Insight: An ontology-based integrated database and analysis platform for epilepsy self-management research

We present Insight as an integrated database and analysis platform for epilepsy self-management research as part of the national Managing Epilepsy Well Network. Insight is the only available informatics platform for accessing and analyzing integrated data from multiple epilepsy self-management research studies with several new data management features and user-friendly functionalities. The features of Insight include, (1) use of Common Data Elements defined by members of the research community and an epilepsy domain ontology for data integration and querying, (2) visualization tools to support real time exploration of data distribution across research studies, and (3) an interactive visual query interface for provenance-enabled research cohort identification. The Insight platform contains data from five completed epilepsy self-management research studies covering various categories of data, including depression, quality of life, seizure frequency, and socioeconomic information. The data represents over 400 participants with 7552 data points. The Insight data exploration and cohort identification query interface has been developed using Ruby on Rails Web technology and open source Web Ontology Language Application Programming Interface to support ontology-based reasoning. We have developed an efficient ontology management module that automatically updates the ontology mappings each time a new version of the Epilepsy and Seizure Ontology is released. The Insight platform features a Role-based Access Control module to authenticate and effectively manage user access to different research studies. User access to Insight is managed by the Managing Epilepsy Well Network database steering committee consisting of representatives of all current collaborating centers of the Managing Epilepsy Well Network. New research studies are being continuously added to the Insight database and the size as well as the unique coverage of the dataset allows investigators to conduct aggregate data analysis that will inform the next generation of epilepsy self-management studies.

[1]  Olivier Bodenreider,et al.  Bio-ontologies: current trends and future directions , 2006, Briefings Bioinform..

[2]  Alon Y. Halevy,et al.  Principles of Data Integration , 2012 .

[3]  Sean Bechhofer,et al.  The OWL API: A Java API for OWL ontologies , 2011, Semantic Web.

[4]  U. Bauer,et al.  [Centers for Disease Control and Prevention (CDC)]. , 2000, Annales de dermatologie et de venereologie.

[5]  Meng Zhao,et al.  Epilepsy and seizure ontology: towards an epilepsy informatics infrastructure for clinical research and patient care , 2014, J. Am. Medical Informatics Assoc..

[6]  C. Diiorio,et al.  Epilepsy self-management: partial replication and extension. , 1994, Research in nursing & health.

[7]  Donald L. Schomer,et al.  Project EASE: a study to test a psychosocial model of epilepsy medication management , 2004, Epilepsy & Behavior.

[8]  W Allen Hauser,et al.  Do seizures beget seizures? , 2002, Progress in brain research.

[9]  Bridianne O'Dea,et al.  A cross-sectional exploration of the clinical characteristics of disengaged (NEET) young people in primary mental healthcare , 2014, BMJ Open.

[10]  Isaac S. Kohane,et al.  Integration of Clinical and Genetic Data in the i2b2 Architecture , 2006, AMIA.

[11]  Guo-Qiang Zhang,et al.  Managing information well: Toward an ontology-driven informatics platform for data sharing and secondary use in epilepsy self-management research centers , 2016, Health Informatics J..

[12]  Shekhar Saxena,et al.  Epilepsy Care in the World: Results of an ILAE/IBE/WHO Global Campaign Against Epilepsy Survey , 2006, Epilepsia.

[13]  Sanjay Ghemawat,et al.  MapReduce: a flexible data processing tool , 2010, CACM.

[14]  Eduardo Mena Nieto.  Observer: an approach for query processing in global information systems based on interoperation across pre-existing ontologies , 1999 .

[15]  Barbara C. Jobst,et al.  A Pilot Study of a Self-Management Intervention for Cognitive Impairment in Epilepsy (S43.001) , 2014 .

[16]  Steven C Schachter,et al.  Epilepsy surveillance among adults--19 States, Behavioral Risk Factor Surveillance System, 2005. , 2008, Morbidity and mortality weekly report. Surveillance summaries.

[17]  N. Barbaro,et al.  Common data elements in epilepsy research: Development and implementation of the NINDS epilepsy CDE project , 2011, Epilepsia.

[18]  K. Cole,et al.  Implementation of an Epilepsy Self-Management Protocol , 2015, The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses.

[19]  C. Diiorio,et al.  Epilepsy self-management: a test of a theoretical model. , 1996, Nursing research.

[20]  Krystyna Milian,et al.  Towards Automatic Patient Eligibility Assessment: From Free-Text Criteria to Queries , 2013, AIME.

[21]  Sara Bresee.  Effective Strategies for Disseminating Information to Providers Working with HIV Patients: The Prevention Is Care Campaign Developed By the Centers for Disease Control and Prevention (CDC) , 2015 .

[22]  Mor Peleg,et al.  The Ontology of Clinical Research (OCRe): An informatics foundation for the science of clinical research , 2014, J. Biomed. Informatics.

[23]  Peter F. Patel-Schneider,et al.  OWL 2 Web Ontology Language Primer (Second Edition) , 2012 .

[24]  Xiaoying Wu,et al.  EliXR: an approach to eligibility criteria extraction and representation , 2011, J. Am. Medical Informatics Assoc..

[25]  Donald Schomer,et al.  Psychosocial predictors of lifestyle management in adults with epilepsy , 2008, Epilepsy & Behavior.

[26]  Kevin D Frick,et al.  Economic impact of epilepsy in the United States , 2009, Epilepsia.

[27]  R. Faught,et al.  Impact of nonadherence to antiepileptic drugs on health care utilization and costs: Findings from the RANSOM study , 2009, Epilepsia.

[28]  P. Camfield,et al.  Does gender influence susceptibility and consequences of acquired epilepsies? , 2014, Neurobiology of Disease.

[29]  Sally Kendall,et al.  The information needs of carers of adults diagnosed with epilepsy , 2004, Seizure.

[30]  Damian Smedley,et al.  The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data , 2014, Nucleic Acids Res..

[31]  Jeff Sutherland,et al.  Manifesto for Agile Software Development , 2013 .

[32]  Amit P. Sheth,et al.  A unified framework for managing provenance information in translational research , 2011, BMC Bioinformatics.

[33]  D. Hesdorffer,et al.  Surveillance of epilepsy and prevention of epilepsy and its sequelae: lessons from the Institute of Medicine report. , 2013, Current opinion in neurology.

[34]  Ross Shegog,et al.  The Prevention Research Centers’ Managing Epilepsy Well Network , 2010, Epilepsy & Behavior.

[35]  Barbara C. Jobst,et al.  A cognitive behavioral intervention (HOBSCOTCH) improves quality of life and attention in epilepsy , 2016, Epilepsy & Behavior.

[36]  Frances McCarty,et al.  WebEase: Development of a Web-Based Epilepsy Self-Management Intervention , 2008, Preventing chronic disease.

[37]  C. Dilorio,et al.  Self‐Management in Persons with Epilepsy , 1995, The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses.

[38]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[39]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[40]  Amit P. Sheth,et al.  An ontology-driven semantic mashup of gene and biological pathway information: Application to the domain of nicotine dependence , 2008, J. Biomed. Informatics.

[41]  Brian Litt,et al.  A multimodal platform for cloud-based collaborative research , 2013, 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER).