Supported in part by the National Science Foundation under Grant No. HRD-0734825. Any opinions, findings, and conclusions or recommendations expressed.

Slides:



Advertisements
Similar presentations
Dr. Leo Obrst MITRE Information Semantics Information Discovery & Understanding Command & Control Center February 6, 2014February 6, 2014February 6, 2014.
Advertisements

Requirements. UC&R: Phase Compliance model –RIF must define a compliance model that will identify required/optional features Default.
VisKo: Enabling Visualization Generation Over the Web Nicholas Del Rio – UTEP Paulo Pinheiro - PNNL 1
Querying on the Web: XQuery, RDQL, SparQL Semantic Web - Spring 2006 Computer Engineering Department Sharif University of Technology.
University of Kentucky GENI User Tools and the Control Plane Zongming Fei, Jim Griffioen University of Kentucky.
Dave Kolas, BBN Technologies Terra Cognita 08 Karlsruhe, Germany 10/26/08 1 Supporting Spatial Semantics with SPARQL.
Hermes: News Personalization Using Semantic Web Technologies
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 8 Slide 1 System modeling 2.
K S L W i n e A g e n t : Testbed Application for Semantic Web Technologies Deborah McGuinness Eric Hsu Jessica Jenkins Rob McCool Sheila McIlraith Paulo.
DSM Workshop, October 22 OOPSLA 2006 Model-Based Workflows Leonardo Salayandía University of Texas at El Paso.
Surfing the Service Web Sudhir Agarwal, Siegfried Handschuh, and Steffen Staab Presenter: Yihong Ding.
March 17, 2008SAC WT Hermes: a Semantic Web-Based News Decision Support System* Flavius Frasincar Erasmus University Rotterdam.
An Intelligent Broker Approach to Semantics-based Service Composition Yufeng Zhang National Lab. for Parallel and Distributed Processing Department of.
Information Fusion: Moving from domain independent to domain literate approaches Professor Deborah L. McGuinness Tetherless World Constellation, Rensselaer.
Semantic Mediation & OWS 8 Glenn Guempel
Visualization Knowledge (VisKo): Leveraging the Semantic Web to Support VisualizationVisKo University of Texas at El Paso Computer Science.
Visualization Knowledge (VisKo): Leveraging the Semantic Web to Support VisualizationVisKo Nicholas Del Rio CyberShARE Center University of Texas at El.
Semantic Web Bootcamp Dominic DiFranzo PhD Student/Research Assistant Rensselaer Polytechnic Institute Tetherless World Constellation.
Amarnath Gupta Univ. of California San Diego. An Abstract Question There is no concrete answer …but …
© 2006 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice Publishing data on the Web (with.
Web Explanations for Semantic Heterogeneity Discovery Pavel Shvaiko 2 nd European Semantic Web Conference (ESWC), 1 June 2005, Crete, Greece work in collaboration.
Information Integration Intelligence with TopBraid Suite SemTech, San Jose, Holger Knublauch
Configurable User Interface Framework for Cross-Disciplinary and Citizen Science Presented by: Peter Fox Authors: Eric Rozell, Han Wang, Patrick West,
Discovering E-Services Using UDDI in SELF-SERV Quan Z. Sheng, Boualem Benatallah, Rayan Stephan, Eileen Oi-Yan Mak, Yan Q. Zhu School of Computer Science.
To advance and integrate education and research in uncertainty, trust, and optimization in support of cyberinfrastructures and to develop scientist-centered.
The Semantic Web Web Science Systems Development Spring 2015.
Software Design Patterns for Information Visualization 薛乃榮 Q NCBCI LAB.
Trisolda Jakub Yaghob Charles University in Prague, Czech Rep.
A Query Translation Scheme for Rapid Implementation of Wrappers Presented By Preetham Swaminathan 03/22/2007 Yannis Papakonstantinou, Ashish Gupta, Hector.
AUTOMATION OF WEB-FORM CREATION - KINNERA ANGADI – MS FINAL DEFENSE GUIDANCE BY – DR. DANIEL ANDRESEN.
Eurostat Expression language (EL) in Eurostat SDMX - TWG Luxembourg, 5 Jun 2013 Adam Wroński.
CARDIAC ELECTROPHYSIOLOGY WEB LAB Developing your own protocol descriptions.
