1 Simple Rules for a Tool and Data Ontology Barry Smith.

Slides:

Advertisements

Similar presentations

Prof. Carolina Ruiz Computer Science Department Bioinformatics and Computational Biology Program WPI WELCOME TO BCB4003/CS4803 BCB503/CS583 BIOLOGICAL.

Advertisements

Systems Biology Existing and future genome sequencing projects and the follow-on structural and functional analysis of complete genomes will produce an.

Overview of Biomedical Informatics Rakesh Nagarajan.

Semantic Web and Web Mining: Networking with Industry and Academia İsmail Hakkı Toroslu IST EVENT 2006.

March 15-17, 2002Work with student Jong Oh Davi Geiger, Courant Institute, NYU On-Line Handwriting Recognition Transducer device (digitizer) Input: sequence.

Design of Web-based Systems IS Development: lecture 10.

1 An Ontology of Relations for Biomedical Informatics Barry Smith 10 January 2005.

The Role of Foundational Relations in the Alignment of Biomedical Ontologies Barry Smith and Cornelius Rosse.

1 Ontology in 15 Minutes Barry Smith. 2 Main obstacle to integrating genetic and EHR data No facility for dealing with time and instances (particulars)

6/17/20151 Table Structure Understanding by Sibling Page Comparison Cui Tao Data Extraction Group Department of Computer Science Brigham Young University.

1 CIS607, Fall 2006 Semantic Information Integration Instructor: Dejing Dou Week 10 (Nov. 29)

1 CIS607, Fall 2004 Semantic Information Integration Attendees: Vikash Agarwal, Julian M Catchen Kevin A Huck, Kushal M Koolwal, Paea J Le Pendu Xiangkui.

1 Ontologie als konkretisierte Darstellung der Wirklichkeit Barry Smith.

1 Information Retrieval and Extraction 資訊檢索與擷取 Chia-Hui Chang, Assistant Professor Dept. of Computer Science & Information Engineering National Central.

Institut für Softwarewissenschaft - Universität WienP.Brezany 1 Toward Knowledge Discovery in Databases Attached to Grids Peter Brezany Institute for Software.

Toward Making Online Biological Data Machine Understandable Cui Tao Data Extraction Research Group Department of Computer Science, Brigham Young University,

Copyright 2003 The McGraw-Hill Companies, Inc CHAPTER Application Software computing ESSENTIALS    

Biomedical Image Analysis and Machine Learning BMI 731 Winter 2005 Kun Huang Department of Biomedical Informatics Ohio State University.

DASHBOARDS Dashboard provides the managers with exactly the information they need in the correct format at the correct time. BI systems are the foundation.

MUSCLE WP9 E-Team Integration of structural and semantic models for multimedia metadata management Aims: (Semi-)automatic MM metadata specification process.

Web-based Portal for Discovery, Retrieval and Visualization of Earth Science Datasets in Grid Environment Zhenping (Jane) Liu.

341: Introduction to Bioinformatics Dr. Natasa Przulj Deaprtment of Computing Imperial College London

DOG I : an Annotation System for Images of Dog Breeds Antonis Dimas Pyrros Koletsis Euripides Petrakis Intelligent Systems Laboratory Technical University.

Bioinformatics Jan Taylor. A bit about me Biochemistry and Molecular Biology Computer Science, Computational Biology Multivariate statistics Machine learning.

Department of Biomedical Informatics Biomedical Data Visualization Kun Huang Department of Biomedical Informatics OSUCCC Biomedical Informatics Shared.

9/30/2004TCSS588A Isabelle Bichindaritz1 Introduction to Bioinformatics.

Data Mining. 2 Models Created by Data Mining Linear Equations Rules Clusters Graphs Tree Structures Recurrent Patterns.

Formal Empirical Applied Mathematical and technical methods and theories Cognitive, behavioral, and organizational techniques and theories ImagingBioInformaticsClinical.

ROOT: A Data Mining Tool from CERN Arun Tripathi and Ravi Kumar 2008 CAS Ratemaking Seminar on Ratemaking 17 March 2008 Cambridge, Massachusetts.

Last Words COSC Big Data (frameworks and environments to analyze big datasets) has become a hot topic; it is a mixture of data analysis, data mining,

Universität Stuttgart Universitätsbibliothek Information Retrieval on the Grid? Results and suggestions from Project GRACE Werner Stephan Stuttgart University.

