Geospatial Semantics. Yingjie Hu. Geospatial Semantics
|
|
|
- Cornelius Bradford
- 6 years ago
- Views:
Transcription
1
2 Outline What is geospatial? Why do we need it? Existing researches. Conclusions.
3 What is geospatial? Semantics The meaning of expressions Syntax How you express the meaning E.g. I love GIS
4 What is geospatial? Semantics The meaning of expressions Syntax How you express the meaning E.g. I love GIS I GIS
5 What is geospatial? Semantics The meaning of expressions Syntax How you express the meaning E.g. I love GIS I GIS Different syntaxes Same meaning
6 What is geospatial? Geospatial The meaning of geospatial data Thematic information, Data source, coordinate systems, data collection time The meaning of geospatial functions The meaning of the input data, the capability of this function, the meaning of the output data
7 Why do we need geospatial? Making computers understand the meaning of geospatial data and functions. Computers cannot truly understand the meaning of data and functions. E.g. Contours treated as polylines Systems are like parrots mimicking language without understanding it.
8 Why do we need geospatial? I like GIS (human language) What did I say???
9 Why do we need geospatial? Why do we need to make computers understand the geospatial data and functions, since our humans can do that?
10 Why do we need geospatial? The reason lies in the distributed geospatial data and functions.
11 Why do we need geospatial? Previously, geospatial data and functions resided locally (which can be easily understood by local community members) Today, they are distributed at different places throughout the world (which requires much interpretation work)
12 Why do we need geospatial? How can we make computers autonomously retrieve the right geospatial data and functions without human intervention?
13 Why do we need geospatial Several approaches? Syntactically define geospatial services E.g. Web service description language (WSDL) defines the type of the input and output data Does not semantically define the services Services with different meanings may be falsely combined together. (temperature and wind direction)
14 Why do we need geospatial? Several approaches Metadata (Data s data) Synonymy (Different words same meaning) UC Santa Barbara and UCSB Zip code and postal code Polysemy (Same word has different meanings) Address (location or speech?) Wood (a piece of tree or an area covered with trees?)
15 How can we make computers understand the meaning of geospatial data and functions since it is so complicated?
16 ??? Web service A Name: Bank Description: The number of banks in this area Output: Integer I want to find the service about bank, but which one Web service B Name: Riverside Description: The number of riversides in this area Output: Integer
17 What can we do? Writing an algorithm to make computers understand the literal meaning of the word?
18 What can we do? Writing an algorithm to make computer understand the literal meaning of the word? But only given the word bank, even humans cannot understand its exact meaning.
19 What can we do? Writing an algorithm to make computer understand the literal meaning of the word? But only given the word bank, even humans cannot understand its exact meaning. Using more detailed metadata to describe the function of the two services?
20 What can we do? Writing an algorithm to make computer understand the literal meaning of the word? But only given the word bank, even humans cannot understand its exact meaning. Using more detailed metadata to describe the function of the two services? But different service providers will describe the services in different ways. How can we suppose a computer to understand these various descriptions?
21 Experience of dealing with geographic information gives us the inspiration to solve this problem. A piece of geographic information can be decomposed as three parts: spatial, temporal and thematic data.
22 Spatial data (Where) Spatial reference system (X, Y)
23 Temporal Data (When) Temporal reference system (Calendar) Jan. 12th, 2012
24 Thematic Data (What) Would it be nice if we also have a semantic reference system? Bank
25 Impossible? Imagine the world before spatial reference systems and calendars, accurately expressing spatial and temporal information would be as difficult as describing thematic data.
26 How to establish semantic reference systems?
27 How to establish semantic reference systems? Ontologies
28 Ontologies Originally come from philosophy. Now used in computer and information science. Specify the meaning of the terms used in a domain and the relations among these terms. Common components in an ontology Classes: concepts about things e.g. car, table Properties: relations connecting classes e.g. is a, has Individuals: specific objects e.g. this car, that table
29 In ontologies, we can have Bank Is one side of River Bank Deals with Money
30 Problem solved? Our solution is based on the assumption that people also agree on using the classes of river and money and the properties of is one side of and deals with.
31 Problem solved? Our solution is based on the assumption that people also agree on using the classes of river and money and the properties of is one side of and deals with. What if some people use stream instead of river in their ontologies?
