A methodology for semantic integration of metadata in bioinformatics data sources
Authors: 
Lei Li, Roop G. Singh, Guangzhi Zheng, Art Vandenberg, Vijay Vaishnavi, 
Sham NavatheAuthors Info & Claims
Lei Li, Roop G. Singh, Guangzhi Zheng, Art Vandenberg, Vijay Vaishnavi, Sham NavatheAuthors Info & ClaimsPages 131 - 136
Abstract
Semantic heterogeneity is becoming increasingly prominent in bioinformatics domains that deal with constantly expanding, dynamic, often very large, datasets from various distributed sources. Metadata is the key component for effective information integration. Traditional approaches for reconciling semantic heterogeneity use standards or mediation-based methods. These approaches have had limited success in addressing the general semantic heterogeneity problem and by themselves are not likely to succeed in bioinformatics domains where one faces the additional complexity of keeping pace with the speed at which data and semantic heterogeneity is being generated. This paper presents a methodology for reconciliation of semantic heterogeneity of metadata in bioinformatics data sources. The approach is based on the proposition that by globally monitoring, clustering, and visualizing bioinformatics metadata across disparately created data sources, patterns of practice can be identified. This can facilitate semantic reconciliation of metadata in current data and mitigate semantic heterogeneity in future data by promoting sharing and reuse of existing metadata. To instantiate the methodology, a research architecture, MicroSEEDS, is presented and its implementation and envisioned uses are discussed.
References
[1]
Batini, C., Lenzerini, M. and Navathe, S. B. A Comparative Analysis of Methodologies for Database Schema Integration. ACM Computing Surveys, 18, 4, December 1986, pp. 323--364.
[2]
Brooks, F. P. No Silver Bullet: Essence and Accidents of Software Engineering. Computer, 20 (4), pp. 10--19, 1987.
[3]
Chen, L., Jamil, H. M., and Wang, N. Automatic Composite Wrapper Generation for Semi-Structured Biological Data Based on Table Structure Identification. SIGMOD Record 33(2): 58--64, 2004.
[4]
Damsgaard, J. and Truex, D. Binary Trading Relations and the Limits of EDI Standards: The Procrustean Bed of Standards. European Journal of Information Systems, 9 (3), pp. 173--188, 2000.
[5]
Foster, I. and Grossman, R. L. Data Integration in a Bandwidth-rich World. Communications of the ACM, vol. 6, no. 11, November 2003. pp50--57.
[6]
Hernandez, T. and Kambhampati, S. Integration of Biological Sources: Current Systems and Challenges Ahead. SIGMOD Record 33(3): 51--60 (2004)
[7]
Jagadish, H. V. and Olken, F. Database Management for Life Science Research: Summary Report of the Workshop on Data Management for Molecular and Cell Biology at the National Library of Medicine, Bethesda, Maryland, February 2-3, 2003. OMICS A Journal of Integrative Biology, 7 (1), 2003.
[8]
Jain, A. K., Murty, M. N., and Flynn, P. J. Data Clustering: A Review. ACM Computing Surveys, 31, 3, pp. 264--323, 1999.
[9]
Kohonen, T. Self-Organizing Maps, Springer-Verlag, Berlin, 1995.
[10]
Kuechler, D., Vaishnavi, V., and. Vandenberg, A. An Architecture to Support Communities of Interest Using Directory Services Capabilities. Proceedings Hawaii International Conference on System Sciences, Big Island, Hawaii, 2003.
[11]
Li, L., Vaishnavi, V., and Vandenberg, A. An Architecture for Semantic Facilitation and Reuse of Directory Metadata. Proc. 2004 International Conference on Information and Knowledge Engineering, Las Vegas, Nevada, 2004.
[12]
Liang, J., Vaishnavi, V., and Vandenberg, A. Clustering of LDAP Directory Schemas to Facilitate Information Resources Interoperability Across Organizations. IEEE Transactions on Systems, Man, and Cybernetics, Part A (to appear).
