Open Access Highly Accessed Open Badges Preliminary communication

Linked open drug data for pharmaceutical research and development

Matthias Samwald123*, Anja Jentzsch4, Christopher Bouton5, Claus Stie Kallesøe6, Egon Willighagen7, Janos Hajagos8, M Scott Marshall109, Eric Prud'hommeaux11, Oktie Hassanzadeh12, Elgar Pichler13 and Susie Stephens14

Author Affiliations

1 Section for Medical Expert and Knowledge-Based Systems, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria

2 Information Retrieval Facility (IRF), Vienna, Austria

3 Digital Enterprise Research Institute (DERI), National University of Ireland Galway, IDA Business Park, Lower Dangan, Galway, Ireland

4 Web-based Systems Group, Freie Universität Berlin, Berlin, Germany

5 Entagen, LLC, Second Floor, 44 Merrimac Street, Newburyport, MA 01950, USA

6 H. Lundbeck A/S, Copenhagen, Denmark

7 Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

8 Department of Medical Informatics, Stony Brook University School of Medicine, Stony Brook, New York, USA

9 University of Amsterdam, Amsterdam, The Netherlands

10 Leiden University Medical Center, Leiden, The Netherlands

11 W3C, Cambridge, MA, USA

12 Department of Computer Science, University of Toronto, Toronto, Ontario, Canada

13 W3C HCLSIG. W3C, Cambridge, MA, USA

14 Johnson & Johnson Pharmaceutical Research & Development, L.L.C., Radnor, USA

For all author emails, please log on.

Journal of Cheminformatics 2011, 3:19  doi:10.1186/1758-2946-3-19

Published: 16 May 2011


There is an abundance of information about drugs available on the Web. Data sources range from medicinal chemistry results, over the impact of drugs on gene expression, to the outcomes of drugs in clinical trials. These data are typically not connected together, which reduces the ease with which insights can be gained. Linking Open Drug Data (LODD) is a task force within the World Wide Web Consortium's (W3C) Health Care and Life Sciences Interest Group (HCLS IG). LODD has surveyed publicly available data about drugs, created Linked Data representations of the data sets, and identified interesting scientific and business questions that can be answered once the data sets are connected. The task force provides recommendations for the best practices of exposing data in a Linked Data representation. In this paper, we present past and ongoing work of LODD and discuss the growing importance of Linked Data as a foundation for pharmaceutical R&D data sharing.

Graphical abstract