32 Problem solved? Our solution is based on the assumption that people also agree on using the classes of river and money and the properties of is one side of and deals with. What if some people use stream instead of river in their ontologies? Then do we have to create ontologies to define every word in our world? That may be even more difficult than creating a new language.
33 Foundation ontology (upper ontology) An ontology which describes general terms across domains and which is agreed and shared by a large community. Classes and properties are considered as primitive elements. Domain ontologies Ontologies for a specific domain. Concepts are constructed based on primitive elements. Shared by people in particular fields.
34
35 Foundation ontology Domain ontology Person School Is a Studies in Person Is a Student Studies in School
36 Different domain ontologies can be transformed to one another since they are all constructed based on the foundation ontology. Just like one spatial reference systems can be transformed to another based on mathematical methods.
37 Problems remain Is it possible to create a foundation ontology agreed by most people? The number of primitive elements is not infinite. It is estimated that there may be 2,000 to 10,000 classes and properties in the foundation ontology. It does not have to be agreed by everyone in this world. Developers will use it to make profits if there is a shared agreement in a large enough community. Existing foundation ontologies: Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE), Basic Formal Ontology (BFO)
38 Conclusions Geospatial means the meaning of geospatial data and functions. Geospatial can help computers find the right data and functions without human intervention. Ontologies can be used to construct semantic reference systems that can clarify the meaning of data and functions.
39 Reference Kuhn, W. (2005). : Why, of What, and How? Journal on Data Semantics III, LNCS, 3534, Kuhn, W., (2003). Semantic Reference Systems. International Journal of Geographical Information Science, Guest Editorial, 17(5), pp Janowicz, K. and Scheider, S. (2010): Semantic Reference Systems. In: Encyclopedia of Geography. B. Warf (Ed.). SAGE Publications. Frank (2003), Ontology for Spatio-temporal Databases, Lecture Notes in Computer Science, 2003, Volume 2520/2003, 9-77.
A General Framework for Conflation
A General Framework for Conflation Benjamin Adams, Linna Li, Martin Raubal, Michael F. Goodchild University of California, Santa Barbara, CA, USA Email: badams@cs.ucsb.edu, linna@geog.ucsb.edu, raubal@geog.ucsb.edu,
From Research Objects to Research Networks: Combining Spatial and Semantic Search
From Research Objects to Research Networks: Combining Spatial and Semantic Search Sara Lafia 1 and Lisa Staehli 2 1 Department of Geography, UCSB, Santa Barbara, CA, USA 2 Institute of Cartography and
Cognitive Engineering for Geographic Information Science
Cognitive Engineering for Geographic Information Science Martin Raubal Department of Geography, UCSB raubal@geog.ucsb.edu 21 Jan 2009 ThinkSpatial, UCSB 1 GIScience Motivation systematic study of all aspects
Geographic Analysis of Linguistically Encoded Movement Patterns A Contextualized Perspective
Geographic Analysis of Linguistically Encoded Movement Patterns A Contextualized Perspective Alexander Klippel 1, Alan MacEachren 1, Prasenjit Mitra 2, Ian Turton 1, Xiao Zhang 2, Anuj Jaiswal 2, Kean
GEO-INFORMATION (LAKE DATA) SERVICE BASED ON ONTOLOGY
GEO-INFORMATION (LAKE DATA) SERVICE BASED ON ONTOLOGY Long-hua He* and Junjie Li Nanjing Institute of Geography & Limnology, Chinese Academy of Science, Nanjing 210008, China * Email: lhhe@niglas.ac.cn
Modeling and Managing the Semantics of Geospatial Data and Services
Modeling and Managing the Semantics of Geospatial Data and Services Werner Kuhn, Martin Raubal, Michael Lutz Institute for Geoinformatics University of Münster (Germany) {kuhn, raubal, m.lutz}@uni-muenster.de
15-424/ Recitation 1 First-Order Logic, Syntax and Semantics, and Differential Equations Notes by: Brandon Bohrer
