Skip to main content
Log in

A digital library framework for biodiversity information systems

  • Regular Paper
  • Published:
International Journal on Digital Libraries Aims and scope Submit manuscript

Abstract

Biodiversity Information Systems (BISs) involve all kinds of heterogeneous data, which include ecological and geographical features. However, available information systems offer very limited support for managing these kinds of data in an integrated fashion. Furthermore, such systems do not fully support image content (e.g., photos of landscapes or living organisms) management, a requirement of many BIS end-users. In order to meet their needs, these users—e.g., biologists, environmental experts—often have to alternate between separate biodiversity and image information systems to combine information extracted from them. This hampers the addition of new data sources, as well as cooperation among scientists. The approach provided in this paper to meet these issues is based on taking advantage of advances in digital library innovations to integrate networked collections of heterogeneous data. It focuses on creating the basis for a next-generation BIS, combining new techniques of content-based image retrieval and database query processing mechanisms. This paper shows the use of this component-based architecture to support the creation of two tailored BIS systems dealing with fish specimen identification using search techniques. Experimental results suggest that this new approach improves the effectiveness of the fish identification process, when compared to the traditional key-based method.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Analyst, S.: http://www.speciesanalyst.net (as of October 2004).

  2. BioGIS: BioGIS—Israel Biodiversity Information System. http://www.eti.uva.nl/(as of October 2004).

  3. BIOTA/FAPESP: SinBiota (Sao Paulo Stateapos; Biodiversity Information System). http://www.biota.org.br/sia (as of October 2004).

  4. OAI: Open Archives Initiative. http://www.openarchives.org (as of October 2004)

  5. Lagoze, C., de Sompel, H.V.: The Open archives initiative: building a low-barrier interoperability framework. In: Proceedings of the Joint Conference on Digital Libraries, pp. 54–62. Roanoke, VA, USA (2001)

  6. da S. Torres, R., da Silva, C.G., Medeiros, C.B., da Rocha, H.V.: Visual structures for image browsing. In: Proceedings of the Twelfth International Conference on Information and Knowledge Management, pp. 167–174. New Orleans, LA, USA (2003)

  7. XMLFile: http://www.dlib.vt.edu/projects/OAI/software/oai-file/oai-file.html (as of October 2004)

  8. Suleman, H.: Open digital libraries. PhD thesis, Computer Science Department, Virginia Tech, Blacksburg, VA (2002), http://scholar.lib.vt.edu/theses/available/etd-11222002-155624/unrestricted/odl.pdf

  9. ESSEX: http://br.endernet.org/∼akrowne/elaine/essex/index.html (as of October 2004).

  10. CITIDEL: Computing and Information Technology Interactive Digital Educational Library. http://www.citidel.org (as of October 2004).

  11. PlanetMath: http://planetmath.org/(as of October 2004)

  12. Flickner, M., Sawhney, H., Niblack, W., Ashley, Q.H.J., Dom, B., Gorkani, M., Hafner, J., Lee, D., Petkovic, D., Steele, D., Yanker, P.: Query by image and video content: The QBIC System. IEEE Computer 28(9), 23–32 (1995)

    Google Scholar 

  13. Ogle, V.E., Stonebraker, M.: Chabot: retrieval from relational database of images. IEEE Comput. 28(9), 40–48 (1995)

    Google Scholar 

  14. Bach, J.R., Fuller, C., Gupta, A., Hampapur, A., Horowitz, B., Humphrey, R., Jain, C.-F.S.R.: Virage image search engine: an open framework for image management. In: Storage and Retrieval for Image and Video Databases (SPIE), pp. 76–87. Bellingham, WA, USA (1996)

  15. Ciaccia, P., Patella, M., Zezula, P.: M-tree: An efficient access method for similarity search in metric spaces. In: Proceedings of 23rd International Conference on Very Large Data Bases, pp. 426–435. Athens, Greece (1997)

  16. den Bercken, J.V., Blohsfeld, B., Dittrich, J.-P., Krämer, J., Schäfer, T., Schneider, M., Seeger, B.: XXL—A Library Approach to supporting efficient implementations of advanced database queries. In: Proceedings of the 27th International Conference on Very Large Data Bases, pp. 39–48. Roma, Italy (2001)

