Top

International Journal on Digital Libraries

Published in:

01-05-2015

VisInfo: a digital library system for time series research data based on exploratory search—a user-centered design approach

Authors: Jürgen Bernard, Debora Daberkow, Dieter Fellner, Katrin Fischer, Oliver Koepler, Jörn Kohlhammer, Mila Runnwerth, Tobias Ruppert, Tobias Schreck, Irina Sens

Published in: International Journal on Digital Libraries | Issue 1/2015

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

To this day, data-driven science is a widely accepted concept in the digital library (DL) context (Hey et al. in The fourth paradigm: data-intensive scientific discovery. Microsoft Research, 2009). In the same way, domain knowledge from information visualization, visual analytics, and exploratory search has found its way into the DL workflow. This trend is expected to continue, considering future DL challenges such as content-based access to new document types, visual search, and exploration for information landscapes, or big data in general. To cope with these challenges, DL actors need to collaborate with external specialists from different domains to complement each other and succeed in given tasks such as making research data publicly available. Through these interdisciplinary approaches, the DL ecosystem may contribute to applications focused on data-driven science and digital scholarship. In this work, we present VisInfo (2014) , a web-based digital library system (DLS) with the goal to provide visual access to time series research data. Based on an exploratory search (ES) concept (White and Roth in Synth Lect Inf Concepts Retr Serv 1(1):1–98, 2009), VisInfo at first provides a content-based overview visualization of large amounts of time series research data. Further, the system enables the user to define visual queries by example or by sketch. Finally, VisInfo presents visual-interactive capability for the exploration of search results. The development process of VisInfo was based on the user-centered design principle. Experts from computer science, a scientific digital library, usability engineering, and scientists from the earth, and environmental sciences were involved in an interdisciplinary approach. We report on comprehensive user studies in the requirement analysis phase based on paper prototyping, user interviews, screen casts, and user questionnaires. Heuristic evaluations and two usability testing rounds were applied during the system implementation and the deployment phase and certify measurable improvements for our DLS. Based on the lessons learned in VisInfo, we suggest a generalized project workflow that may be applied in related, prospective approaches.

previous article Towards robust tags for scientific publications from natural language processing tools and Wikipedia

next article What lies beneath?: Knowledge infrastructures in the subseafloor biosphere and beyond

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Available only for authorised users

http://www.elsevier.de/.

http://demo.vis-info.info/.

Ahmed, Z., Yost, P., McGovern, A., Weaver, C.: Steerable clustering for visual analysis of ecosystems. EuroVA, 49–52 (2011)

Aigner, W., Miksch, S., Schumann, H., Tominski, C.: Visualization of Time-Oriented Data. Springer, London (2011). doi:10.1007/978-0-85729-079-3 CrossRef

Ailamaki, A., Kantere, V., Dash, D.: Managing scientific data. Commun. ACM 53(6), 68–78 (2010)CrossRef

Belkin, N., Dumais, S., Scholtz, J., Wilkinson, R.: Evaluating interactive information retrieval systems. In: Extended abstracts of the 2004 conference on Human factors and computing systems - CHI ’04, p. 1594. ACM Press, New York (2004). doi:10.1145/985921.986162

Bernard, J., Brase, J., Fellner, D., Koepler, O., Kohlhammer, J., Ruppert, T., Schreck, T., Sens, I.: A visual digital library approach for time-oriented scientific primary data. Springer Int. J. Digit. Libr., ECDL 2010 Special Issue 11(2), 111–123 (2011)

Bernard, J., König-Langlo, G., Sieger, R.: Time-oriented earth observation measurements from the baseline surface radiation network (bsrn) in the years 1992 to 2012, reference list of 6813 datasets. (2012). DOI doi:10.1594/PANGAEA.787726

Bernard, J., Ruppert, T., Goroll, O., May, T., Kohlhammer, J.: Visual-interactive preprocessing of time series data. In: Kerren, A., Seipel, S. (eds.) SIGRAD, vol. 81, pp. 39–48. Linköping University Electronic Press, Sweden (2012)

Bernard, J., Ruppert, T., Scherer, M., Kohlhammer, J., Schreck, T.: Content-based layouts for exploratory metadata search in scientific research data. In: Proceedings of JCDL, pp. 139–148. ACM (2012)

Bernard, J., Ruppert, T., Scherer, M., Schreck, T., Kohlhammer, J.: Guided discovery of interesting relationships between time series clusters and metadata properties. In: Proceedings of i-KNOW, pp. 22:1–22:8. ACM (2012). DOI doi:10.1145/2362456.2362485

10.