JISCrte Meeting, May 25,2011 Dr. Yu Qian School of Engineering Information Sciences, Middlesex University

Multimedia Databases (MMDB)

Multimedia Information Retrieval and Multimedia Data Mining Chengcui Zhang Assistant Professor Dept. of Computer and Information Science University of.

Chapter 1 Introduction to Data Mining

Use of Machine Learning in Chemoinformatics Irene Kouskoumvekaki Associate Professor December 12th, 2012 Biological Sequence Analysis course.

EADGENE and SABRE Post-Analyses Workshop 12-14th November 2008, Lelystad, Netherlands 1 François Moreews SIGENAE, INRA, Rennes Cytoscape.

GeWorkbench Highlights caBIG ® Molecular Analysis Tools Knowledge Center AACR Annual Meeting, April 3, 2011.

INPUT#3 SOFTWARE ENGINEERING. QUALITY SOFTWARE?  Satisfies the needs of the users and programmers involved with it.

Introduction to Software Engineering. Why SE? Software crisis manifested itself in several ways [1]: ◦ Project running over-time. ◦ Project running over-budget.

Last Words DM 1. Mining Data Steams / Incremental Data Mining / Mining sensor data (e.g. modify a decision tree assuming that new examples arrive continuously,

NA-MIC National Alliance for Medical Image Computing National Alliance for Medical Image Computing: NAMIC Ron Kikinis, M.D.

Chapter 5: Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization DECISION SUPPORT SYSTEMS AND BUSINESS.

ACGT: Open Grid Services for Improving Medical Knowledge Discovery Stelios G. Sfakianakis, FORTH.

Using Domain Ontologies to Improve Information Retrieval in Scientific Publications Engineering Informatics Lab at Stanford.

1 Limitations of BLAST Can only search for a single query (e.g. find all genes similar to TTGGACAGGATCGA) What about more complex queries? “Find all genes.

Supported in part by the National Science Foundation under Grant No. HRD Any opinions, findings, and conclusions or recommendations expressed.

Nuria Lopez-Bigas Methods and tools in functional genomics (microarrays) BCO17.

GeWorkbench John Watkinson Columbia University. geWorkbench The bioinformatics platform of the National Center for the Multi-scale Analysis of Genomic.

NA-MIC National Alliance for Medical Image Computing Process-, Work-Flow in Medical Image Processing Guido Gerig

Graduate School of Informatics Kyoto University, November 21, 2001 Technologies of the Interspace Peer-Peer Semantic Indexing Bruce Schatz CANIS Laboratory.

Biomedical Informatics Research Network Pipelines & Processing: Tools & Toolkits David Rex, John Moreland October 9, nd Annual All Hands Meeting.

Image Classification for Automatic Annotation

Semantic web Bootstrapping & Annotation Hassan Sayyadi Semantic web research laboratory Computer department Sharif university of.

Knowledge Representation. Keywordsquick way for agents to locate potentially useful information Thesaurimore structured approach than keywords, arranging.

GeWorkbench Overview Support Team Molecular Analysis Tools Knowledge Center Columbia University and The Broad Institute of MIT and Harvard.

Satisfying Requirements BPF for DRA shall address: –DAQ Environment (Eclipse RCP): Gumtree ISEE workbench integration; –Design Composing and Configurability,

MBAT Infrastructure Controversial remarks…. What is an atlas?  a set of 2D images or a 3D volume in a specified coordinate system with a set of spatially.

Data Mining Concepts and Techniques Course Presentation by Ali A. Ali Department of Information Technology Institute of Graduate Studies and Research Alexandria.

High throughput biology data management and data intensive computing drivers George Michaels.

1 Survey of Biodata Analysis from a Data Mining Perspective Peter Bajcsy Jiawei Han Lei Liu Jiong Yang.

Advanced Scientific Visualization Guilford County SciVis V

Computer Graphics Lecture 2. Computer graphics application 1- Graphics and chart :- Early application for graphics display simple data graphic, but today.

MATLAB Distributed, and Other Toolboxes

Datamining : Refers to extracting or mining knowledge from large amounts of data Applications : Market Analysis Fraud Detection Customer Retention Production.

Ontology in 15 Minutes Barry Smith.

SDM workshop Strawman report History and Progress and Goal.

Knowledge Based Workflow Building Architecture

Data Warehousing and Data Mining

Ontology in 15 Minutes Barry Smith.

