The Life Sciences Semantic Web is Full of Creeps!

Good, Benjamin M.; Wilkinson, Mark D.
September 2006
Briefings in Bioinformatics;Sep2006, Vol. 7 Issue 3, p275
Academic Journal
The Semantic Web for the Life Sciences (SWLS), when realized, will dramatically improve our ability to conduct bioinformatics analyses using the vast and growing stores of web-accessible resources. This ability will be achieved through the widespread acceptance and application of standards for naming, representing, describing and accessing biological information. The W3C-led Semantic Web initiative has established most, if not all, of the standards and technologies needed to achieve a unified, global SWLS. Unfortunately, the bioinformatics community has, thus far, appeared reluctant to fully adopt them. Rather, we are seeing what could be described as ‘semantic creep’—timid, piecemeal and ad hoc adoption of parts of standards by groups that should be stridently taking a leadership role for the community. We suggest that, at this point, the primary hindrances to the creation of the SWLS may be social rather than technological in nature, and that, like the original Web, the establishment of the SWLS will depend primarily on the will and participation of its consumers.


Related Articles

  • GoWeb: a semantic search engine for the life science web. Dietze, Heiko; Schroeder, Michael // BMC Bioinformatics;2009 Supplement 10, Vol. 10, Special section p1 

    Background: Current search engines are keyword-based. Semantic technologies promise a next generation of semantic search engines, which will be able to answer questions. Current approaches either apply natural language processing to unstructured text or they assume the existence of structured...

  • ONTO-ToolKit: enabling bio-ontology engineering via Galaxy. Antezana, Erick; Venkatesan, Aravind; Mungall, Chris; Mironov, Vladimir; Kuiper, Martin // BMC Bioinformatics;Jan2010 Supplement 12, Vol. 11, p1 

    Background: The biosciences increasingly face the challenge of integrating a wide variety of available data, information and knowledge in order to gain an understanding of biological systems. Data integration is supported by a diverse series of tools, but the lack of a consistent terminology to...

  • Distributing the Workload. Augen, Jeff // Bio-IT World;Sep2004, Vol. 3 Issue 9, pS-22 

    Discusses bioinformatics problems in a clustered environment. Categories of the problems; Approaches for performing sequence searches in the environment; Solution for computing infrastructure design.

  • Trends in life science grid: from computing grid to knowledge grid. Konagaya, Akihiko // BMC Bioinformatics;2006 Supplement 5, Vol. 7, pS10 

    Background: Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution. Results: This survey reviews the latest grid technologies...

  • Computation Tools Bust Down the Domain Doors. Kahn, Scott // Bio-IT World;Sep2004, Vol. 3 Issue 9, pS-18 

    Focuses on the changes in life science information technology as of September 2004. Consideration of trends toward biological computation; Wider access to experimental methods; Integration of the methods.

  • BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains. Toshiaki Katayama; Wilkinson, Mark D.; Kiyoko F. Aoki-Kinoshita; Shuichi Kawashima; Yasunori Yamamoto; Atsuko Yamaguchi; Shinobu Okamoto; Shin Kawano; Jin-Dong Kim; Yue Wang; Hongyan Wu; Yoshinobu Kano; Hiromasa Ono; Hidemasa Bono; Kocbek, Simon; Aerts, Jan; Yukie Akune; Antezana, Erick; Kazuharu Arakawa; Aranda, Bruno // Journal of Biomedical Semantics;2014, Vol. 5 Issue 1, p1 

    The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the...

  • OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows. Aranguren, Mikel Egaña; Fernández-Breis, Jesualdo Tomás; Mungall, Chris; Antezana, Erick; González2, Alejandro Rodríguez; Wilkinson, Mark D. // Journal of Biomedical Semantics;2013, Vol. 4 Issue 1, p1 

    Background: Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor...

  • RDFScape: Semantic Web meets Systems Biology. Splendiani, Andrea // BMC Bioinformatics;2008 Supplement 4, Vol. 9, Special section p1 

    Background: The recent availability of high-throughput data in molecular biology has increased the need for a formal representation of this knowledge domain. New ontologies are being developed to formalize knowledge, e.g. about the functions of proteins. As the Semantic Web is being introduced...

  • Incorporating functional inter-relationships into protein function prediction algorithms. Pandey, Gaurav; Myers, Chad L.; Kumar, Vipin // BMC Bioinformatics;2009, Vol. 10, Special section p1 

    Background: Functional classification schemes (e.g. the Gene Ontology) that serve as the basis for annotation efforts in several organisms are often the source of gold standard information for computational efforts at supervised protein function prediction. While successful function prediction...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics