Geographic knowledge infrastructure : applications to territorial intelligence and smart cities / Robert Laurini
- Author:
- Laurini, Robert
- Published:
- London : ISTE Press ; Oxford : Elsevier, 2017.
- Physical Description:
- 1 online resource : illustrations
- Access Online:
- ezaccess.libraries.psu.edu
- Contents:
- Machine generated contents note: ch. 1 From Geodata to Geographic Knowledge -- 1.1.A Rapid History of Urban Planning and Information Technology -- 1.2.Territorial intelligence, smart cities and smart planning -- 1.2.1.Smart cities -- 1.2.2.Territorial intelligence -- 1.2.3.Smart Urban Planning -- 1.3.Data acquisition sensors -- 1.3.1.Digital sensors -- 1.3.2.Citizens as sensors -- crowdsourcing -- 1.4.About reasoning -- 1.4.1.Spatial reasoning -- 1.4.2.Geographic reasoning -- 1.5.Promises of geographic knowledge -- 1.6.Conclusion: advocacy for geographic knowledge infrastructures -- ch. 2 Knowledge Representation -- 2.1.Automated reasoning -- 2.1.1.Data, information and knowledge -- 2.1.2.Vision of Turban/Aaronson -- 2.2.Logical formalisms -- 2.2.1.Propositional logic -- 2.2.2.Predicate logic -- 2.2.3.Descriptive logics -- 2.2.4.Fuzzy sets and logics -- 2.2.5.About Lewis Carroll's example -- 2.2.6.Logics and space -- 2.3.RDF (Resource Description Framework) -- 2.4.Rule modeling -- 2.4.1.Rules and classical logics -- 2.4.2.Decision trees and tables -- 2.4.3.Rules and fuzzy logic -- 2.4.4.From business rules to geographic rules -- 2.4.5.Generic model of rules -- 2.5.About mathematical models -- 2.6.Case-based reasoning -- 2.7.Conclusion: what is special for geographic knowledge? -- ch. 3 Towards Geographic Knowledge Systems -- 3.1.Lessons learnt from GIS -- 3.1.1.About the mathematical visions of the world -- 3.1.2.About geo-objects modeling and storing -- 3.1.3.About data quality and homologies -- 3.1.4.About multiple representations and granularity of interest -- 3.1.5.Requirements for geographic knowledge systems -- 3.2.GKS structure -- 3.3.Towards the integration of external knowledge -- 3.4.Prolegomena and principles -- 3.4.1.Prolegomena -- 3.4.2.Principles -- 3.5.About quality of geographic knowledge bases -- 3.6.About multimedia knowledge -- 3.7.First conclusion on GKS -- ch. 4 Geographic Objects -- 4.1.About the semantics of geographic objects -- 4.1.1.Categories or classes -- 4.1.2.Place names and identifiers -- 4.1.3.Geometric types -- 4.2.From lines to ribbons -- 4.2.1.Rectangular ribbons -- 4.2.2.Ribbons and taenic transformation -- 4.2.3.Loose ribbons -- 4.3.Mutation of object geometric types -- 4.3.1.General process (GRD process) -- 4.3.2.Rules of visual acuity applied to geographic objects -- 4.4.Fuzzy geographic objects -- 4.5.About altitude -- 4.5.1.Irregular points -- 4.5.2.Gridded points -- 4.5.3.Contour level curves -- 4.6.Continuous fields -- 4.7.Quality and geometric homology relations -- 4.7.1.Quality control based on rules -- 4.7.2.Geometric homology -- 4.8.Geographic objects and projects -- 4.9.Final remarks concerning geographic objects -- ch. 5 Geographic Relations -- 5.1.Spatial operations -- 5.1.1.Minimum bounding rectangle -- 5.1.2.Centroid -- 5.1.3.Buffer zones -- 5.1.4.Union, intersection and difference -- 5.1.5.Convex hull -- 5.2.Spatial relations -- 5.2.1.Topological relations -- 5.2.2.Projective and other spatial relations -- 5.2.3.Rectangle relations -- 5.3.Characteristics of spherical spatial relations -- 5.3.1.Projective relations -- 5.3.2.Projective relations for areas -- 5.4.Spatial relations in urban space -- 5.4.1.Other binary topological relations -- 5.4.2.Relations between urban features and places -- 5.5.Ribbon operations and relations -- 5.5.1.Simple operations and relations -- 5.5.2.Orientation -- 5.5.3.3D Relations between ribbons -- 5.5.4.Chaining ribbons -- 5.6.Mutation of topological relations according to the granularity of interest -- 5.6.1.Example of topological mutation due to granularity of interest -- 5.6.2.Mutation table of Egenhofer relations -- 5.6.3.Mutation of ribbon relations -- 5.7.Other geographic relations -- 5.8.Conclusion regarding geographic relations -- ch. 6 Geographic Ontologies -- 6.1.Introduction -- 6.2.Generalities about ontologies -- 6.2.1.Role and definition -- 6.2.2.Categories of ontologies -- 6.2.3.Ontology approaches -- 6.2.4.Ontology examples -- 6.2.5.Ontology components -- 6.2.6.Ontology languages -- 6.2.7.Conventional ontologies applied to geography -- 6.3.Towntology: ontologies for urban planning -- 6.3.1.Genesis and objectives of the towntology project -- 6.3.2.Lessons learnt from the towntology project -- 6.4.Characteristics of geographic ontologies -- 6.4.1.Space representation and management -- 6.4.2.Links with linguistics -- 6.5.Examples of geographic ontologies -- 6.6.Fusioning ontologies -- 6.7.Conclusion and challenges regarding geographic ontologies -- ch. 7 Complex