15-424/15-624 Recitation 1 First-Order Logic, Syntax and Semantics, and Differential Equations Notes by: Brandon Bohrer (bbohrer@cs.cmu.edu) 1 Agenda Admin Everyone should have access to both Piazza and
GEOGRAPHICAL NAMES ONTOLOGY
GEOGRAPHICAL NAMES ONTOLOGY Željka JAKIR, Željko HEĆIMOVIĆ, Zvonko ŠTEFAN zeljka.jakir@cgi.hr, zeljko.hecimovic@cgi.hr, zvonko.stefan@cgi.hr 1 CONTENTS: I. About semantic and semantic web of data II. About
Syntactic Patterns of Spatial Relations in Text
Syntactic Patterns of Spatial Relations in Text Shaonan Zhu, Xueying Zhang Key Laboratory of Virtual Geography Environment,Ministry of Education, Nanjing Normal University,Nanjing, China Abstract: Natural
Logic. Introduction to Artificial Intelligence CS/ECE 348 Lecture 11 September 27, 2001
Logic Introduction to Artificial Intelligence CS/ECE 348 Lecture 11 September 27, 2001 Last Lecture Games Cont. α-β pruning Outline Games with chance, e.g. Backgammon Logical Agents and thewumpus World
Taxonomies of Building Objects towards Topographic and Thematic Geo-Ontologies
Taxonomies of Building Objects towards Topographic and Thematic Geo-Ontologies Melih Basaraner Division of Cartography, Department of Geomatic Engineering, Yildiz Technical University (YTU), Istanbul Turkey
Ontologies and Spatial Decision Support
Ontologies and Spatial Decision Support Naicong Li, Philip Murphy, The Redlands Institute, University of Redlands Krzysztof Janowicz, University of California, Santa Barbara Earth Science-Ontolog mini
ISO Plant Hardiness Zones Data Product Specification
ISO 19131 Plant Hardiness Zones Data Product Specification Revision: A Page 1 of 12 Data specification: Plant Hardiness Zones - Table of Contents - 1. OVERVIEW...3 1.1. Informal description...3 1.2. Data
The Relevance of Spatial Relation Terms and Geographical Feature Types
The Relevance of Spatial Relation Terms and Geographical Feature Types Reporter Chunju Zhang Date: 2012-05-29 1 2 Introduction Classification of Spatial Relation Terms 3 4 5 Calculation of Relevance Conclusion
Dynamic Ontology Service for Historical Persons and Places Based on Crowdsourcing
Dynamic Ontology Service for Historical Persons and Places Based on Crowdsourcing 22.1.2016, COST RRL WG2 Workshop Jouni Tuominen Semantic Computing Research Group (SeCo), http://seco.cs.aalto.fi, Aalto
Spatializing Research Hypotheses a long- term research vision for
Spatializing Research Hypotheses a long- term research vision for spatial@ucsb Werner Kuhn Center for Spatial Studies a vision for spatial Spatial computing shall reach the same level of general utility
Lecture 1: Geospatial Data Models
Lecture 1: GEOG413/613 Dr. Anthony Jjumba Introduction Course Outline Journal Article Review Projects (and short presentations) Final Exam (April 3) Participation in class discussions Geog413/Geog613 A
Towards Process-Based Ontology for Representing Dynamic Geospatial Phenomena
Towards Process-Based Ontology for Representing Dynamic Geospatial Phenomena Anusuriya Devaraju Institute for Geoinformatics, University of Muenster, Germany anusuriya.devaraju@uni-muenster.de 1 Introduction
CS1021. Why logic? Logic about inference or argument. Start from assumptions or axioms. Make deductions according to rules of reasoning.
3: Logic Why logic? Logic about inference or argument Start from assumptions or axioms Make deductions according to rules of reasoning Logic 3-1 Why logic? (continued) If I don t buy a lottery ticket on
CyberGIS: What Still Needs to Be Done? Michael F. Goodchild University of California Santa Barbara
CyberGIS: What Still Needs to Be Done? Michael F. Goodchild University of California Santa Barbara Progress to date Interoperable location referencing coordinate transformations geocoding addresses point-of-interest
Spatial Webs. Michael F. Goodchild University of California Santa Barbara
Spatial Webs Michael F. Goodchild University of California Santa Barbara The locations of computing User location u the user interface Processing location p u-p 1960s < 10m dedicated lines ca 1970
Geospatial Semantics: Why, of What, and How?