Modeling and Representing National Climate Assessment Information using Linked Data Jin Guang Zheng 1 Curt Tilmes 2
Visualization Knowledge (VisKo): Leveraging the Semantic Web to Support VisualizationVisKo Paulo Pinheiro da Silva and Nicholas Del Rio CyberShARE Center.
©Ferenc Vajda 1 Semantic Grid Ferenc Vajda Computer and Automation Research Institute Hungarian Academy of Sciences.
A Context Model based on Ontological Languages: a Proposal for Information Visualization School of Informatics Castilla-La Mancha University Ramón Hervás.
GEON Cyberinfrastructure Workshop Beijing, China, July 21-23, 2006 Workflow-Driven Ontologies for the Geosciences Leonardo Salayandía The University of.
WDO-It! 101 Workshop: Creating an abstraction of a process UTEP’s Trust Laboratory NDR HP MP.
Ontology-Based Computing Kenneth Baclawski Northeastern University and Jarg.
WDO-It! 102 Workshop: Using an abstraction of a process to capture provenance UTEP’s Trust Laboratory NDR HP MP.
Tool for Ontology Paraphrasing, Querying and Visualization on the Semantic Web Project By Senthil Kumar K III MCA (SS)‏
VLDB2005 CMS-ToPSS: Efficient Dissemination of RSS Documents Milenko Petrovic Haifeng Liu Hans-Arno Jacobsen University of Toronto.
Visualization Knowledge Query Language (VKQL) Workshop Nicholas Del Rio University of Texas at El Paso Computer Science.
User Profiling using Semantic Web Group members: Ashwin Somaiah Asha Stephen Charlie Sudharshan Reddy.
Scientific Workflow systems: Summary and Opportunities for SEEK and e-Science.
Semantic Phyloinformatic Web Services Using the EvoInfo Stack Speaker: John Harney LSDIS Lab, Dept. of Computer Science, University of Georgia Mentor(s):
Visualization Four groups Design pattern for information visualization
Ontology based e-Real Estate Agency Information System By Moein Mehrolhasani Bijan Zamanian cmpe 588.
A Semantic Web Approach for the Third Provenance Challenge Tetherless World Rensselaer Polytechnic Institute James Michaelis, Li Ding,
CHAPTER 4 THE VISUALIZATION PIPELINE. CONTENTS The focus is on presenting the structure of a complete visualization application, both from a conceptual.
Conclusions Presenter: Manolis Koubarakis Extended Semantic Web Conference 2012.
Personalized Recommendation of Related Content Based on Automatic Metadata Extraction Andreas Nauerz 1, Fedor Bakalov 2, Birgitta.
Supported in part by the National Science Foundation under Grant No. HRD Any opinions, findings, and conclusions or recommendations expressed.
Explainable Adaptive Assistants Deborah L. McGuinness, Tetherless World Constellation, RPI Alyssa Glass, Stanford University Michael Wolverton, SRI International.
A Declarative Domain-Free Approach for Querying and Generating Visualizations Nicholas Del Rio 1 1 Committee Chair:Dr. Paulo Pinheiro 1 Dr. Vladik Kreinovich.
1 A Medical Information Management System Using the Semantic Web Technology Networked Computing and Advanced INFORMATION MANAGEMENT, NCM '08. Fourth.
Semantic Water Quality Portal Jin Guang Zheng and Ping Wang Tetherless World Constellation.
NSF Cyber Trust Annual Principal Investigator Meeting September 2005 Newport Beach, California UMBC an Honors University in Maryland Trust and Security.
Rinke Hoekstra Use of OWL in the Legal Domain Statement of Interest OWLED 2008 DC, Gaithersburg.
VisKo: Enabling Visualization Generation Over the Web Nicholas Del Rio – UTEP Paulo Pinheiro - PNNL 1
Annotating and Embedding Provenance in Science Data Repositories to Enable Next Generation Science Applications Deborah L. McGuinness.
Components.
Encoding Extraction as Inferences
Web Ontology Language for Service (OWL-S)
Discussion and Conclusion
Session 2: Metadata and Catalogues
Dr. Bhavani Thuraisingham The University of Texas at Dallas
Chaitali Gupta, Madhusudhan Govindaraju
This material is based upon work supported by the National Science Foundation under Grant #XXXXXX. Any opinions, findings, and conclusions or recommendations.