Presentation transcript:

1 Simple Rules for a Tool and Data Ontology Barry Smith

2 is_a (sensu MeSH) (?) MeSH Descriptors Index Medicus Descriptor Anthropology, Education, Sociology and Social Phenomena (MeSH Category) Social Sciences Political Systems National Socialism National Socialism is_a Political Systems National Socialism is_a Anthropology National Socialism is_a MeSH Descriptors

3 is_a (sensu OBO-RO) A is_a B =Def every instance of A is an instance of B instances are real-world examples, e.g. actual software tools, actual bodies of data,...

4 Three kinds of relations Mary’s heart part_of Mary Mary’s heart instance_of heart human heart part_of human

5 Data –Clinical InformationClinical Information Aggregate Human Data Individual Human Data Nonhuman Data –Experimental DataExperimental Data Gene-Phenotype Association DB Medical Images DB Molecular Interaction DB –OntologiesOntologies

6 Rules on terms Terms should be in the singular ontologies is_a data

7 Dissemination –Interactive Web-Based ToolsInteractive Web-Based Tools –PublicationPublication –Training CoursesTraining Courses –Web PostingsWeb Postings –publication is_a dissemination –interactive web-based tools is_a dissemination

8 Dissemination Terms should be count nouns interactive web-based tools is_a dissemination

9 Tools –Analysis and ModelingAnalysis and Modeling –Data ManagementData Management –Ontology Development and ManagementOntology Development and Management

10 Tools –Analysis and ModelingAnalysis and Modeling EDA Feature Analysis Genomic & Phenotypic Data Analysis Image Processing (2 instances)Image Processing(2 instances) Network characterization Pre-Processing Regulatory/Signaling network reconstruction Sequence Annotation Simulation Software Engineering and Development Tools Statistical Analysis Structure-based protein classification Toolkits (4 instances)Toolkits(4 instances) User and developer documentation Visualization

11 Analysis and Modeling avoid terms with ‘and’ or ‘or’ or ‘and/or’

12 Analysis and Modeling EDA Feature Analysis –Shape AnalysisShape Analysis »Pattern RecognitionPattern Recognition Genomic & Phenotypic Data Analysis Image Processing (2 instances)Image Processing(2 instances) –Atlas GenerationAtlas Generation –Cortical ModelingCortical Modeling –RegistrationRegistration –SegmentationSegmentation Network characterization Pre-Processing –Data TransformsData Transforms »Spectral TransformsSpectral Transforms »Fourier TransformFourier Transform »Wavelet TransformWavelet Transform –FilteringFiltering »Skull StrippingSkull Stripping »Inhomogeneity CorrectionInhomogeneity Correction

13 Analysis and Modeling Regulatory/Signaling network reconstruction Sequence Annotation Simulation Software Engineering and Development Tools –Cross-LanguageWrapping (1 instance)Cross-LanguageWrapping(1 instance) –Cross-Platform Tools (2 instances)Cross-Platform Tools(2 instances) –IntegrationIntegration »Graphical e.g., HIVE PipelineGraphical e.g., HIVE Pipeline »Grid Computing ResourcesGrid Computing Resources »Mappers e.g., BrainGraph BrainMapperMappers e.g., BrainGraph BrainMapper »PortalsPortals »Resource Integration ComponentsResource Integration Components –Testing Tools (2 instances)Testing Tools(2 instances)

14 Analysis and Modeling Integration is_a Software Engineering and Development Tools

15 Analysis and Modeling Statistical Analysis –E.g., RE.g., R Structure-based protein classification Toolkits (4 instances)Toolkits(4 instances) User and developer documentation Visualization –Clinical Charts e.g., DemographicsClinical Charts e.g., Demographics –Graph ViewersGraph Viewers »Hyperbolic GraphsHyperbolic Graphs »Hierarchical TreesHierarchical Trees –ImagingImaging »Cross-Sectional ViewersCross-Sectional Viewers »Manifold Viewers 2D, 3D, 4D, NDManifold Viewers 2D, 3D, 4D, ND –SequencesSequences

16 Tools –Data ManagementData Management Data Storage Data Transfer Information retrieval, traversal and querying –Ontology Development and ManagementOntology Development and Management Data Annotation Ontology Development Ontology Diff and Alignment Ontology Visualization Programmatic Access Web Access

17 Don’t be afraid to write down what seems trivial data management is_a tools data management tool is_a tool