[13]
Liu, Y., Ciliax, B. J., Borges, K., Dasigi, V., Ram, A., Navathe, S., and Dingledine, R. Comparison of Two Schemes for Automatic Keyword Extraction from MEDLINE for Functional Gene Clustering. IEEE Conf. on Computational Systems Bioinformatics (CSB'2004), August 2004.
[14]
MGED: Microarray Gene Expression Data Society (MGED), home page, 2004. <http://www.mged.org> (Last accessed November 14, 2004).
[15]
Navathe, S. and Patil, U. Genomic and Proteomic Databases and Applications: "A challenge for Database Technology," Proc. 9th International Conference on Database Systems for Advanced Applications (DASFAA 2004), Jeju Island, Korea, March 2004, - Invited Paper.
[16]
Newman, H. B., Ellisman, M. H., and Orcutt J. A. Data-Intensive E-Science Frontier. Communications of the ACM, 46 (11), pp. 68--77, November 2003.
[17]
Panayiota, P. and Nicholas, D. Familiarity with and Use of Metadata Formats and Metadata Registries amongst Those Working in Diverse Professional Communities within the Information Sector. Aslib Proceedings, 53, 8, pp. 309--324, 2001
[18]
Roszkiewicz, R. Metadata in Context. The Seybold Report, vol. 4, no. 8, 2004.
[19]
Roussinov, D. Information Foraging Through Clustering and Summarization: A Self-Organizing Approach. A Dissertation Submitted to the Faculty of the Committee on Business Administration, the University of Arizona, 1999.
[20]
Shaw, C. D., Hall, J. A., Ebertc D. S., and Roberts, D. A., "Interactive Lens Visualization Techniques," in IEEE Visualization'99, pp. 155--160, October 1999.
[21]
Sheth, A., Gala, S. K., Navathe, S. B. On Automatic Reasoning for Schema Integration. Int. Journal of Intelligent Co-operative Information Systems, 2 (1), March 1993.
[22]
Stekel, D., Microarray Bioinformatics, Cambridge University Press, 2003.
[23]
Stoimenov, L., Djordjevic, K., Stojanovic, D. Integration of GIS Data Sources over the Internet Using Mediator and Wrapper Technology. Proceedings of the 2000 10th Mediterranean Electrotechnical Conference. Information Technology and Electrotechnology for the Mediterranean Countries (MeleCon 2000), pp. 334--336, 2000.
[24]
Vaishnavi, V. and Kuechler, W. Universal Enterprise Integration: The Challenges of and Approaches to Web-Enabled Virtual Organizations. Information Technology & Management, 6 (1), 2005, to appear.
[25]
Vandenberg, A., Liang, J., Bolet, V., Kou, H., Vaishnavi, V., and Kuechler, D. Research Prototype: Semantic Facilitator #8482; SM for LDAP Directory Services. Proceedings of the 12th Annual Workshop on Information Technologies and Systems, 2002.
Index Terms
- A methodology for semantic integration of metadata in bioinformatics data sources
Recommendations
A semantic web approach to heterogeneous metadata integration
ICCCI'10: Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume PartIHeterogeneous metadata integration is an issue in digital libraries. Mapping is often used for an integrated metadata access, but the implicit knowledge and relations embedded in metadata are ignored. This paper aims to present a semantic web approach ...
Information systems interoperability: What lies beneath?
Interoperability is the most critical issue facing businesses that need to access information from multiple information systems. Our objective in this research is to develop a comprehensive framework and methodology to facilitate semantic ...
Syntactic and semantic metadata integration for science data use
This paper proposes a novel metadata solution to allow applications to intelligently use science data in an automated fashion. The solution provides rich syntactic and semantic metadata, where the semantic metadata is linked with an ontology to define ...
Comments
Information & Contributors
Information
Published In
Copyright © 2005 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 18 March 2005
Check for updates
Author Tags
Qualifiers
- Article
Conference
ACM SE05
Sponsor:
Acceptance Rates
Overall Acceptance Rate 502 of 1,023 submissions, 49%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 594Total Downloads
- Downloads (Last 12 months)1
- Downloads (Last 6 weeks)0
Reflects downloads up to 05 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in