Intersection of GI and IT

Slides:



Advertisements
Similar presentations
GMD German National Research Center for Information Technology Darmstadt University of Technology Perspectives and Priorities for Digital Libraries Research.
Advertisements

1.Data categorization 2.Information 3.Knowledge 4.Wisdom 5.Social understanding Which of the following requires a firm to expend resources to organize.
C ONTRIBUTIONS TO A THEORY OF GEOGRAPHICAL INFORMATION ENGINEERING Scientific colloquium in honour of Prof. Andre U. Frank Vienna, 2008 Gilberto Câmara.
SING* and ToNC * Scientific Foundations for Internet’s Next Generation Sirin Tekinay Program Director Theoretical Foundations Communication Research National.
Web Mapping Using XML and SVG SHEA Yu-kai Geoffrey Senior Lecturer Department of Land Surveying & Geo-Informatics The Hong Kong Polytechnic University.
1 Geographic Information Systems (GIS) Fundamentals for Program Managers.
Distinctions Between Computing Disciplines
Computational Thinking Related Efforts. CS Principles – Big Ideas  Computing is a creative human activity that engenders innovation and promotes exploration.
Semantic Web Technologies Lecture # 2 Faculty of Computer Science, IBA.
Information Technology
INFORMATION TECHNOLOGY IN BUSINESS AND SOCIETY SESSION 21 – LOCATION-BASED SERVICES SEAN J. TAYLOR.
Introduction to Computer and Programming CS-101 Lecture 6 By : Lecturer : Omer Salih Dawood Department of Computer Science College of Arts and Science.
 1. Which is not one of the six principles that address crucial issues fundamental to all school math programs? A. Curriculum B. Assessment C. Measurement.
1/24 Information Technology Definition and Curriculum.
Chapter 1 Introduction to Data Mining
Linked-data and the Internet of Things Payam Barnaghi Centre for Communication Systems Research University of Surrey March 2012.
Shaping the scientific evolution of technology enhanced learning noe-kaleidoscope.org #90 contractors — 23 countries 1100 researchers (2/3) and PhD students.
Major Disciplines in Computer Science Ken Nguyen Department of Information Technology Clayton State University.
Computing Ontology Part II. So far, We have seen the history of the ACM computing classification system – What have you observed? – What topics from CS2013.
CSE 102 Introduction to Computer Engineering What is Computer Engineering?
Breakout # 1 – Data Collecting and Making It Available Data definition “ Any information that [environmental] researchers need to accomplish their tasks”
Digital Libraries1 David Rashty. Digital Libraries2 “A library is an arsenal of liberty” Anonymous.
Computational Tools for Population Biology Tanya Berger-Wolf, Computer Science, UIC; Daniel Rubenstein, Ecology and Evolutionary Biology, Princeton; Jared.
Why to care about research?
Fire Emissions Network Sept. 4, 2002 A white paper for the development of a NSF Digital Government Program proposal Stefan Falke Washington University.
What is Multimedia Anyway? David Millard and Paul Lewis.
Informatics for Scientific Data Bio-informatics and Medical Informatics Week 9 Lecture notes INF 380E: Perspectives on Information.
Research in Computer Graphics, Visualization and Human- Computer Interaction CSc 8900/9900 Ying Zhu Associate Professor Department of Computer Science.
1998 NSF Information and Data Management Workshop Research Agenda for the 21st Century.
There is an inherent meaning in everything. “Signs for people who can see.”
National Science Foundation Engineering Research Center GeoRealism GeoRealism Expanding the human ability to comprehend a larger geo space Cyrus Shahabi.
A Context Framework for Ambient Intelligence
CompSci 280 S Introduction to Software Development
Chapter 1 Computer Technology: Your Need to Know
GIS Mapping for K-12 Students
IT Introduction Welcome to Business 514.
IOT – Firefighting Example
Computing Research for Sustainability
Information Day on “Search Engines for Audio-Visual Content”
Department of Geography Jeon-Young Kang · Yi Yang
Computer Science Courses
CCNT Lab of Zhejiang University
Independent Study of Ontologies
Stephanie Montgomery, Vice President, Technology and Standards
Preparing for the Future
Introduction to ArcGIS Software
Datamining : Refers to extracting or mining knowledge from large amounts of data Applications : Market Analysis Fraud Detection Customer Retention Production.
Chapter 29 Emerging Technologies and the Generation of Knowledge
Mobile Commerce and the Internet of Things
Distributed Systems Bina Ramamurthy 11/12/2018 From the CDK text.
Ambient Intelligence -by Internal Guide: M.Preethi(10C91A0563)
Data Warehousing and Data Mining
Putting trash in its place: Participatory GIS, social networking, and targeting unofficial trash sites Frank Lafone Trevor Harris Department of Geology.
What are your Career Options?
Distributed Systems Bina Ramamurthy 12/2/2018 B.Ramamurthy.
C.U.SHAH COLLEGE OF ENG. & TECH.
Data Mining: Concepts and Techniques
Distributed systems: How did we get here?
Data Mining: Concepts and Techniques
Smart Learning concepts to enhance SMART Universities in Africa
Syed Masiur Rahman (student id #220256)
Lecture 2 Components of GIS
Web Mining Department of Computer Science and Engg.
PPT1: Basics of software engineering
Software and Software Engineering
Data Mining: Concepts and Techniques
Social Abstractions for Information agents
Stephanie Montgomery, Vice President, Technology and Standards
IEEE IT (Information Technology) Strategy – 2005
V. Uddameri Texas Tech University
Presentation transcript:

Intersection of GI and IT Spatial Databases Max J. Egenhofer National Center for Geographic Information and Analysis Department of Spatial Information Science and Engineering University of Maine

Outline A reflection on GI  IT Some technical challenges Some community challenges Evolution of GI and its implications Conclusions and near-term success measures

GI  IT Geospatial Information  Information Technology = ?

GI  IT Geospatial Information  Information Technology = ?

GI  IT Geospatial Information  Information Technology = Information

GI  IT GI IT

GI  IT GI IT

GI  IT GI IT

GI  IT GI IT

GI  IT GI IT

GI  IT GI IT

GI  IT GI IT

GI  IT GI IT

GI  IT GI IT

GI  IT IT GI

GI  IT IT GI

GI  IT IT GI

GI  IT GI IT

GI  IT GI IT

GI  IT Geospatial Information  Information Technology = Information

GI  IT Geospatial Information  Information Technology = Information

GI  IT Geospatial Information  Information Science = Information

GI  IT Geospatial Information Systems  Information Science = Information

GI  IT Geospatial Information Systems  Information Science = Information

GI  IT Geospatial Information Science  Information Science = Information

GI  IT Geospatial Information Science  Information Science = Information

GI  IT Geospatial Information Science  Computer Science = Information

GI  IT Geospatial Information Science  Computer Science = Information

Geosptial Informtion Science GI  IT Geosptial Informtion Science  Computer Science = Information

Geosal Inftion Science GI  IT Geosal Inftion Science  Computer Science = Information

GI  IT Geal Infn Science  Computer Science = Information

GI  IT Ge In Science  Computer Science = Information

GI  IT GIScience  Computer Science = Information

GI  IT GIScience  Computer Science = Information

GI  IT GIEngineering  Computer Science = Information

What are these Information Technologies? GI*  IT What are these Information Technologies?

Information Technologies Global Positioning Systems (GPS)

Information Technologies Cell phones

Information Technologies Portable computing devices

Information Technologies Digital cameras

Information Technologies Digital video cameras

Information Technologies Miniaturization of Location Devices - GPS receivers - Gyroscopes

Information Technologies chem bio Microsensors

Opportunities Mobile geospatial computing New gadgets GI for the masses Tighter integration of data acquisition with spatial databases Real-time 3D model building Spatialized video Augmented reality Sensor-based GISs

Impediments Low wireless bandwidth Lack of appropriate models for spatio-temporal fields

Database Challenges Massively parallel data acquisition Intelligent pre-fetch strategies Generation of incremental spatial query results and their presentation

What are these parts of computer science? GI*  CS What are these parts of computer science?

The CS Foundation for GI* GIS User Interfaces Graphical Presentation Spatial Reasoning Semantics Geometric Calculations Very Large Data Sets Programming in the Large/Gigantic Complex Operations Data Transfer

The CS Foundation for GI* Human-Computer Interaction GIS User Interfaces Graphical Presentation Graphics AI Spatial Reasoning Information Retrieval Semantics Geometric Calculations Computational Geometry Very Large Data Sets Database Systems Software Engineering Programming in the Large/Gigantic Algorithms Complex Operations Networking Data Transfer

Opportunities

Opportunities Human-Computer Interaction Graphics AI Information Retrieval Computational Geometry Database Systems Database Systems Networking LBS Software Engineering Algorithms Networking

Human-Computer Interaction Opportunities Human-Computer Interaction In-situ terrain interaction Graphics AI Information Retrieval Database Systems Computational Geometry Computational Geometry Database Systems Software Engineering Algorithms Networking

Human-Computer Interaction Opportunities Database Systems Human-Computer Interaction Human-Computer Interaction Graphics Gadgets AI Information Retrieval Computational Geometry Database Systems Software Engineering Algorithms Networking

Impediments

Impediments Human-Computer Interaction GIS User Interfaces Graphical Presentation Graphics AI Spatial Reasoning Information Retrieval Semantics Geometric Calculations Computational Geometry Very Large Data Sets Database Systems Software Engineering Programming in the Large/Gigantic Algorithms Complex Operations Networking Data Transfer

Impediments Human-Computer Interaction GIS User Interfaces Graphical Presentation Graphics AI Spatial Reasoning Information Retrieval Semantics Geometric Calculations Computational Geometry Very Large Data Sets Database Systems Software Engineering Programming in the Large/Gigantic Algorithms Complex Operations Networking

Impediments Human-Computer Interaction GIS User Interfaces Graphical Presentation Graphics AI Spatial Reasoning Information Retrieval Semantics Geometric Calculations Computational Geometry Very Large Data Sets Database Systems Software Engineering Programming in the Large/Gigantic Algorithms Algorithms Complex Operations Networking

Challenges Join forces Explore common concepts Learn to understand different terminologies Develop interfaces Exploit the best of two (or more) worlds

Will GI* remain the same as we know it today?

Evolution of Geospatial Information Phase 1: Abundance of geospatial data • Enabled by geospatial data acquisition technologies • Geospatial data are unconventional, need special treatment • Geospatial databases are often very large • Geospatial data often linked with time-critical data • Analysis primarily through geometric operations

Evolution of Geospatial Information Phase 2: Implicit geospatial information • Geospatial descriptions in text form • Enabled by the Web and (digital) archives • Spatial reasoning without explicit geometry • Improved understanding through graphical summaries of text

Evolution of Geospatial Information Phase 3: From geospatial to spatial • Spatial (and spatio-temporal) similarities across vastly different scales (from DNA to galaxies) • Ontological differences • Need to capture semantics comprehensively • Analysis requires geometry plus meaning • Opportunity for GI to play a key role

Result: The Spatial Web Vast amount of heterogeneous spatial data sources • Needs dramatically better support for richly structured ontologies in databases • Ability to query and integrate across different ontologies • Spatial information as the integrator of data

Evolution of Geospatial Information Phase 4: Space as an organizational metaphor in information science • Dealing with spatial information provides a meaningful vocabulary • Metaphorical use of spatial terminology • The ease of communicating spatially • Analytical power of spatial reasoning • Foundation for a new information theory?

Result Ubiquitous Spatial Databases

GI  IT GIScience  Computer Science = Information

GI  IT GIScience  Computer Science = Information

GI  IT SIScience  Computer Science = Information

GI  IT Se In Science  Computer Science = Information

GI  IT Seal Infn Science  Computer Science = Information

GI  IT Seosal Inftion Science  Computer Science = Information

GI  IT Seotial In formtion Science  Computer Science = Information

GI  IT Spatial Information Science  Computer Science = Information

Conclusions Spatial databases has been at the forefront of GI  CS for over 10 years New challenges are relative to semantics LBS is the short-term future of applied GI  IT More profound issues in the role of spatial in the overall organization of information Needs joined forces, within CS and across relevant disciplines

Near-Term Success for GI  IT Regular GI articles in Communications of the ACM and IEEE Computer Stronger CS participation in UCGIS Strong CS participation in GIScience 2002 Concentrated Federal Funding programs in GIScience and Engineering (from CISE to GISE or SISE) ACM SIGGIS