Geospatial Semantics: Why, of What, and How? Werner Kuhn Institute for Geoinformatics University of Münster Robert-Koch-Str. 26-28 D-48151 Münster (Germany) kuhn@uni-muenster.de Abstract. Why are notions
Introduction INTRODUCTION TO GIS GIS - GIS GIS 1/12/2015. New York Association of Professional Land Surveyors January 22, 2015
New York Association of Professional Land Surveyors January 22, 2015 INTRODUCTION TO GIS Introduction GIS - GIS GIS 1 2 What is a GIS Geographic of or relating to geography the study of the physical features
Key Words: geospatial ontologies, formal concept analysis, semantic integration, multi-scale, multi-context.
Marinos Kavouras & Margarita Kokla Department of Rural and Surveying Engineering National Technical University of Athens 9, H. Polytechniou Str., 157 80 Zografos Campus, Athens - Greece Tel: 30+1+772-2731/2637,
CS560 Knowledge Discovery and Management. CS560 - Lecture 3 1
CS560 Knowledge Discovery and Management Yugi Lee STB #560D (816) 235-5932 leeyu@umkc.edu www.sce.umkc.edu/~leeyu CS560 - Lecture 3 1 Logic A logic allows the axiomatization of the domain information,
Zero Hours of System Training
Zero Hours of System Training A challenge for the next 25 years Werner Kuhn Center for Spatial Studies Department of Geography University of California at Santa Barbara 1854 http://en.wikipedia.org/wiki/file:snow-cholera-map-1.jpg
Crossing the Atlantic: Then and Now
Your web browser (Safari 7) is out of date. For more security, comfort and Activitydevelop the best experience on this site: Update your browser Ignore Crossing the Atlantic: Then and Now How has the amount
Spatial Data on the Web Working Group. Geospatial RDA P9 Barcelona, 5 April 2017
Spatial Data on the Web Working Group Geospatial IG @ RDA P9 Barcelona, 5 April 2017 Spatial Data on the Web Joint effort of the World Wide Web Consortium (W3C) and the Open Geospatial Consortium (OGC)
Modeling Discrete Processes Over Multiple Levels Of Detail Using Partial Function Application
Modeling Discrete Processes Over Multiple Levels Of Detail Using Partial Function Application Paul WEISER a and Andrew U. FRANK a a Technical University of Vienna Institute for Geoinformation and Cartography,
A Case Study for Semantic Translation of the Water Framework Directive and a Topographic Database
A Case Study for Semantic Translation of the Water Framework Directive and a Topographic Database Angela Schwering * + Glen Hart + + Ordnance Survey of Great Britain Southampton, U.K. * Institute for Geoinformatics,
MONITORING LOGISTICS OPERATIONS OF THE FOREST BASED SUPPLY CHAIN IN (NEAR) REAL-TIME UTILIZING HARMONIZATION APPROACHES: a Case Study from Austria
MONITORING LOGISTICS OPERATIONS OF THE FOREST BASED SUPPLY CHAIN IN (NEAR) REAL-TIME UTILIZING HARMONIZATION APPROACHES: a Case Study from Austria Johannes Scholz 1 Manfred Mittlboeck 2 Ralph Jank 2 1
Towards knowledge-based integration and visualization of geospatial data using Semantic Web technologies *
Towards knowledge-based integration and visualization of geospatial data using Semantic Web technologies * Weiming Huang GIS Centre, Lund University, Lund, Sweden weiming.huang@nateko.lu.se Abstract. Geospatial
Semantics, ontologies and escience for the Geosciences
Semantics, ontologies and escience for the Geosciences Femke Reitsma¹, John Laxton², Stuart Ballard³, Werner Kuhn, Alia Abdelmoty ¹femke.reitsma@ed.ac.uk: School of Geosciences, Edinburgh University ²
Ling 130 Notes: Syntax and Semantics of Propositional Logic
Ling 130 Notes: Syntax and Semantics of Propositional Logic Sophia A. Malamud January 21, 2011 1 Preliminaries. Goals: Motivate propositional logic syntax and inferencing. Feel comfortable manipulating
Bringing machine learning & compositional semantics together: central concepts
Bringing machine learning & compositional semantics together: central concepts https://githubcom/cgpotts/annualreview-complearning Chris Potts Stanford Linguistics CS 244U: Natural language understanding
Syllogistic Logic and its Extensions
1/31 Syllogistic Logic and its Extensions Larry Moss, Indiana University NASSLLI 2014 2/31 Logic and Language: Traditional Syllogisms All men are mortal. Socrates is a man. Socrates is mortal. Some men
The Nature and Value of Geographic Information. Michael F. Goodchild University of California Santa Barbara