Taxonomy of public services
Presentation transcript:

Supported in part by the National Science Foundation under Grant No. HRD Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Visualization Queries: University of Texas at El Paso Computer Science Trust Lab and Center of Excellence Sharing Resources to Advance Research and Education through Cyber-infrastructure CI GEO ED X-INF ES The pipeline composition rules are applied to a knowledge base of visualization toolkit operators, ranging from Visualization Toolkit (VTK), NCAR Command Language (NCL), and Generic Mapping Tools (GMT). Each toolkit operator description is encoded in the Resource Document Framework (RDF), and includes: The input formats ingested The output format of the data produced The classification of the operator (e.g., viewer, transformer, mapper) The generated view if the operator is a mapper vtkImage Reader vtk Contour Filter vtkJPEG Writer dim, scalar type, byte order interval, color function {color function} {magnification} Vtk PolyData Mapper vtkImageData vtkPolyData vtkRender Window Knowledge Base of Toolkit Operators Nicholas Del Rio and Paulo Pinheiro da Silva Visualization toolkits, such as Generic Mapping Tools (GMT) and Visualization Toolkit (VTK), consist of a suite of visualization operators from which users can chain together and build visualization applications. Using these toolkits can be challenging because users must: develop the applications using procedural code, and thus understand implementation details associated with each operator, including input/output formats, parameters, and function. Background A knowledge enhanced management system ingests the query and knows how to derive visualization pipelines. The system applies a set of rules for composing pipelines defined by the Web Ontology Language (OWL) and SPARQL queries. Input format of first pipeline operator must match format of data Output format of operator must match input format of following operator Output format of final operator must match input format of viewer Pipelines must contain an operator that generates the requested view Pellet is used to derive the pipelines provided: Information specified in the query Pipeline composition rules Knowledge base of toolkit operators Query Processing PREFIX formatshttp://rio.cs.utep.edu/ciserver/ciprojects/formats/ PREFIX typeshttp://rio.cs.utep.edu/ciserver/ciprojects/HolesCode/HolesCodeWDO.owl# PREFIX viskohttp://rio.cs.utep.edu/ciserver/ciprojects/visko/ PREFIX paramshttp://trust.utep.edu/visko/services/vtkVolumeService.owl# SELECT * IN-VIEWER visko:firefox FROM FORMAT formats:BINARYFLOATARRAY TYPE types:d2 The wild card (*) symbol was used in place of the view, resulting in multiple visualizations. Example: Velocity Model A Declarative Approach To Generating Visualizations Using the Semantic Web With the goal of improving scientists’ experience using visualization technology, we have applied the query-answering pattern to a visualization setting, where scientists specify what visualizations they want generated using a declarative SQL-like notation known as Visualization Query. Visualization Query Language PREFIX formatshttp://utep.edu/formats.owl# PREFIX typeshttp://utep.edu/HolesCodeWDO.owl# PREFIX viskohttp://utep.edu/visko.owl# PREFIX paramshttp://utep.edu/MapperParams.owl# SELECT visko:isosurfaces IN-VIEWER visko:firefox FROM FORMAT formats:BINARYFLOATARRAY TYPE types:d2 WHERE params:xRotation = 104AND params:yRotation = 0AND params:zRotation = 0 PREFIX viskohttp://rio.cs.utep.edu/ciserver/ciprojects/visko/ PREFIX paramshttp://trust.utep.edu/visko/services/netCDFTimeSeries.owl# SELECT visko:XYPlot IN-VIEWER visko:firefox FROM FORMAT TYPE visko:e1 WHERE params:title = Average-Data AND params:xDimSize = 338 AND params:xDimName = time AND params:yRAxisLabel = Mean-CO2 AND params:rPlotVariablesList = mean_CO2 AND params:yLAxisLabel = Mean-H2O-HMP AND params:lPlotVariablesList = mean_H2O_hmp Example: Environmental Data Parameter bindings fully specified Parameters controlled the plot annotation (e.g., titles and labels ) No parameter bindings, system will roll back to defaults Prefix Section (optional) View and Viewer Specification Data Characterization Parameter Bindings (optional) Parameter Format/Type Operator hasParam buildsView hasInput/Output View Geometry isa OWL-Service implementedBy