Semantic mashup of biomedical data

Cheung, Kei-Hoi; Kashyapb, Vipul; Lucianoc, Joanne S.; Chend, Huajun; Wange, Yimin; Stephensf, Susie
Cheung, K
Kashyapb, V
Lucianoc, J
Chend, H
Wange, Y
Stephensf, S
Journal of Biomedical Informatics
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Journal of Biomedical Informatics 41 (2008) 683­686

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Journal of Biomedical Informatics
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Guest Editorial

Semantic mashup of biomedical data

1. Introduction As the diversity and quantity of Web-accessible data in the biomedical domain grow, there are increasing benefits in empowering end-user scientists, working on their own, to integrate the various sources of data. Traditionally, significant programming effort has been required to parse and integrate heterogeneous datasets prior to enabling scientists to answer interesting questions. The heterogeneity includes different data formats, information models, and terminologies. Recently, a new breed of Web-based data-integration tools has been developed to simplify this process. They are called ``mashups." These mashup tools have been designed to empower end-users to be able to extract, format, and remix data across multiple Web sites. Examples of such tools include Dapper (, which allows users to extract/scrape data from Web pages visually and to produce the extracted data as feeds in formats such as Rich Site Summary (RSS) (http://web.; Google Maps (, which provides the ability to mashup (integrate) datasets in the Keyhole Markup Language (KML) format and to visualize the integrated results; and Yahoo! Pipes (, which provides operators/widgets to mashup heterogeneously formatted datasets (e.g., tabular, RSS, and KML formats). In addition to accessing user-friendly mashup tools, Web programmers can directly use open Web APIs, such as those listed in ProgrammableWeb (

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