Proceedings of the Joint Workshop on Semantic Technologies Applied to Biomedical Informatics and Individualized Medicine (SATBI+SWIM 2012) Held at the 11th International Semantic Web Conference (ISWC 2012) November 12th, Boston, USA Preface Two major challenges to the use of digitally encoded biomedical data for improving health are its distributed nature and lack of harmonization [1]. Semantic technologies, including ontologies, terminologies, Uniform Resource Identifiers (URIs), and the Resource Description Framework (RDF), are key to addressing these challenges. By enabling the precise identification of entities and the computable encoding of formal class definitions, semantic technologies enable large-scale semantic normalization of distributed biomedical data sets. The Joint Workshop on Semantic Technologies Applied to Biomedical Informatics and Individualized Medicine, co-located with the 11th International Semantic Web Conference, brought together researchers, developers, and practitioners who are actively applying semantic technologies and biomedical data to improving health. Five peer- reviewed papers describing original research in this area were presented at the workshop.  Corrigan, Soler, and Delaney present incremental progress of the "Translational Medicine and Patient Safety in Europe" project, funded by the EU FP7. The focus of the work is a proof of concept infrastructure to support the creation of actionable knowledge within the electronic health record for clinical decision support. The infrastructure is based on evidence from new research findings coupled with contemporary clinical knowledge and practice. The focus of this work is the use of methods from ontology development and statistics to create a consistent model of the evidence-of-association between the clinical and diagnostics cues.  McCusker et al. present a novel and intriguing architecture called the “Global Health Explorer” for processing Twitter "tweets" to identify the occurrence of terms from biomedical ontologies for the purpose of visual analysis and data exploration. Novel features of the architecture include an approach the authors term “Ontology-as-API”, and the integration of a high dimensional data visualization tool called the Data Cube Explorer. This paper highlights how ontologies and terminologies perform a critical role in enabling biomedical Natural Language Processing (NLP) algorithms to richly annotate biomedical and entities and relationships. The approach may compliment other public health data sets such as World Health Organizations' Global Health Observatory (GHO) dataset and the ReDD-Observatory.  De Waard and Scheider propose the use of an ontology model called ORCA to enable better representation of biomedical argumentations. ORCA is a lightweight ontology to represent observational and interpretational assertions in scientific documents. The paper presents a brief description of the ontology, the motivation behind it, related work, and a few biomedical applications. This paper is highly relevant since the reliability and attribution of biomedical results, data, and information is a critical issue in research. Moreover, the research highlights an important use of ontologies to model scientific discourse and evidence with the vision of creating computable chains of claims and evidence that explicitly model the consensus, disagreement, and questions necessary for advancing science in a given field.  Baranya et al. present an approach for improving medical visualization of semantically annotated CT-Images. The approach combines multiple biomedical ontologies and image characteristics to define what is referred to as a Transfer Function (TF). Essentially a TF maps volumetric data into optional properties, and in general, is not easy to define. The proposed framework--ANISE--is a rule-based system that comprises multiple annotators and rules engine to for defining the TFs based on semantic annotations using ontologies such as FMA and RadLex.  Chniti et al. describe a novel framework for writing business rules using a structured language that should be usable by domain experts while ensuring that the rules involve entities from a formal ontology can be executed over an object- oriented decisions support system. Rules authored in natural language are translated to IRL executable rules. From there, there are BOMs, XOMs, Java objects and WODMs. Many thanks to all our contributors and participants at SATBI+SWIM 2012 and also the Programme Committee whose feedback has resulted in a fruitful collection of papers, providing added value to current leading edge research. Also, a special gratitude to Dr. Joanne S. Luciano and Dr. Eric Neumann for accepting our invitation and participate as keynote speakers of SATBI+SWIM 2012. November 2012 Alejandro Rodríguez-González Jyotishman Pathak Mark D. Wilkinson Nigam H. Shah Robert Stevens Richard Boyce Ángel García-Crespo References 1. IOM (Institute of Medicine). 2012. Digital data priorities for continuous learning in health and health care: Workshop Summary. Washington, DC: The National Academies Press. Organization Organizing Committee Alejandro Rodríguez González, PhD CBGP-UPM, Spain Jyotishman Pathak, PhD Mayo Clinic, USA Mark Wilkinson, PhD CBGP-UPM, Spain Nigam H. Shah, MBBS, PhD Stanford University, USA Robert Stevens, PhD University of Manchester, UK Richard Boyce, PhD University of Pittsburgh, USA Angel García Crespo, PhD University Carlos III of Madrid, Spain Program Committee Helena Deus, PhD Digital Research Enterprise Institute, Ireland Jesualdo Tomas Fernandez Breis, PhD University of Murcia, Spain Michel Dumontier, PhD Carleton University, Canada Mikel Egaña Aranguren, PhD CBGP-UPM, Spain Joanne Luciano, PhD Harvard University, USA Alan Ruttenberg University of Buffalo, USA Oktie Hassanzadeh IBM Research, USA M. Scott Marshall, PhD MAASTRO Clinic, Maastricht William Hogan University of Arkansas, USA Table of Contents Public Health Surveillance Using Global Health Explorer . . . . . . . . . . . . . . . . . . . . . . . . 1 James P. McCusker, Jeongmin Lee, Chavon Thomas and Deborah L. McGuinness Formalising Uncertainty: An Ontology of Reasoning, Certainty and Attribution (ORCA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Anita de Waard and Jodi Schneider A Workflow for Improving Medical Visualization of Semantically Annotated CT-Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Alexander Baranya, Luis Landaeta, Alexandra La Cruz and Maria-Esther Vidal Development of an Ontological Model of Evidence for TRANSFoRm Utilizing Transition Project Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Derek Corrigan, Jean-Karl Soler and Brendan Delaney Pharmaceutical Validation of Medication Orders Using an OWL Ontology and Business Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Amina Chniti, Abdelali BOUSSADI, Patrice DEGOULET, Patrick Albert and Jean Charlet Keynote: How clinical and genomic data integration can support pharmacogenomics efforts related to personalized medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Eric Neumann Keynote: Understanding Recovery as a Mechanism for Individualized Treatment Selection in Major Depressive Disorder: A case study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Joanne S. Luciano