  17. Cammert, M., Heinz, C., Kramer, J., Schneider, M., Seeger, B.: A status report on XXL—a software infrastructure for efficient query processing. Data Eng. Bull. 26(2), 12–18 (2003)

    Google Scholar 

  18. Suleman, H., Fox, E., Krowne, A., Luo, M.: Building digital libraries from simple building blocks. Technical Report TR-03-09, Computer Science Department, Virginia Tech, Blacksburg, VA, USA (2003), http://eprints.cs.vt.edu:8000/archive/00000656/

  19. Suleman, H., Fox, E.A., Kelapure, R., Krowne, A., Luo, M.: Building digital libraries from simple building blocks. Online Inform. Rev. 27(5), 301–310 (2003)

    Google Scholar 

  20. XMLSpy: http://www.xmlspy.com/(as of October 2004)

  21. Sebastian, T.B., Kimia, B.B.: Curves vs. skeletons in object recognition. Sign. Process. 85(2), 247–263 (2005)

    Google Scholar 

  22. Swain, M., Ballard, D.: Color indexing. Int. J. Comput. Vision 7(1), 11–32 (1991)

    Article  Google Scholar 

  23. da S. Torres, R., Falcão, A.X., da F. Costa, L.: A graph-based approach for multiscale shape analysis. Pattern Recogn. 37(6), 1163–1174 (2004)

    Google Scholar 

  24. da S. Torres, R., Picado, E.M., Falcão, A.X., da F. Costa, L.: Effective Image Retrieval by Shape Saliences. In: Proceedings of the Brazilian Symposium on Computer Graphics and Image Processing, pp. 49–55. São Carlos, SP, Brazil (2003)

  25. Mokhtarian, F., Abbasi, S.: Shape similarity retrieval under affine transforms. Pattern Recogn. 35(1), 31–41 (2002)

    Article  Google Scholar 

  26. Arica, N., Vural, F.T.Y.: BAS: A perceptual shape descriptor based on the beam angle statistics. Pattern Recogn. Lett. 24(9/10), 1627–1639 (2003)

    Google Scholar 

  27. da S. Torres, R., Falcão, A.X., Costa, L. da F.: Shape description by image foresting transform. In: Proceedings of the 14th International Conference on Digital Signal Processing, Vol. 2, pp. 1089–1092. Santorini, Greece (2002)

  28. Stehling, R., Nascimento, M., Falcão, A.: A compact and efficient image retrieval approach based on border/interior pixel classification. In: Proceedings of the 11th ACM International. Conference on Information and Knowledge Management, pp. 102–109. McLean, Virginia, USA (2002)

  29. Goncalves, M.A., Marther, P., Wang, J., Zhou, Y., Luo, M., Richardson, R., Shen, R., Xu, L., Fox, E.A.: Java MARIAN: From an OPAC to a modern digital library system. In: String Processing and Information Retrieval: 9th International Symposium, SPIRE 2002, pp. 194–209. Lisbon, Portugal (2002)

  30. FishBase: http://www.fishbase.org (as of October 2003)

  31. Jenkins, R.E., Burkhead, N.M.: Freshwater Fishes of Virginia. American Fisheries Society, Bethesda, MD (1993)

    Google Scholar 

  32. Helfrich, L., Newcomb, T., Halleman, E., Stein, K.: EFISH, http://www.cnr.edu/efish (as of October 2004)

  33. Sanchez, J., Lopez, C., Schnase, J.: An agent-based approach to the construction of floristic digital libraries. In: Proceedings of the 3rd ACM International Conference on Digital Libraries, pp. 210–216. Pittsburgh, PA, ACM Press (1998)

  34. Sanchez, J.A., Fernandez, L., Schnase, J.L.: Agora: Enhancing group awareness and collaboration in floristic digital libraries. In: Proceedings of the Fourth International Workshop on Groupware, pp. 85–95. Rio de Janeiro (1998)