The Nature and Value of Geographic Information Michael F. Goodchild University of California Santa Barbara What is the GI in GIScience?! Is information stuff? if it is, then it must be possible to measure
Dale Jacquette CONUNDRUMS OF CONDITIONALS IN CONTRAPOSITION
Dale Jacquette CONUNDRUMS OF CONDITIONALS IN CONTRAPOSITION A previously unnoticed metalogical paradox about contraposition is formulated in the informal metalanguage of propositional logic, where it exploits
Philosophy of Science: Models in Science
Philosophy of Science: Models in Science Kristina Rolin 2012 Questions What is a scientific theory and how does it relate to the world? What is a model? How do models differ from theories and how do they
How to Handle Incomplete Knowledge Concerning Moving Objects
B B is How to Handle Incomplete Knowledge Concerning Moving Objects Nico Van de Weghe 1, Peter Bogaert 1, Anthony G. Cohn 2, Matthias Delafontaine 1, Leen De Temmerman 1, Tijs Neutens 1, Philippe De Maeyer
Towards Geographic Information Observatories
Towards Geographic Information Observatories Krzysztof Janowicz 1, Benjamin Adams 2, Grant McKenzie 1, and Tomi Kauppinen 3,4 1 University of California, Santa Barbara, USA 2 The University of Auckland,
Why Is Cartographic Generalization So Hard?
1 Why Is Cartographic Generalization So Hard? Andrew U. Frank Department for Geoinformation and Cartography Gusshausstrasse 27-29/E-127-1 A-1040 Vienna, Austria frank@geoinfo.tuwien.ac.at 1 Introduction
An Egocentric Reference System for Affordances
Undefined 0 (2012) 1 0 1 IOS Press An Egocentric Reference System for Affordances Editor(s): Name Surname, University, Country Solicited review(s): Name Surname, University, Country Open review(s): Name
A conceptualization is a map from the problem domain into the representation. A conceptualization specifies:
Knowledge Sharing A conceptualization is a map from the problem domain into the representation. A conceptualization specifies: What sorts of individuals are being modeled The vocabulary for specifying
Cognitive modeling with conceptual spaces
Cognitive modeling with conceptual spaces Martin Raubal Department of Geography, University of California at Santa Barbara 5713 Ellison Hall, Santa Barbara, CA 93106, U.S.A. raubal@geog.ucsb.edu Abstract.
Knowledge Sharing. A conceptualization is a map from the problem domain into the representation. A conceptualization specifies:
Knowledge Sharing A conceptualization is a map from the problem domain into the representation. A conceptualization specifies: What sorts of individuals are being modeled The vocabulary for specifying
A spatial literacy initiative for undergraduate education at UCSB
A spatial literacy initiative for undergraduate education at UCSB Mike Goodchild & Don Janelle Department of Geography / spatial@ucsb University of California, Santa Barbara ThinkSpatial Brown bag forum
Description Logics. Foundations of Propositional Logic. franconi. Enrico Franconi
(1/27) Description Logics Foundations of Propositional Logic Enrico Franconi franconi@cs.man.ac.uk http://www.cs.man.ac.uk/ franconi Department of Computer Science, University of Manchester (2/27) Knowledge
Notes on Latent Semantic Analysis
Notes on Latent Semantic Analysis Costas Boulis 1 Introduction One of the most fundamental problems of information retrieval (IR) is to find all documents (and nothing but those) that are semantically
Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore
Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore GIS ( GEO GRAPHIC INFO RMATIO N SYSTEM) geospatial information system
GIS = Geographic Information Systems;
What is GIS GIS = Geographic Information Systems; What Information are we talking about? Information about anything that has a place (e.g. locations of features, address of people) on Earth s surface,
UBGI and Address Standards
Workshop on address standards UBGI and Address Standards 2008. 5.25 Copenhagen, Denmark Sang-Ki Hong Convenor, WG 10 1 Evolution of Geographic Information Visualization Feature (Contents) Context Accessibility
Mappings For Cognitive Semantic Interoperability
Mappings For Cognitive Semantic Interoperability Martin Raubal Institute for Geoinformatics University of Münster, Germany raubal@uni-muenster.de SUMMARY Semantic interoperability for geographic information
Using spatial-temporal signatures to infer human activities from personal trajectories on location-enabled mobile devices