Geographic Objects and Structures -- 7.1.Simple collections -- 7.2.Ribbon graphs and networks -- 7.3.Tessellations -- 7.3.1.Hierarchical tessellations -- 7.3.2.Reduction of tessellations -- 7.4.Shape grammars and applications to geographic objects -- 7.4.1.Introduction to shape grammars -- 7.4.2.Applications to landscape and town planning -- 7.5.Complex geographic objects and their relations -- 7.6.Conclusion -- ch. 8 Gazetteers and Multilingualism -- 8.1.Generalities -- 8.2.Examples -- 8.2.1.Simple gazetteer -- 8.2.2.Gazetteer As An Index for A Map (Street Directory) -- 8.2.3.Gazetteer for a local post-office -- 8.2.4.Gazetteer for hydrology -- 8.2.5.Gazetteer for the history of a place -- 8.2.6.Gazetteer covering several countries -- 8.3.Existing systems -- 8.3.1.GeoNames -- 8.3.2.GeoSPARQL -- 8.3.3.OntoGazetteer -- 8.3.4.Metagazetteer -- 8.4.Inference rules for matching geographic ontologies and gazetteers in different languages -- 8.4.1.Languages -- 8.4.2.Homology relation for toponyms -- 8.4.3.About exonyms and endonyms -- 8.4.4.Matching two geographic ontologies each in different languages -- 8.4.5.Homologous geographic objects -- 8.5.Enriching geographic knowledge bases by rules -- 8.5.1.Inferring geometry -- 8.5.2.From homologous geometry to homologous objects -- 8.5.3.Inferring ontological relations -- 8.6.Conclusion -- ch. 9 Geographic Knowledge Discovery and Data Mining -- 9.1.Introduction to data mining -- 9.1.1.KDD process -- 9.1.2.Association rules in non-spatial databases -- 9.2.Elements of spatial data mining -- 9.2.1.Co-location patterns -- 9.2.2.Association rules extracted from spatial data mining -- 9.3.Conclusion -- ch. 10 Geographic Applicative Rules -- 10.1.About rules in information technology -- 10.2.Introductory example regarding street naming -- 10.3.Geographic knowledge and reasoning -- 10.3.1.General information -- 10.3.2.Geographic knowledge bases -- 10.4.Study of the semantics of the geographic rules -- 10.4.1.Global rules -- 10.4.2.Local rules -- 10.4.3.Low level or generic rules -- 10.4.4.Rules and plurality of places -- 10.4.5.Rules and logics of stakeholders -- 10.4.6.Handling exceptions -- 10.5.Toward applicative geographic rules modeling -- 10.5.1.General considerations -- 10.5.2.Outline of a model -- 10.5.3.Rules Indexing -- 10.5.4.Requirements for a rule language -- 10.6.Conclusion about applicative geographic rules -- ch. 11 Geovisualization and Chorems -- 11.1.Graphics semiology -- 11.2.From vision analytics to geovisualization -- 11.2.1.Visual analytics -- recommendations -- 11.2.2.Definition of geovisualization -- 11.2.3.Cartograms -- 11.2.4.Examples in geovisualization -- 11.2.5.How to lie with maps? -- 11.2.6.Visual DB access -- 11.3.Chorems -- 11.3.1.Elementary chorems -- 11.3.2.Approaches, manual versus automatic? -- 11.3.3.Chorems as a new way to access geographic databases and knowledge bases -- 11.3.4.Final remarks regarding chorems -- 11.4.Dashboards for smart cities -- 11.5.Conclusions -- ch. 12 GKS: Querying and Interoperability -- 12.1.Geographic queries -- 12.1.1.Textual queries -- 12.1.2.Visual languages and queries -- 12.2.Geographic knowledge bases interoperability -- 12.2.1.Generalities about interoperability -- 12.2.2.Interoperability of databases based on ontologies -- 12.2.3.Federating tessellations -- 12.2.4.Federating networks -- 12.2.5.Federating GKS -- 12.3.Conclusion -- ch. 13 Conclusion: Knowledge as Infrastructure for Smart Governance -- 13.1.Business intelligence -- 13.2.GeoSpatial Business Intelligence or geo-intelligence -- 13.3.Territorial intelligence -- 13.3.1.Public participation -- 13.3.2.Smart people and smart governance -- 13.3.3.Smart people involvement -- 13.4.Knowledge as infrastructure for smart governance -- 13.4.1.Geographic knowledge organization -- 13.4.2.Geographic knowledge accessibility -- 13.4.3.Categories of geographic knowledge -- 13.4.4.Technology and sociological watching -- 13.4.5.Back on external knowledge -- 13.4.6.Geographic knowledge on the move -- 13.5.Conclusion, from knowledge to wisdom.
- Summary:
- Geographic Knowledge Engineering: Applications to Territorial Intelligence and Smart Cities studies the specific nature of geographic knowledge and the structure of geographic knowledge bases. Geographic relations, ontologies, gazetteers and rules are detailed as the basic components of such bases, and these rules are defined to develop our understanding of the mechanisms of geographic reasoning. The book examines various problems linked to geovisualization, chorems, visual querying and interoperability to shape knowledge infrastructure for smart governance.
- Subject(s):
- ISBN:
- 9780081023525 (electronic bk.)
0081023529 (electronic bk.)
9781785482434 - Bibliography Note:
- Includes bibliographical references and index.
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