Constructing a New-Style Conceptual Model of Brain Data for Systematic Brain Informatics

The development of brain science has led to a vast increase of brain data. To meet requirements of a systematic methodology of Brain Informatics (BI), this paper proposes a new conceptual model of brain data, namely Data-Brain, which explicitly represents various relationships among multiple human brain data sources, with respect to all major aspects and capabilities of human information processing systems (HIPS). A multidimension framework and a BI methodology-based ontological modeling approach have been developed to implement a Data-Brain. The Data-Brain, Data-Brain-based BI provenances, and heterogeneous brain data can be used to construct a Data-Brain-based brain data center which provides a global framework to integrate data, information, and knowledge coming from the whole research process for systematic BI study. Such a Data-Brain modeling approach represents a radically new way for domain-driven conceptual modeling of brain data, which models a whole process of systematically investigating human information processing mechanisms.

[1]  Gilles Kassel,et al.  Towards an ontology for sharing medical images and regions of interest in neuroimaging , 2008, J. Biomed. Informatics.

[2]  Steffen Staab,et al.  Discovering Conceptual Relations from Text , 2000, ECAI.

[3]  Asunción Gómez-Pérez,et al.  METHONTOLOGY: From Ontological Art Towards Ontological Engineering , 1997, AAAI 1997.

[4]  Ning Zhong,et al.  Multi-aspect data analysis for investigating human computation mechanism , 2010, Cognitive Systems Research.

[5]  E. Prud hommeaux,et al.  SPARQL query language for RDF , 2011 .

[6]  Shashi Shekhar,et al.  Data models in geographic information systems , 1997, CACM.

[7]  Robert Meersman,et al.  On Using Conceptual Data Modeling for Ontology Engineering , 2004, J. Data Semant..

[8]  Yisheng Dong,et al.  Formal Approach and Automated Tool for Translating ER Schemata into OWL Ontologies , 2004, PAKDD.

[9]  Jianhui Chen,et al.  Data-Brain Modeling for Systematic Brain Informatics , 2009, Brain Informatics.

[10]  Martin L. King,et al.  Towards a Methodology for Building Ontologies , 1995 .

[11]  Marko Grobelnik,et al.  A SURVEY OF ONTOLOGY EVALUATION TECHNIQUES , 2005 .

[12]  Mark A. Musen,et al.  Specifying Ontology Views by Traversal , 2004, International Semantic Web Conference.

[13]  Pedro M. Domingos,et al.  Learning to Match the Schemas of Data Sources: A Multistrategy Approach , 2003, Machine Learning.

[14]  Hongfei Lin,et al.  BioPPIExtractor: A protein-protein interaction extraction system for biomedical literature , 2009, Expert Syst. Appl..

[15]  Jörg Holetschek,et al.  A database for therapy evaluation in neurological disorders: application in epilepsy , 2004, IEEE Transactions on Information Technology in Biomedicine.

[16]  Allen D. Malony,et al.  Development of NeuroElectroMagnetic ontologies(NEMO): a framework for mining brainwave ontologies , 2007, KDD '07.

[17]  Yiyu Yao,et al.  Web Intelligence (WI) , 2000, Proceedings 24th Annual International Computer Software and Applications Conference. COMPSAC2000.

[18]  Ramez Elmasri,et al.  Extending EER Modeling Concepts for Biological Data , 2006, 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06).

[19]  J B Woodward,et al.  The Functional Magnetic Resonance Imaging Data Center (fMRIDC): the challenges and rewards of large-scale databasing of neuroimaging studies. , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[20]  Michael Krauthammer,et al.  Term identification in the biomedical literature , 2004, J. Biomed. Informatics.

[21]  Ning Zhong,et al.  Impending Brain Informatics Research from Web Intelligence Perspective , 2006, Int. J. Inf. Technol. Decis. Mak..

[22]  Yiyu Yao,et al.  Web Intelligence (WI): A New Paradigm for Developing the Wisdom Web and Social Network Intelligence , 2003 .

[23]  Yiyu Yao,et al.  Web Intelligence Meets Brain Informatics , 2006, WImBI.

[24]  Jianhui Chen,et al.  Data-Brain Modeling Based on Brain Informatics Methodology , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[25]  Jianhua Ma,et al.  Research challenges and perspectives on Wisdom Web of Things (W2T) , 2010, The Journal of Supercomputing.

