): http://www.bsrn.awi.de/. Accessed 20 May 2011
  8. 8.
    Berndt, R., Blümel, I., Clausen, M., Damm, D., Diet, J., Fellner, D., Fremerey, C., Klein, R., Krahl, F., Scherer, M., Schreck, T., Sens, I., Thomas, V., Wessel, R.: The PROBADO project—approach and lessons learned in building a digital library system for heterogeneous non-textual documents. In: European Conference on Digital Libraries, Lecture Notes in Computer Science, vol. 6273, pp. 376–383 (2010)Google Scholar
  9. 9.
    Brase, J.: Using digital library techniques-Registration of scientific primary data. In: Lecture Notes in Computer Science, pp. 488–494 (2004)Google Scholar
  10. 10.
    Castelli, D., Pagano, P.: Opendlib: a digital library service system. In: ECDL, pp. 292–308 (2002)Google Scholar
  11. 11.
    Chan, K., Fu, A.: Efficient time series matching by wavelets. In: Proceedings of the 15th IEEE International Conference on Data Engineering, 1999, pp. 126–133 (2002)Google Scholar
  12. 12.
    Chang, R., Charlotte, U., Ghoniem, M., Kosara, R., Ribarsky, W., Yang, J., Suma, E., Kern, D., Sudjianto, A.: Wirevis: visualization of categorical, time-varying data from financial transactions. In: Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (2007)Google Scholar
  13. 13.
    Dryad Digital Repository for Data Underlying Published Works: http://www.datadryad.org/. Accessed 20 May 2011
  14. 14.
    Dunn, J.W., Mayer, C.A.: Variations: a digital music library system at indiana university. In: DL ’99: Proceedings of the fourth ACM conference on Digital libraries, ACM, New York, NY, USA, pp. 12–19 (1999)Google Scholar
  15. 15.
    ELIXIR European Life Sciences Infrastructure for Biological Information.: http://www.elixir-europe.org/. Accessed 20 May 2011
  16. 16.
    German Research Foundation (DFG).: Report on round table meeting of research data (in German). Whitepaper (2008). http://www.dfg.de/download/pdf/foerde-rung/programme/lis/forschungsprimaerdaten_0108.pdf. Accessed 20 May 20 2011
  17. 17.
    Hochheiser H., Shneiderman B.: Dynamic query tools for time series data sets: timebox widgets for interactive exploration. Inf. Vis. 3(1), 1–18 (2004)CrossRefGoogle Scholar
  18. 18.
    Keogh E., Chakrabarti K., Pazzani M., Mehrotra S.: Dimensionality reduction for fast similarity search in large time series databases. Knowl. Inform. Syst. 3(3), 263–286 (2001)CrossRefGoogle Scholar
  19. 19.
    Kohonen T.: Self-Organizing Maps. 3rd edn. Springer, New York (2001)CrossRefGoogle Scholar
  20. 20.
    Lagoze C., Payette S., Shin E., Wilper C.: Fedora: an architecture for complex objects and their relationships. Int. J. Digit. Libr. 6(2), 124–138 (2006)CrossRefGoogle Scholar
  21. 21.
    Liao T.W.: Clustering of time series data—a survey. Pattern Recognit. 38, 1857–1874 (2005)CrossRefGoogle Scholar
  22. 22.
    Lin, J., Keogh, E., Lonardi, S., Chiu, B.: A symbolic representation of time series, with implications for streaming algorithms. In: Proceedings of ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (2003)Google Scholar
  23. 23.
    PANGAEA Publishing Network for Geoscientific & Environmental Data: http://www.pangaea.de/. Accessed 20 May 2011
  24. 24.
    PsychData National Repository for Psychological Research Data: http://psychdata.zpid.de/ (in German). Accessed 20 May 2011
  25. 25.
    Schreck, T., Bernard, J., Von Landesberger, T., Kohlhammer, J.: Visual cluster analysis of trajectory data with interactive kohonen maps. Inform. Vis. 8(1), 14–29 (2009)Google Scholar
  26. 26.
    Shneiderman, B.: The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings of the 1996 IEEE Symposium on Visual Languages, IEEE Computer Society, Washington, DC, pp. 336–343 (1996)Google Scholar
  27. 27.
    Sieger, R., Grobe, H., Diepenbroek, M.: Panplot—software to visualize profiles and core logs. Alfred Wegener Institute for Polar and Marine Research, Bremerhaven (2005). doi: https://doi.org/10.1594/PANGAEA.330147
  28. 28.
    Šimunić, K.: Visualization of stock market charts. In: Proceedings of International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (2003)Google Scholar
  29. 29.
    Society for Scientific Data Processing Goettingen: Cooperative long-term preservation for research centers (in German). Project Report (2009)Google Scholar
  30. 30.
    Van Wijk, J., Van Selow, E.: Cluster and calendar based visualization of time series data. In: IEEE Symposium on Information Visualization 1999 (Info Vis’ 99), pp. 4–9 (1999)Google Scholar
  31. 31.
    Wattenberg, M.: Sketching a graph to query a time-series database. In: CHI ’01 extended abstracts on Human factors in computing systems, CHI ’01, pp. 381–382 (2001)Google Scholar
  32. 32.
    Witten, I.H., Mcnab, R.J., Boddie, S.J., Bainbridge, D.: Greenstone: A comprehensive open-source digital library software system. In: Proceedings of the Fifth ACM International Conference on Digital Libraries (2000)Google Scholar
  33. 33.
    World Data Center System: http://www.ngdc.noaa.gov/wdc. Accessed 20 May 2011
  34. 34.
    Ziegler, H., Jenny, M., Gruse, T., Keim, D.: Visual market sector analysis for financial time series data. In: IEEE Symposium on Visual Analytics Science and Technology, pp. 83–90 (2010)Google Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Jürgen Bernard
    • 1
  • Jan Brase
    • 2
  • Dieter Fellner
    • 3
  • Oliver Koepler
    • 2
  • Jörn Kohlhammer
    • 3
  • Tobias Ruppert
    • 3
  • Tobias Schreck
    • 4
  • Irina Sens
    • 2
  1. 1.Technische Universität DarmstadtDarmstadtGermany
  2. 2.German National Library of Science and TechnologyHannoverGermany
  3. 3.Fraunhofer IGDDarmstadtGermany
  4. 4.University of KonstanzKonstanzGermany

Personalised recommendations