Using spatial-temporal signatures to infer human activities from personal trajectories on location-enabled mobile devices Yingjie Hu 1, Wenwen Li 2, Krzysztof Janowicz 1, Kathleen Deutsch 1, Grant McKenzie
Section 2.1: Introduction to the Logic of Quantified Statements
Section 2.1: Introduction to the Logic of Quantified Statements In the previous chapter, we studied a branch of logic called propositional logic or propositional calculus. Loosely speaking, propositional
Lecture 4: Proposition, Connectives and Truth Tables
Discrete Mathematics (II) Spring 2017 Lecture 4: Proposition, Connectives and Truth Tables Lecturer: Yi Li 1 Overview In last lecture, we give a brief introduction to mathematical logic and then redefine
Extensions to the Logic of All x are y: Verbs, Relative Clauses, and Only
1/53 Extensions to the Logic of All x are y: Verbs, Relative Clauses, and Only Larry Moss Indiana University Nordic Logic School August 7-11, 2017 2/53 An example that we ll see a few times Consider the
Global Grids and the Future of Geospatial Computing. Kevin M. Sahr Department of Computer Science Southern Oregon University
Global Grids and the Future of Geospatial Computing Kevin M. Sahr Department of Computer Science Southern Oregon University 1 Kevin Sahr - November 11, 2013 The Situation Geospatial computing has achieved
An Ontology-based Framework for Modeling Movement on a Smart Campus
An Ontology-based Framework for Modeling Movement on a Smart Campus Junchuan Fan 1, Kathleen Stewart 1 1 Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, IA, 52242,
Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore
Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore Activitydevelop DIVERSITY IN NEW YO RK PL ACE NAMES What do place
Propositional Logic and Semantics
Propositional Logic and Semantics English is naturally ambiguous. For example, consider the following employee (non)recommendations and their ambiguity in the English language: I can assure you that no
Environmental Cognition and Perception I
Environmental Cognition and Perception I Review: Spatial Interaction and Spatial Behavior II - Individual travel behavior - Activity space - Mental maps How we perceive the environment Maps in the head
Today we begin the first technical topic related directly to the course that is: Equilibrium Carrier Concentration.
Solid State Devices Dr. S. Karmalkar Department of Electronics and Communication Engineering Indian Institute of Technology, Madras Lecture - 3 Equilibrium and Carrier Concentration Today we begin the
Propositional Logic: Logical Agents (Part I)
Propositional Logic: Logical Agents (Part I) This lecture topic: Propositional Logic (two lectures) Chapter 7.1-7.4 (this lecture, Part I) Chapter 7.5 (next lecture, Part II) Next lecture topic: First-order
BACK TO SCHO O L W ITH
Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore BACK TO SCHO O L W ITH GEO - L ITERACY Essays on Geo-Literacy For
Welcome to GST 101: Introduction to Geospatial Technology. This course will introduce you to Geographic Information Systems (GIS), cartography,
Welcome to GST 101: Introduction to Geospatial Technology. This course will introduce you to Geographic Information Systems (GIS), cartography, remote sensing, and spatial analysis through a series of
3D MAPS SCALE, ACCURACY, LEVEL OF DETAIL
26 th International Cartographic Conference August 25 30, 2013 Dresden, Germany 3D MAPS SCALE, ACCURACY, LEVEL OF DETAIL Prof. Dr. Temenoujka BANDROVA Eng. Stefan BONCHEV University of Architecture, Civil
LIN1032 Formal Foundations for Linguistics
LIN1032 Formal Foundations for Lecture 1 Albert Gatt Practical stuff Course tutors: Albert Gatt (first half) albert.gatt@um.edu.mt Ray Fabri (second half) ray.fabri@um.edu.mt Course website: TBA Practical
Improving Spatial Data Interoperability
Improving Spatial Data Interoperability A Framework for Geostatistical Support-To To-Support Interpolation Michael F. Goodchild, Phaedon C. Kyriakidis, Philipp Schneider, Matt Rice, Qingfeng Guan, Jordan
COMP219: Artificial Intelligence. Lecture 19: Logic for KR
COMP219: Artificial Intelligence Lecture 19: Logic for KR 1 Overview Last time Expert Systems and Ontologies Today Logic as a knowledge representation scheme Propositional Logic Syntax Semantics Proof
Curriculum Vitae. Dr. Danqing (Dana) Xiao. Ph.D. in Department of Geography, University of California Santa Barbara.
