Geospatial Reasoning With Open Data

Geospatial data is data about objects, events, or phenomena that have a location on the surface of the earth, including location information (usually coordinates on the earth), attribute information (the characteristics of the object, event, or phenomena concerned), and often also temporal information (the time or life span at which the location and attributes exist). In this chapter, we discuss the ways in which geospatial reasoning has been applied to open data. We define geospatial reasoning as both reasoning about the location of objects on the earth (e.g., relating to inference of spatial relationships) and reasoning about geospatial data (e.g., relating to the attributes of data that is geospatial in nature). We then present two case studies to illustrate the use of geospatial reasoning with open data: (1) the use of fuzzy reasoning for map buffering and (2) methods for automatically learning nonclassical ontologies from geospatial data (data driven ontologies).

[1]  Stefano Borgo,et al.  A formal ontological perspective on the behaviors and functions of technical artifacts , 2008, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[2]  Dieter Fensel,et al.  Knowledge Engineering: Principles and Methods , 1998, Data Knowl. Eng..

[3]  Eva Klien,et al.  Ontology‐based retrieval of geographic information , 2006, Int. J. Geogr. Inf. Sci..

[4]  Sandro Rama Fiorini,et al.  An approach for grounding ontologies in raw data using foundational ontology , 2013, Inf. Syst..

[5]  Glen Hart,et al.  Geospatial semantics and linked spatiotemporal data - Past, present, and future , 2012, Semantic Web.

[6]  Paulo Cesar G. da Costa,et al.  PR-OWL: A Framework for Probabilistic Ontologies , 2006, FOIS.

[7]  Eliseo Clementini,et al.  Qualitative Representation of Positional Information , 1997, Artif. Intell..

[8]  Jo Wood,et al.  Where is Helvellyn? Fuzziness of multi‐scale landscape morphometry , 2004 .

[9]  M. Thonnat,et al.  Symbol Grounding for Semantic Image Interpretation: From Image Data to Semantics , 2005, Tenth IEEE International Conference on Computer Vision Workshops (ICCVW'05).

[10]  Miriam Baglioni,et al.  Building Geospatial Ontologies from Geographical Databases , 2007, GeoS.

[11]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[12]  Francesca A. Lisi,et al.  Nonmonotonic Onto-Relational Learning , 2009, ILP.

[13]  Bernd Neumann,et al.  On scene interpretation with description logics , 2006, Image Vis. Comput..

[14]  Mark Gahegan,et al.  Proximity Operators for Qualitative Spatial Reasoning , 1995, COSIT.

[15]  Reinhard Moratz,et al.  Spatial reasoning with augmented points: Extending cardinal directions with local distances , 2012, J. Spatial Inf. Sci..

[16]  Ronald A. Keele,et al.  Using Dynamic Bayesian Networks for Investigating the Impacts of Extreme Events , 2012 .

[17]  Barry Bitters,et al.  Spatial Relationship Networks: Network Theory Applied to GIS Data , 2009 .

[18]  Anthony G. Cohn,et al.  Qualitative Spatial Representation and Reasoning: An Overview , 2001, Fundam. Informaticae.

[19]  Jiming Liu,et al.  A Method of Spatial Reasoning Based on Qualitative Trigonometry , 1998, Artif. Intell..

[20]  Estevam R. Hruschka,et al.  Toward an Architecture for Never-Ending Language Learning , 2010, AAAI.

[21]  C. Tomlin.  Geographic information systems and cartographic modeling , 1990 .

[22]  Farhad Samadzadegan,et al.  Developing a Novel Method for Road Hazardous Segment Identification Based on Fuzzy Reasoning and GIS , 2012 .

[23]  Chris Cornelis,et al.  Fuzzy region connection calculus: An interpretation based on closeness , 2008, Int. J. Approx. Reason..

[24]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[25]  Paul Krause,et al.  Bayesian Networks for the management of greenhouse gas emissions in the British agricultural sector , 2012, Environ. Model. Softw..

[26]  Z. Pawlak.  Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[27]  Michael F. Worboys,et al.  Nearness relations in environmental space , 2001, Int. J. Geogr. Inf. Sci..

[28]  Wang-Kun Chen,et al.  A fuzzy intelligent decision support system for typhoon disaster management , 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

[29]  David M. Mark,et al.  Natural-Language Spatial Relations Between Linear and Areal Objects: The Topology and Metric of English-Language Terms , 1998, Int. J. Geogr. Inf. Sci..

[30]  Deborah L. McGuinness,et al.  Ontologies Come of Age , 2003, Spinning the Semantic Web.

[31]  Stephan Winter,et al.  The elements of probabilistic time geography , 2011, GeoInformatica.

[32]  Steffen Staab,et al.  Ontology Learning for the Semantic Web , 2002, IEEE Intell. Syst..

[33]  Anthony G. Cohn,et al.  Qualitative Spatial Representation and Reasoning with the Region Connection Calculus , 1997, GeoInformatica.

[34]  Anthony G. Cohn,et al.  Towards an Architecture for Cognitive Vision Using Qualitative Spatio-temporal Representations and Abduction , 2003, Spatial Cognition.

[35]  Hung T. Nguyen,et al.  On robustness of fuzzy logics , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[36]  Andrew U. Frank,et al.  Tiers of ontology and consistency constraints in geographical information systems , 2001, Int. J. Geogr. Inf. Sci..

[37]  M. Egenhofer.  Categorizing Binary Topological Relations Between Regions, Lines, and Points in Geographic Databases , 1998 .

[38]  Didier G. Leibovici,et al.  Discovering Order in Chaos: Using a Heuristic Ontology to Derive Spatio-Temporal Sequences for Cadastral Data , 2015, Spatial Cogn. Comput..

[39]  Adam Pease,et al.  Towards a standard upper ontology , 2001, FOIS.

[40]  Oliver Kutz,et al.  Natural Language Meets Spatial Calculi , 2008, Spatial Cognition.

[41]  Amitabha Mukerjee,et al.  A Qualitative Model for Space , 1990, AAAI.

[42]  Philip James,et al.  Orchestration of Grid-Enabled Geospatial Web Services in Geoscientific Workflows , 2010, IEEE Transactions on Automation Science and Engineering.

[43]  Thomas Blaschke,et al.  Ontology-Based Classification of Building Types Detected from Airborne Laser Scanning Data , 2014, Remote. Sens..

[44]  Werner Kuhn,et al.  Ontology-based discovery of geographic information services - An application in disaster management , 2006, Comput. Environ. Urban Syst..

[45]  Paulo Cesar G. da Costa,et al.  Envisioning Uncertainty in Geospatial Information , 2007, BMA.

[46]  Jens Lehmann,et al.  Concept learning in description logics using refinement operators , 2009, Machine Learning.

[47]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[48]  Christian Freksa,et al.  Qualitative spatial reasoning using orientation, distance, and path knowledge , 2004, Applied Intelligence.

[49]  Deborah L. McGuinness,et al.  OWL Web ontology language overview , 2004 .

[50]  Hans W. Guesgen,et al.  Buffering Fuzzy Maps in GIS , 2003, Spatial Cogn. Comput..

[51]  Guoray Cai,et al.  Contextualization of Geospatial Database Semantics for Human–GIS Interaction , 2007, GeoInformatica.

[52]  Eliseo Clementini,et al.  A Reasoning System of Ternary Projective Relations , 2010, IEEE Transactions on Knowledge and Data Engineering.

[53]  Christian Freksa,et al.  Using Orientation Information for Qualitative Spatial Reasoning , 1992, Spatio-Temporal Reasoning.

[54]  Alia I. Abdelmoty,et al.  Ontology-Based Spatial Query Expansion in Information Retrieval , 2005, OTM Conferences.

[55]  Laura Díaz,et al.  Service-oriented applications for environmental models: Reusable geospatial services , 2010, Environ. Model. Softw..

[56]  Jens Lehmann,et al.  Pattern Based Knowledge Base Enrichment , 2013, SEMWEB.

[57]  Martha Palmer,et al.  Verb Semantics and Lexical Selection , 1994, ACL.

[58]  Jens Lehmann,et al.  Class expression learning for ontology engineering , 2011, J. Web Semant..

[59]  B. Bennett.  What is a Forest? On the Vagueness of Certain Geographic Concepts , 2001 .

[60]  Jens Lehmann,et al.  Universal OWL Axiom Enrichment for Large Knowledge Bases , 2012, EKAW.

[61]  Hans W. Guesgen,et al.  Fuzzy Reasoning about Geographic Regions , 2005 .

[62]  Natasha Alechina,et al.  The Logic of NEAR and FAR , 2013, COSIT.

[63]  Umberto Straccia,et al.  Fuzzy Ontology Representation using OWL 2 , 2010, Int. J. Approx. Reason..

[64]  Johanna Völker,et al.  Statistical Schema Induction , 2011, ESWC.

[65]  Robert G. Raskin,et al.  Knowledge representation in the semantic web for Earth and environmental terminology (SWEET) , 2005, Comput. Geosci..

[66]  Boyan Brodaric,et al.  Finding Science with Science: Evaluating a Domain and Scientific Ontology User Interface for the Discovery of Scientific Resources , 2013, Trans. GIS.

[67]  Marcin Paprzycki,et al.  Fuzzy spatial relationships and mobile agent technology in geospatial information systems , 2002 .