{"title":"Reviewing the Qualifiers of Imperfection in Geographic Information","authors":"Giovanni Fusco, A. Tettamanzi","doi":"10.1002/9781119507284.ch9","DOIUrl":"https://doi.org/10.1002/9781119507284.ch9","url":null,"abstract":"This chapter argues that the qualifiers of imperfection in geographic information can be reviewed in the highly formalized framework of AGM belief revision in knowledge engineering. It tackles the belief revision methods used for imperfect information, especially Bayesian revision (Bayes' theorem and Jeffrey's rule) and the alternatives in non‐probabilistic formalisms (Dempster's rule of combination in evidence theory, possibilistic conditioning in possibility theory). The chapter shows how the theories about the imperfect representation of spatial objects can be implemented from an operational point of view, to solve the issue of belief revision on available information. It also shows how revision operations may create imperfections in the set of beliefs. Afterward, the chapter considers the more general case in which clauses use from the very beginning formalisms employed for uncertain knowledge, and how revision operations may take advantage of these formalisms to reach revised and consistent states of uncertain beliefs.","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132775628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Imperfection of Geographic Information: Concepts and Terminologies","authors":"R. Devillers, É. Desjardin, Cyril de Runz","doi":"10.1002/9781119507284.ch2","DOIUrl":"https://doi.org/10.1002/9781119507284.ch2","url":null,"abstract":"","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"45 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114092028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Clément Iphar, Benjamin Costé, A. Napoli, C. Ray, R. Devillers
{"title":"Integrity and Trust of Geographic Information","authors":"Clément Iphar, Benjamin Costé, A. Napoli, C. Ray, R. Devillers","doi":"10.1002/9781119507284.ch4","DOIUrl":"https://doi.org/10.1002/9781119507284.ch4","url":null,"abstract":"This chapter presents the concepts of integrity and trust in the context of the assessment of spatial data quality. It describes approaches that can be used to assess the internal and external quality of geolocated information produced by mobile objects. The first step, a bottom‐up approach, suggests assessing the integrity of information based on the database structure. The second step, a top‐down approach, suggests assessing the trust that should be given to information based on the measures that can be applied to a dataset. Taking the example of geolocation data, in particular, in the context of maritime navigation, the chapter demonstrates how these concepts and methods may be used to define the integrity and trust of the data produced by a vessel monitoring system. Characterizing the integrity and trust of geographic information makes it possible to provide better information about the uncertainty of the data used in decision‐making processes in maritime safety.","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126049780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Representing Diagrams of Imperfect Geographic Objects","authors":"F. Pinet, Cyril de Runz","doi":"10.1002/9781119507284.ch6","DOIUrl":"https://doi.org/10.1002/9781119507284.ch6","url":null,"abstract":"","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115320542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reasoning in Modal Logic for Uncertain Data","authors":"E. Gavignet, N. Cullot","doi":"10.1002/9781119507284.ch8","DOIUrl":"https://doi.org/10.1002/9781119507284.ch8","url":null,"abstract":"","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124819709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Imperfection and Geographic Information","authors":"F. Pinet, M. Batton-Hubert, É. Desjardin","doi":"10.1002/9781119507284.ch1","DOIUrl":"https://doi.org/10.1002/9781119507284.ch1","url":null,"abstract":"This chapter clarifies the terminology and the definitions assigned to various concepts that revolve around the imperfection and uncertainty of geographic information. These terms have been used in different ways over the years. The chapter introduces the different parts of this book while also revealing which issues they tackle. The first part of the book describes the foundations and main concepts related to the imperfection of geographic data. The issue is to shed light on and provide a summary of terminologies, the origins of imperfections, as well as the concepts of quality, integrity, and confidence. The second part of the book tackles the main representations of imperfection and their applications for geographic information. The final part of the book introduces a few data processing and reasoning systems that involve spatial objects. Imperfection is considered in relation to our knowledge about the objects.","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122954986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Formalisms and Representations of Imperfect Geographic Objects","authors":"M. Batton-Hubert, F. Pinet","doi":"10.1002/9781119507284.ch5","DOIUrl":"https://doi.org/10.1002/9781119507284.ch5","url":null,"abstract":"This chapter first shows some examples of geographic data and spatial information to illustrate where and how imperfection takes shape. It then presents the main mathematical tools used to manipulate those two concepts, i.e. imperfection meant as partial knowledge and uncertainty meant as correspondence to reality, besides introducing the ways in which a geometric and topological object evolves. In the context of spatial analysis, it is often necessary to simultaneously combine attribute measures of a geographic object and geometric measures of the object through its adopted geometric model (vector or raster). Thus, it is necessary to introduce combination operators that imply membership or possibility distribution functions which characterize the imperfection of the fuzzy object. After recontextualizing the set operations defined over these fuzzy sets, the chapter also presents the mathematical functions that make it possible to define some set operations for keeping these membership properties.","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116624640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Features of Decision Aid and Analysis Processes in Geography: How to Grasp Complexity, Uncertainty, and Risks?","authors":"M. Merad","doi":"10.1002/9781119507284.ch10","DOIUrl":"https://doi.org/10.1002/9781119507284.ch10","url":null,"abstract":"","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114077782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jean-Michel Follin, Jean-François Girres, Ana-Maria Olteanu-Raimond, D. Sheeren
{"title":"The Origins of Imperfection in Geographic Data","authors":"Jean-Michel Follin, Jean-François Girres, Ana-Maria Olteanu-Raimond, D. Sheeren","doi":"10.1002/9781119507284.ch3","DOIUrl":"https://doi.org/10.1002/9781119507284.ch3","url":null,"abstract":"","PeriodicalId":240032,"journal":{"name":"Geographic Data Imperfection 1","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116955268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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