Universal Geospatial Ontology for the Semantic Interoperability of Data

2014 ◽  
pp. 1-27
Author(s):  
Tarek Sboui ◽  
Yvan Bédard
Keyword(s):  
Systematic Approach ◽  
Semantic Interoperability ◽  
Data Models ◽  
Geospatial Data ◽  
Data Usage ◽  
Geospatial Ontology

Ontologies have been used to support the interoperability of geospatial data by overcoming semantic problems related to semantic heterogeneities and to differences in data usage contexts. Ideally, to solve semantic heterogeneities, the data models involved in the interoperability process could be enriched, and the relationships between their elements could be defined based on a universal geospatial ontology. However, such ontology would encounter difficulties in achieving an efficient interoperability. This chapter aims to argue that universal ontology-based interoperability remains vulnerable to the risks of uncertain meaning of geospatial data that may go unnoticed during the interoperability process. The chapter discusses these risks and proposes a systematic approach to better support users dealing with them. The proposed approach identifies the risks, assesses their severity, and helps users to make decisions about them.

Data Models and Query Languages for Linked Geospatial Data

2012 ◽  
pp. 290-328 ◽  
Author(s):  
Manolis Koubarakis ◽  
Manos Karpathiotakis ◽  
Kostis Kyzirakos ◽  
Charalampos Nikolaou ◽  
Michael Sioutis
Keyword(s):  
Query Languages ◽  
Data Models ◽  
Geospatial Data

The Semantic Interoperability Centre Europe

2011 ◽  
pp. 144-161 ◽  
Author(s):  
Aldo Laudi
Keyword(s):  
European Commission ◽  
Public Administration ◽  
Semantic Interoperability ◽  
Data Models ◽  
Collaborative Approach ◽  
Joint Effort ◽  
Community Based ◽  
Guiding Principles ◽  
High Level

This chapter presents a case of a centralised and collaborative approach to interoperability in public administration: SEMIC.EU, the Semantic Interoperability Centre Europe.SEMIC.EU is a horizontal measure of the European Commission implemented with the primary purpose of enhancing semantic interoperability in public administrations and projects across Europe. The European Commission service calls on projects and individuals alike to share their solutions for semantic interoperability (so called “assets”) or to find them through a joint effort. A standardised clearing process governs the evolution of the contributed data models, XML schemas, code lists and ontologies and gives guidance to potential re-users.The chapter argues that especially at a high level of administration like the European one, the guiding principles for common solutions to semantic interoperability coordination must be. exchange of existing practices and community-based negotiation of purposes and meanings.

A Systematic Approach for Managing the Risk Related to Semantic Interoperability between Geospatial Datacubes

2010 ◽  
Vol 1 (2) ◽  
pp. 20-41 ◽  
Author(s):  
Tarek Sboui ◽  
Mehrdad Salehi ◽  
Yvan Bédard
Keyword(s):  
Decision Support ◽  
Business Intelligence ◽  
Systematic Approach ◽  
Semantic Interoperability ◽  
General Level ◽  
Semantic Heterogeneity ◽  
Geographic Knowledge ◽  
Transactional Databases ◽  
The Subject ◽  
Geographic Knowledge Discovery

Geospatial datacubes are the database backend of novel types of spatiotemporal decision-support systems employed in large organizations. These datacubes extend the datacube concept underlying the field of Business Intelligence (BI) into the realm of geospatial decision-support and geographic knowledge discovery. The interoperability between geospatial datacubes facilitates the reuse of their content. Such interoperability, however, faces risks of data misinterpretation related to the heterogeneity of geospatial datacubes. Although the interoperability of transactional databases has been the subject of several research works, no research dealing with the interoperability of geospatial datacubes exists. In this paper, the authors support the semantic interoperability between geospatial datacubes and propose a categorization of semantic heterogeneity problems that may occur in geospatial datacubes. Additionally, the authors propose an approach to deal with the related risks of data misinterpretation, which consists of evaluating the fitness-for-use of datacubes models, and a general framework that facilitates making appropriate decisions about such risks. The framework is based on a hierarchical top-down structure going from the most general level to the most detailed level, showing the usefulness of the proposed approach in environmental applications.

scholarly journals A systematic approach to mapping longitudinal data usage: Reflections on tracking Millennium Cohort Study activity

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1559
Author(s):  
Dylan Kneale ◽  
Praveetha Patalay ◽  
James Thomas ◽  
Meena Khatwa ◽  
Claire Stansfield ◽  
...  
Keyword(s):  
Cohort Study ◽  
Systematic Approach ◽  
Survey Design ◽  
Overweight And Obesity ◽  
Millennium Cohort Study ◽  
Systematic Review Methods ◽  
Data Usage ◽  
Study Activity ◽  
Parental Reports ◽  
Areas Of Interest

Background: The Millennium Cohort Study is the youngest of the UK’s four national birth cohort studies, but the only study (to our knowledge) where a systematic approach to exploring data usage has been undertaken. Methods: In this paper we: (i) explore previous exercises and provide justification for our approach; (ii) share headline findings of our research, (iii) outline the challenges of intersecting systematic review methods with survey design methods; and (iv) discuss the implications for future survey design as well as for future exercises tracking survey data usage. All of the results were obtained through undertaking systematic searches across 30 databases which generated over 4000 results. We then searched these records, first on title and abstract and then on the full text and extracted data on studies that fell within our specific areas of interest. Results: A total of 481 studies were identified as using MCS data in novel analyses. Among these studies, measures that have been collected across sweeps—diet, BMI, SDQ and screen time—are all comparatively well used. Data that were collected from the child’s own reports (e.g. friendships and feelings) have seldom been utilised in comparison to data collected through parental reports and using validated tools (e.g. SDQ). Imposing thresholds on data was found to be problematic in some cases, for example for BMI, where a number of different thresholds for overweight and obesity were in use. The use of different thresholds can lead to substantial differences in the results obtained. Conclusions: Longitudinal consistency in measures is key to identifying change over time, and the review helped map the degree of consistency in measures, and their utility. The findings shaped decisions around inclusion of variables in MCS7 (age 17 years), as well as the way in which existing data were deposited.

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