Curriculum Vitae Dr. Danqing (Dana) Xiao Personal Information Assistant Professor Department of Environmental, Geographical, and Geological Sciences (EGGS), Bloomsburg University of Pennsylvania Research
Your web browser (Safari 7) is out of date. For more security, comfort and. the best experience on this site: Update your browser Ignore
Your web browser (Safari 7) is out of date. For more security, comfort and lesson the best experience on this site: Update your browser Ignore Political Borders Why are the borders of countries located
COMP219: Artificial Intelligence. Lecture 19: Logic for KR
COMP219: Artificial Intelligence Lecture 19: Logic for KR 1 Overview Last time Expert Systems and Ontologies Today Logic as a knowledge representation scheme Propositional Logic Syntax Semantics Proof
Towards a better adoption of ISO/TC 211 standards: Courses on international standards in geomatics
Towards a better adoption of ISO/TC 211 standards: Courses on international standards in geomatics Dr. Thierry Badard Centre for Research in Geomatics (CRG) University Laval, Québec, Canada Thierry.Badard@scg.ulaval.ca
Gistat: moving towards a location information management system
Gistat: moving towards a location information management system (merging geographical, statistical and historical information) Pina Grazia Ticca Marco Ballin Istat - Italy Aguascalientes, Mexico 2-4 December
The Global Statistical Geospatial Framework and the Global Fundamental Geospatial Themes
The Global Statistical Geospatial Framework and the Global Fundamental Geospatial Themes Sub-regional workshop on integration of administrative data, big data and geospatial information for the compilation
Retrieval by Content. Part 2: Text Retrieval Term Frequency and Inverse Document Frequency. Srihari: CSE 626 1
Retrieval by Content Part 2: Text Retrieval Term Frequency and Inverse Document Frequency Srihari: CSE 626 1 Text Retrieval Retrieval of text-based information is referred to as Information Retrieval (IR)
Reducing Consumer Uncertainty
Spatial Analytics Reducing Consumer Uncertainty Eliciting User and Producer Views on Geospatial Data Quality Introduction Cooperative Research Centre for Spatial Information (CRCSI) in Australia Communicate
Understanding Geographic Information System GIS
Understanding Geographic Information System GIS What do we know about GIS? G eographic I nformation Maps Data S ystem Computerized What do we know about maps? Types of Maps (Familiar Examples) Street Maps
Reasoning. Inference. Knowledge Representation 4/6/2018. User
Reasoning Robotics First-order logic Chapter 8-Russel Representation and Reasoning In order to determine appropriate actions to take, an intelligent system needs to represent information about the world
Spatial Data Science. Soumya K Ghosh
Workshop on Data Science and Machine Learning (DSML 17) ISI Kolkata, March 28-31, 2017 Spatial Data Science Soumya K Ghosh Professor Department of Computer Science and Engineering Indian Institute of Technology,
The production and use of a hydrographic flow-direction network of surface waters. Rickard HALLENGREN, Håkan OLSSON and Erik SISELL, Sweden
The production and use of a hydrographic flow-direction network of surface waters Rickard HALLENGREN, Håkan OLSSON and Erik SISELL, Sweden Key words: hydrographic, flow-direction network, surface waters
This is why Esri is in business and how we look for great talent (data science or otherwise) accordingly. Esri focuses on mapping and data for
1 This is why Esri is in business and how we look for great talent (data science or otherwise) accordingly. Esri focuses on mapping and data for conservation, disaster aid and relief, climate change mitigation
Logic in Computer Science. Frank Wolter
Logic in Computer Science Frank Wolter Meta Information Slides, exercises, and other relevant information are available at: http://www.liv.ac.uk/~frank/teaching/comp118/comp118.html The module has 18 lectures.