Bernard, J., Steiger, M., Widmer, S., LckeTieke, H., May, T., Kohlhammer, J.: Visual-interactive exploration of interesting multivariate relations in mixed research data sets. Comput. Graph. Forum 33(3), 291–300 (2014). doi:10.1111/cgf.12385 CrossRef

11.

Bernard, J., Wilhelm, N., Krüger, B., May, T., Schreck, T., Kohlhammer, J.: MotionExplorer: exploratory search in human motion capture data based on hierarchical aggregation. IEEE TVCG 19(12), 2257–2266 (2013). doi:10.1109/TVCG.2013.178

12.

Bernard, J., Wilhelm, N., Scherer, M., May, T., Schreck, T.: TimeSeriesPaths: projection-based explorative analysis of multivariate time series data. J. WSCG 20, 97–106 (2012)

13.

Borgman, C., Wallis, J.C., Enyedy, N.: Building Digital Libraries for Scientific Data: An Exploratory Study of Data Practices in Habitat Ecology. In: ECDL 2006, pp. 170–183. Springer. LINCS (2006)

14.

Brase, J.: Datacite - A Global Registration Agency for Research Data. In: Cooperation and Promotion of Information Resources in Science and Technology, 2009. COINFO ’09, pp. 257–261 (2009)

15.

Candela, L., Castelli, D., Ferro, N., Koutrika, G., Meghini, C., Pagano, P., Ross, S., Soergel, D., Agosti, M., Dobreva, M. (eds.): The DELOS Digital Library Reference model. Foundations for digital Libraries (Version 0.98). ISTI-CNR at Gruppo ALI, Pisa (2008). http://eprints.port.ac.uk/4104/

16.

Card, S.K., Mackinlay, J.D., Shneiderman, B. (eds.): Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann Publishers Inc., San Francisco (1999)

17.

Costas, R., Meijer, I., Zahedi, Z., Wouters, P.: The value of research data-metrics for datasets from a cultural and technical point of view. A Knowledge Exchange Report. Available from: www.knowledge-exchange.info/datametrics (2013)

18.

Davenport, T.H., Patil, D., et al.: Data scientist: the sexiest job of the 21st century. Harv. Bus. Rev. 90(10), 70–77 (2012)

19.

Deelman, E., Gannon, D., Shields, M., Taylor, I.: Workflows and e-science: an overview of workflow system features and capabilities. Future Gener. Comput. Syst. 25(5), 528–540 (2009). doi:10.1016/j.future.2008.06.012 CrossRef

20.

Duke, M., Day, M., Heery, R., Carr, L.A., Coles, S.J.: Enhancing access to research data: the challenge of crystallography. In: Proceedings of JCDL, pp. 46–55. ACM, New York, NY, USA (2005)

21.

Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery: An overview. In: Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P., Uthurusamy, R. (eds.) Advances in Knowledge Discovery and Data Mining, pp. 1–34. American Association for Artificial Intelligence, Menlo Park, CA, USA (1996)

22.

Fu, Tc: A review on time series data mining. Eng. Appl. Artif. Intell 24(1), 164–181 (2011). doi:10.1016/j.engappai.2010.09.007 CrossRef

23.

Fuchs, R., Hauser, H.: Visualization of multi-variate scientific data. Comput. Graph. Forum 28, 1670–1690 (2009)CrossRef

24.

Hearst, M.A.: Search User Interfaces, 1st edn. Cambridge University Press, Cambridge (2009)CrossRef

25.

Herrmannova, D., Knoth, P.: Visual search for supporting content exploration in large document collections. D-Lib Magazine 18, 7–8 (2012)

26.

Hey, A.J.G., Tansley, S., Tolle, K.M.: The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research (2009)

27.

Hill, L.L., Carver, L., Larsgaard, M., Dolin, R., Smith, T.R., Frew, J., Rae, M.A.: Alexandria digital library: user evaluation studies and system design. J. ASIS 51(3), 246–259 (2000). doi:10.1002/(SICI)1097-4571(2000)51:3<246::AID-ASI4>3.0.CO;2-6

28.

Hoeber, O.: User Evaluation Methods for Visual Web Search Interfaces. 2009 13th International Conference Information Visualisation pp. 139–145 (2009). doi:10.1109/IV.2009.21

29.

Hull, D., Pettifer, S.R., Kell, D.B.: Defrosting the digital library: bibliographic tools for the next generation web. PLos Comput. Biol. 4(10):e1000204 (2008)

30.

Jeng, J.: Usability assessment of academic digital libraries: effectiveness, efficiency, satisfaction, and learnability. Libri 55(2–3), 96–121 (2005). doi:10.1515/LIBR.2005.96

31.

Jeng, J.H.: Usability of digital libraries. In: Proceedings of JCDL, p. 407. ACM Press, New York, NY, USA (2004). doi:10.1145/996350.996473

32.

John, B.E.: Evaluating usability evaluation techniques. ACM Comput. Surv. 28(4es), 139-es (1996)CrossRef

33.

Kehrer, J., Hauser, H.: Visualization and visual analysis of multifaceted scientific data: A survey. IEEE TVCG 19(3), 495–513 (2013). doi:10.1109/TVCG.2012.110

34.

Keim, D., Kohlhammer, J., Ellis, G., Mansmann, F. (eds.): Mastering the Information Age: Solving Problems with Visual Analytics. Eurographics Association, Aire-la-Ville (2011)

35.

Keogh, E., Chakrabarti, K., Pazzani, M., Mehrotra, S.: Dimensionality reduction for fast similarity search in large time series databases. J. Knowl. Inf. Syst. 3, 263–286 (2000)CrossRef

36.

Kohonen, T., Schroeder, M.R., Huang, T.S. (eds.): Self-Organizing Maps, 3rd edn. Springer-Verlag New York Inc, Secaucus, NJ, USA (2008)

37.

Lewis, C., Polson, P.G., Wharton, C., Rieman, J.: Testing a walkthrough methodology for theory-based design of walk-up-and-use interfaces. In: Proceedings of the SIGCHI, pp. 235–242. ACM Press, New York, NY, USA (1990). doi:10.1145/97243.97279

38.

Liao, T.W.: Clustering of time series data-a survey. Pattern Recognit. 38, 1857–1874 (2005)CrossRefMATH

39.

Ludäscher, B., Lin, K., Bowers, S., Jaeger-Frank, E., Brodaric, B., Baru, C.: Managing scientific data: from data integration to scientific workflows. Geoinformatics: Data to Knowledge, Geolog. Society of America Special Paper 397 pp. 109–129 (2006)

40.

Marchionini, G.: Exploratory search: from finding to understanding. Commun. ACM 49(4), 41–46 (2006)CrossRef

41.

Marcial, L.H., Hemminger, B.M.: Scientific data repositories on the web: an initial survey. JASIST 61(10), 2029–2048 (2010)CrossRef

42.

Munzner, T.: A nested model for visualization design and validation. IEEE Trans. Vis. Comput. Graph. 15(6), 921–928 (2009). doi:10.1109/tvcg.2009.111 CrossRef

43.

Nielsen, J.: The usability engineering life cycle. Computer 25(3), 12–22 (1992). doi:10.1109/2.121503 CrossRef

44.

Nielsen, J., Landauer, T.K.: A mathematical model of the finding of usability problems. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems—CHI ’93, pp. 206–213. ACM Press, New York (1993). doi:10.1145/169059.169166

45.

Nielsen, J., Molich, R.: Heuristic evaluation of user interfaces. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems Empowering People–CHI ’90, April, pp. 249–256. ACM Press, New York (1990). DOI doi:10.1145/97243.97281

46.

Nocke, T., Sterzel, T., Böttinger, M., Wrobel, M.: Visualization of climate and climate change data: an overview. Digital Earth Summit on Geoinformatics 2008, Tools for Global Change Research, pp. 226–232. Herbert Wichmann, Heidelberg (2008)

47.

Ohmura, A., Dutton, E.G., Forgan, B., Fröhlich, C., Gilgen, H., Hegner, H., Heimo, A., König-Langlo, G., Mcarthur, B., Müller, G., Philipona, R., Pinker, R., Whitlock, C.D., Dehne, K., Wild, M.: Baseline surface radiation network (BSRN/WCRP): new precision radiometry for climate research. Bull. Am. Met. Soc. 79, 2115–2136 (1998)

48.

PANGAEA—Data Publisher for Earth and Environmental Science: http://www.pangaea.de/. Accessed 14 Oct 2014. doi:10.1594/pangaea

49.

Plaisant, C.: The challenge of information visualization evaluation. In: Proceedings of the Working Conference on Advanced Visual Interfaces, pp. 109–116. ACM Press, New York (2004). doi:10.1145/989863.989880

50.

Reeves, T.C., Buhr, S., Barker, L.: Evaluating digital libraries: toward evolution of concepts. In: Proceedings of JCDL, vol. 49, p. 420. ACM Press, New York (2005). doi:10.1145/1065385.1065525

51.

Rubin, J., Chisnell, D.: Handbook of Usability Testing: How to Plan, Design, and Conduct Effective Tests, 2nd edn. Wiley, Indianapolis (2008)

52.

Ruppert, T., Bernard, J., Kohlhammer, J.: Bridging knowledge gaps in policy analysis with information visualization. In: EGOV/ePart Ongoing Research, LNI, vol. 221, pp. 92–103. GI (2013)

53.

Salvador, S., Chan, P.: Toward accurate dynamic time warping in linear time and space. Intell. Data Anal. 11(5), 561–580 (2007)

54.

Saracevic, T.: Digital library evaluation: toward evolution of concepts. Libr. Trend 49(2), 350–369 (2000)

55.

Scherer, M., Bernard, J., Schreck, T.: Retrieval and exploratory search in multivariate research data repositories using regressional features. In: Proceedings of JCDL, pp. 363–372. ACM, New York (2011)

56.

Schreck, T., Bernard, J., Tekušová, T., Kohlhammer, J.: Visual cluster analysis of trajectory data with interactive Kohonen maps. Palgrave Macmillan Inf. Vis. 8, 14–29 (2009). http://www.palgrave-journals.com/doifinder/10.1057/ivs.2008.29

57.

SDSS—The Sloan Digital Sky Survey. http://www.sdss.org/. Accessed 15 Oct 2014

58.

Sedlmair, M., Meyer, M., Munzner, T.: Design study methodology: reflections from the trenches and the stacks. IEEE Trans. Vis. Comput. Graph. (Proc. InfoVis) 18(12), 2431–2440 (2012)CrossRef

59.

Shackel, B.: Usability context, framework, definition, design and evaluation. In: Shackel, B., Richardson, S.J. (eds.) Human Factors for Informatics Usability, pp. 21–37. Cambridge University Press, New York (1991)

60.

Sheble, L.: Greenstone User and Developer Survey 2009 (2009). http://greenstonesurvey.wordpress.com/infosheet/

61.

Stein, L.D.: Towards a cyberinfrastructure for the biological sciences: progress, visions and challenges. Nat. Rev. Genet. 9(9), 678–688 (2008)CrossRef

62.

Strötgen, J., Gertz, M.: Event-centric search and exploration in document collections. In: Proceedings of JCDL, pp. 223–232. ACM, New York (2012)

63.

Suber, P.: Open Access. MIT Press, Cambridge (2012)

64.

Tominski, C., Donges, J.F., Nocke, T.: Information visualization in climate research. In: Information Visualisation, pp. 298–305. IEEE Computer Society, Washington (2011)

65.

Tsatsaronis, G., Varlamis, I., Torge, S., Reimann, M., Nørvåg, K., Schroeder, M., Zschunke, M.: How to become a group leader? Or modeling author types based on graph mining. In: Proceedings of TPDL, pp. 15–26. Springer, Berlin (2011)

66.

Van Wijk, J., Van Selow, E.: Cluster and calendar based visualization of time series data. In: Symposium on Information Visualization, pp. 4–9. IEEE Comp. Soc. (1999)

67.

VisInfo—Visual Access to Time-oriented Research Data. http://demo.vis-info.info/. Accessed 14 Oct 2014

68.

White, R., Roth, R.: Exploratory search: beyond the query-response paradigm. Synth. Lect. Inf. Concepts Retr. Serv. 1(1), 1–98 (2009)

69.

Yuan, X., Zhang, X., Trofimovsky, A.: Testing visualization on the use of information systems. In: Proceedings of IIiX, p. 365 (2010). doi:10.1145/1840784.1840840

70.

Ziegler, H., Jenny, M., Gruse, T., Keim, D.: Visual market sector analysis for financial time series data. In: Proceedings of VAST, pp. 83–90 (2010). doi:10.1109/VAST.2010.5652530

Title: VisInfo: a digital library system for time series research data based on exploratory search—a user-centered design approach
Authors: Jürgen Bernard
Debora Daberkow
Dieter Fellner
Katrin Fischer
Oliver Koepler
Jörn Kohlhammer
Mila Runnwerth
Tobias Ruppert
Tobias Schreck
Irina Sens
Publication date: 01-05-2015
Publisher: Springer Berlin Heidelberg
Published in: International Journal on Digital Libraries / Issue 1/2015
Print ISSN: 1432-5012
Electronic ISSN: 1432-1300
DOI: https://doi.org/10.1007/s00799-014-0134-y

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 1/2015

The new knowledge infrastructure

Introduction to the special issue on digital scholarship

A pipeline for digital restoration of deteriorating photographic negatives

Exploring publication metadata graphs with the LODmilla browser and editor

What lies beneath?: Knowledge infrastructures in the subseafloor biosphere and beyond

Digital field scholarship and the liberal arts: results from a 2012–13 sandbox

Premium Partner