  35. Sanchez, J.A., Flores, C.A., Schnase, J.L.: Mutant: agents as guides for multiple taxonomies in the floristic digital library. In: Proceedings of the Fourth ACM Conference on Digital Libraries, pp. 244–245. ACM Press, Berkeley, CA (1999)

  36. Hong, J.S., Chen, H., Hsiang, J.: A Digital Museum of Taiwanese Butterflies. In: Proceedings of the Fifth ACM Conference on Digital Libraries, pp. 260–261. ACM Press, San Antonio, TX (2000)

  37. Zhu, B., Ramsey, M., Chen, H.: Creating a large-scale content-based airphoto image digital library. IEEE Trans. Image Process. 9(1), 163–167 (2000)

    Google Scholar 

  38. Smith, T.R.: A digital library for geographically referenced materials. IEEE Comput. 29(5), 54–60 (1996)

    Google Scholar 

  39. Janee, G., Frew, J.: The ADEPT Digital Library Architecture. In: Proceeding of the Second ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 342–350, ACM Press, Portland, OR (2002)

  40. Rui, Y., Huang, T.S., Chang, S.F.: Image retrieval: Current techniques, promising directions, and open issues. Journal of Communications and Image Representation 10(1), 39–62 (1999)

    Google Scholar 

  41. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the years. IEEE Trans. Pattern Anal. Machine Intell. 22(12), 1349–1380 (2000)

    Article  Google Scholar 

  42. del Bimbo, A.: Visual Information Retrieval. Morgan Kaufmann, San Francisco, CA (1999)

  43. Lew, M.S. (ed.), Principles of Visual Information Retrieval—Advances in Pattern Recognition. Springer-Verlag, London Berlin Heidelberg (2001)

  44. Yoshitaka, A.: A survey on content-based retrieval for multimedia databases. IEEE Trans. Knowledge Data Eng. 11(1), 56–63 (1999)

    Article  Google Scholar 

  45. Aslandogan, Y.A., Yu, C.T.: Techniques and systems for image and video retrieval. IEEE Trans. Knowledge Data Eng. 11(1), 56–63 (1999)

    Article  Google Scholar 

  46. Antani, A., Kasturi, R., Jain, R.: A Survey on the use of pattern recognition methods for abstraction, indexing and retrieval of images and video. Pattern Recogn. 35(4), 945–965 (2002)

    Article  Google Scholar 

  47. Castelli, V., Bergman, L.D. (eds.): Image Databases. Search and Retrieval of Digital Imagery. Wiley, New York (2002)

    Google Scholar 

  48. Bhm, C., Berchtold, S., Keim, D.A.: Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases. ACM Comput. Surveys (CSUR) 33(3), 322–373 (2001).

    Google Scholar 

  49. Zhang, D., Lu, G.: Review of shape representation and description. Pattern Recogn. 37(1), 1–19 (2004)

    Google Scholar 

  50. Lewis, P.H., Martinez, K., Abas, F.S., Fauzi, M.F.A., Chan, S.C.Y., Addis, M.J., Boniface, M.J., Grimwood, P., Stevenson, A., Lahanier, C., Stevenson, J.: An integrated content and metadata based retrieval system for art. IEEE Trans. Image Process. 13(3), 302–313 (2004)

    Article  Google Scholar 

  51. Muller, H., Michoux, N., Bandon, D., Geissbuhler, A.: A review of content-based image retrieval systems in medical applications—clinical benefits and future directions. Int. J. Med. Inform. 73(1), 1–23 (2004)

    Google Scholar 

  52. Natsev, A., Rastogi, R., Shim, K.: WALRUS: A similarity retrieval algorithm for image database. IEEE Trans. Knowledge Data Eng. 16(3), 301–316 (2004)

    Article  Google Scholar 

  53. Evgeniou, T., Pontil, M., Papageorgiou, C., Poggio, T.: Image representations and feature selection for multimedia database search. IEEE Trans. Knowledge Data Eng. 15(4), 911–920 (2003)

    Article  Google Scholar 

  54. El-Naqa, I., Yang, Y., Galatsanos, N.P., Nishikawa, R.M., Wernick, M.N.: A similarity learning approach to content-based image retrieval: Application to digital mammography. IEEE Trans. Med. Imag. 23(10), 1233–1244 (2004)

    Google Scholar 

  55. Carson, C., Belongie, S., Greenspan, H., Malik, J.: Blobworld: Image segmentation using expectation-maximization and its application to image querying. IEEE Trans. Pattern Anal. Machine Intell. 24(8), 1026–1038 (2002)

    Article  Google Scholar 

  56. Vu, K., Hua, K.A., Tavanapong, W.: Image retrieval based on regions of interest. IEEE Trans. Knowledge Data Eng. 15(4), 1045–1049 (2003)

    Google Scholar 

  57. PicHunter, I.J., Miller, M.L., Minka, T.P., Papathomas, T.V., Yianilos, P.N.: The bayesian image retrieval system, pichunter: theory, implementation, and psychophysical experiments. IEEE Trans. Image Process. 9(1), 20–37 (2000)

    Google Scholar 

  58. Christel, M.G., Olligschlaeger, A.M., Huang, C.: Interactive maps for a digital video library. IEEE Multimedia 7(1), 60–67 (2000)

    Article  Google Scholar 

  59. Lu, Y., Zhang, H., Wenyin, L., Hu, C.: Joint semantics and feature based image retrieval using relevance feedback. IEEE Trans. Multimedia 5(3), 339–347 (2003)

    Google Scholar 

  60. Nakagawa, A., Kutics, A., Tanaka, K., Nakajima, M.: Combining words and object-based visual features in image retrieval. In: Proceedings of the 12th International Conference on Image Anal. Process., pp. 354–359. Mantova, Italy (2003)

  61. Zhao, R., Grosky, W.I.: Narrowing the semantic gap—improved text-based web document retrieval using visual features. IEEE Trans. Multimedia 4(3), 189–200 (2002)

    Google Scholar 

  62. Zhou, X.S., Huang, T.S.: Unifying keywords and visual contents in image retrieval. IEEE Multimedia 4(2), 23–33 (2002)

    Google Scholar 

  63. Sclaroff, S., Cascia, M.L., Sethi, S.: Unifying textual and visual cues for content-based image retrieval on the World Wide Web. Comput. Vision Image Understand. 75(1/2), 86–98 (1999)

    Google Scholar 

  64. Sikora, T.: The MPEG-7 visual standard for content description – An overview. IEEE Transactions on Circuits and Systems for Video Technology 11(6), 696–902 (2001)

    Article  MathSciNet  Google Scholar 

  65. Chang, S.F., Sikora, T., Puri, A.: Overview of the MPEG-7 standard. IEEE Trans. Circuits Syst. Video Technol. 11(6), 688–695 (2001)

    Google Scholar 

  66. Manjunath, B.S., Ohm, J.R., Vasudevan, V.V., Yamada, A.: Color and texture descriptors. IEEE Trans. Circuits Syst. Video Technol. 11(6), 703–715 (2001)

    Article  Google Scholar 

  67. Bober, M.: MPEG-7 visual shape descriptors. IEEE Trans. Circuits Syst. Video Technol. 11(6), 716–719 (2001)

    Article  Google Scholar 

  68. Paepcke, A., Chang, C.-C.K., Winograd, T., Garcia-Molina, H.: Interoperability for digital libraries worldwide. Communications of the ACM 41(4), 33–42 (1998)

    Article  Google Scholar 

  69. Goncalves, M.A., France, R.K., Fox, E.A.: MARIAN: Flexible Interoperability for Federated Digital Libraries. In: Proceedings of the 5th European Conference on Research and Advanced Technology for Digital Libraries, pp. 173–186, Germany (2001)

  70. ETANA: Managing Complex Information Applications: An Archaeology Digital Library (2004) http://feathers.dlib.vt.edu (as of October 2004)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ricardo da S. Torres.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Torres, R.d.S., Medeiros, C.B., Gonçcalves, M.A. et al. A digital library framework for biodiversity information systems. Int J Digit Libr 6, 3–17 (2006). https://doi.org/10.1007/s00799-005-0124-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00799-005-0124-1

Keywords

Navigation