Geospatial data integration and visualisation using Linked Data
Geospatial data integration and visualisation using Linked Data Weiming Huang weiming.huang@nateko.lu.se Ali Mansourian ali.mansourian@nateko.lu.se Lars Harrie lars.harrie@nateko.lu.se Abstract Geospatial
Many Ways to Name a Place
Your web browser (Safari 7) is out of date. For more security, comfort and Activityapply the best experience on this site: Update your browser Ignore Many Ways to Name a Place What are the names for the
Discrete Mathematics. Kenneth A. Ribet. January 31, 2013
January 31, 2013 A non-constructive proof Two classical facts are that π and e 2.71828... are irrational. Further, it is known that neither satisfies a quadratic equation x 2 + ax + b = 0 where a and b
GIS and Spatial Statistics: One World View or Two? Michael F. Goodchild University of California Santa Barbara
GIS and Spatial Statistics: One World View or Two? Michael F. Goodchild University of California Santa Barbara Location as attribute The data table Census summary table What value is location as an explanatory
Propositional Definite Clause Logic: Syntax, Semantics and Bottom-up Proofs
Propositional Definite Clause Logic: Syntax, Semantics and Bottom-up Proofs Computer Science cpsc322, Lecture 20 (Textbook Chpt 5.1.2-5.2.2 ) June, 6, 2017 CPSC 322, Lecture 20 Slide 1 Lecture Overview
Spatial Data Infrastructure Concepts and Components. Douglas Nebert U.S. Federal Geographic Data Committee Secretariat
Spatial Data Infrastructure Concepts and Components Douglas Nebert U.S. Federal Geographic Data Committee Secretariat August 2009 What is a Spatial Data Infrastructure (SDI)? The SDI provides a basis for
Minnesota Transportation Museum
Minnesota Transportation Museum Minnesota Social Studies s Alignment Second Grade 1 Code Benchmark 1. Citizenship and Government 1. Civic Skills. Civic Values and Principles of Democracy 4. Governmental
COSE212: Programming Languages. Lecture 1 Inductive Definitions (1)
COSE212: Programming Languages Lecture 1 Inductive Definitions (1) Hakjoo Oh 2017 Fall Hakjoo Oh COSE212 2017 Fall, Lecture 1 September 4, 2017 1 / 9 Inductive Definitions Inductive definition (induction)
Contents... GIS Approach. 4D Geo-referenced Database Approach for GIS. G IS Specific GIS Applications. FIG Working Week 2004.
FIG Working Week 2004 4D Geo-referenced Database Approach for GIS Components of GIS GIS Approach How to Produce Maps Contents... Everything is moving with Earth by Time Why 4D Geo-referenced Database Design
Calculus: What is a Limit? (understanding epislon-delta proofs)
Calculus: What is a Limit? (understanding epislon-delta proofs) Here is the definition of a limit: Suppose f is a function. We say that Lim aa ff() = LL if for every εε > 0 there is a δδ > 0 so that if
Semantic Granularity in Ontology-Driven Geographic Information Systems
Semantic Granularity in Ontology-Driven Geographic Information Systems Frederico Fonseca a Max Egenhofer b Clodoveu Davis c Gilberto Câmara d a School of Information Sciences and Technology Pennsylvania
USGIF Essential Body of Knowledge Competency Areas
GEOINT Job/Practice Analysis USGIF, in consultation with psychometric consultants and the GEOINT community, executed a job/practice analysis to identify common competencies within the GEOINT profession.
Grade 4 Benchmarks. Benchmark Concepts Skills Essential Question(s)
**Be aware of the use of and & or in the benchmark language related to Canada and Mexico; sometimes students may look at the US and one of our neighboring countries and other times students need to study
Peter Wood. Department of Computer Science and Information Systems Birkbeck, University of London Automata and Formal Languages
and and Department of Computer Science and Information Systems Birkbeck, University of London ptw@dcs.bbk.ac.uk Outline and Doing and analysing problems/languages computability/solvability/decidability
Yingjie Hu. Research Interests Geographic Information Science, Geospatial Semantics, Information Value, Data Mining, Spatial Data infrastructures
Assistant Professor Department of Geography University of Tennessee, Knoxville Yingjie Hu Office: 206A Burchfiel Geography Bldg. Tel: (865) 974-5343 Email: yhu21@utk.edu Research Interests Geographic Information
A GIS helps you answer questions and solve problems by looking at your data in a way that is quickly understood and easily shared.
WHAT IS GIS? A geographic information system (GIS) integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. GIS allows