[26]  Maurizio Vincini,et al.  Synthesizing an Integrated Ontology , 2003, IEEE Internet Comput..

[27]  Aldo Gangemi,et al.  Ontology Learning and Its Application to Automated Terminology Translation , 2003, IEEE Intell. Syst..

[28]  Michael Uschold,et al.  Ontologies: principles, methods and applications , 1996, The Knowledge Engineering Review.

[29]  Steffen Staab,et al.  Ontology Learning for the Semantic Web , 2002, IEEE Intell. Syst..

[30]  Irina Astrova,et al.  Reverse Engineering of Relational Databases to Ontologies , 2004, ESWS.

[31]  Frederico T. Fonseca,et al.  Learning The Differences Between Ontologies and Conceptual Schemas Through Ontology-Driven Information Systems , 2007, J. Assoc. Inf. Syst..

[32]  Yiyu Yao,et al.  The Neural Mechanism of Human Numerical Inductive Reasoning Process: A Combined ERP and fMRI Study , 2006, WImBI.

[33]  Ning Zhong,et al.  In Search of the Wisdom Web , 2002, Computer.

[34]  Irina Astrova,et al.  Reverse Engineering of Relational Databases to Ontologies: An Approach Based on an Analysis of HTML Forms , 2004 .

[35]  Ning Zhong,et al.  Agent-Enriched Data Mining: A Case Study in Brain Informatics , 2009, IEEE Intelligent Systems.

[36]  Takahira Yamaguchi,et al.  DODDLE II: A Domain Ontology Development Environment Using a MRD and Text Corpus , 2004, IEICE Trans. Inf. Syst..

[37]  Arthur W. Toga,et al.  Provenance in neuroimaging , 2008, NeuroImage.

[38]  Paola Velardi,et al.  Integrated approach to Web ontology learning and engineering , 2002, Computer.

[39]  Ning Zhong,et al.  In search of the wisdom web , 2002, Computer.

[40]  Angela R Laird,et al.  Brainmap taxonomy of experimental design: Description and evaluation , 2005, Human brain mapping.

[41]  Yannis Kalfoglou,et al.  Ontology mapping: the state of the art , 2003, The Knowledge Engineering Review.

[42]  Jeremy J. Carroll,et al.  Resource description framework (rdf) concepts and abstract syntax , 2003 .

[43]  Ning Zhong,et al.  BUILDING A DATA‐MINING GRID FOR MULTIPLE HUMAN BRAIN DATA ANALYSIS , 2005, Comput. Intell..

[44]  Shushma Patel,et al.  A layered reference model of the brain (LRMB) , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[45]  Yogesh L. Simmhan,et al.  A survey of data provenance in e-science , 2005, SGMD.

[46]  Fabio Massimo Zanzotto,et al.  Inductive probabilistic taxonomy learning using singular value decomposition , 2011, Natural Language Engineering.

[47]  Bernard Gibaud,et al.  Web Ontology Language Requirements w.r.t Expressiveness of Taxonomy and Axioms in Medicine , 2003, SEMWEB.

[48]  Jianhui Chen,et al.  Data-Brain driven systematic human brain data analysis: A case study in numerical inductive reasoning centric investigation , 2012, Cognitive Systems Research.

[49]  H. Sofia Pinto,et al.  Some Issues on Ontology Integration , 1999, IJCAI 1999.

[50]  Hyoil Han,et al.  A survey on ontology mapping , 2006, SGMD.

[51]  Mehrnoush Shamsfard,et al.  Learning ontologies from natural language texts , 2004, Int. J. Hum. Comput. Stud..

[52]  Anna Formica,et al.  Ontology-based concept similarity in Formal Concept Analysis , 2006, Inf. Sci..

[53]  Peter P. Chen The Entity-Relationship Model: Towards a unified view of Data , 1976 .

[54]  Douglas H. Fisher,et al.  Knowledge Acquisition Via Incremental Conceptual Clustering , 1987, Machine Learning.

[55]  Mark A. Musen,et al.  PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment , 2000, AAAI/IAAI.

[56]  Ning Zhong,et al.  Building a Brain-Informatics Portal on the Wisdom Web with a Multi-layer Grid: A New Challenge for Web Intelligence Research , 2005, MDAI.

[57]  Ning Zhong,et al.  How to Make "Web Intelligence (WI) meets Brain Informatics (BI)" Successfully? , 2006, COMPSAC.