Nathalie Abadie

Specifications for User Generated Spatial Content

This paper addresses the issue of quality in the context of collaborative edition of spatial content. The overall approach is grounded on the definition of explicit and adequate specifications for such content, i.e. the data model, the conceptual model, conventions for data acquisition, possible integrity constraints, possible relationships with external reference data. Explicit specifications could be processed to automatically check when different users simultaneously contribute on the same area. Their definition requires expertness, firstly, to ensure spatial content consistency and, secondly, to establish relevant relationships with external reference data. Designing these specifications is not an easy task for contributors. Hence, the focus of this paper is to assist them in this task. We propose a generic process to automatically produce specification items such as feature types, attribute types, and relationship types, including possible relationship types with external reference data from a set of keywords. It exploits information from two different kinds of existing contents: user generated content (like Wikipedia) and more conventional content (like WordNet and NMA databases). It has been applied to keywords found in existing user generated spatial contents.

Ontology-Based Formal Specifications for User-Friendly Geospatial Data Discovery

Nowadays, a huge amount of geodata is available. In this context, efficient discovery and retrieval of geographic data is a key issue to assess their fitness for use and optimal reuse. Such processes are mainly based on metadata. Over the last decade, standardization efforts have been made by the International Standard Organization (ISO) and the Open Geospatial Consortium (OGC) in the field of syntactic interoperability between geographic information components. Among existing standards, ISO-19115 standard provides an abstract specification of metadata for geospatial data discovery and exploration, ISO-19110 defines feature catalogues, and ISO-19131 defines data product specifications. Yet, information provided by these standardized metadata is not always formalized enough to enable efficient discovery, understanding and comparison of available datasets. Notably, information regarding geodata capture rules can be represented only through free text into the standard metadata (ISO 19131).More generally, geospatial database capture specifications are a very complex but very rich source of knowledge about geospatial data. They could be used with benefits in geospatial data discovery process if they would be represented in a more formal way than in existing ISO standards. In this context, we propose a model to formalize geospatial databases capture specifications. Firstly, we extend existing standards to represent information that was insufficiently formalized. Second, we propose an OWL representation of our global model. This ontological approach enables to overcome the limitations related to string-based queries and to provide efficient access to data capture information. Finally, we implement this model as a Web application allowing users to discover the available geospatial data and to access to their specifications through a user-friendly interface.

An Adaptive Approach for Interlinking Georeferenced Data

The resources published on the Web of data are often described by spatial references such as coordinates. The common data linking approaches are mainly based on the hypothesis that spatially close resources are more likely to represent the same thing. However, this assumption is valid only when the spatial references that are compared have been produced with the same positional accuracy, and when they actually represent the same spatial characteristic of the resources captured in an unambiguous way. Otherwise, spatial distance-based matching algorithms may produce erroneous links. In this article, we first suggest to formalize and acquire the knowledge about the spatial references, namely their positional accuracy, their geometric modeling, their level of detail, and the vagueness of the spatial entities they represent. We then propose an interlinking approach that dynamically adapts the way spatial references are compared, based on this knowledge.

Assessing the Positional Planimetric Accuracy of DBpedia Georeferenced Resources

Assessing the quality of the main linked data sources on the Web like DBpedia or Yago is an important research topic. The existing approaches for quality assessment mostly focus on determining whether data sources are compliant with Web of data best practices or on their completeness, semantic accuracy, consistency, relevancy or trustworthiness. In this article, we aim at assessing the accuracy of a particular type of information often associated with Web of data resources: direct spatial references. We present the approaches currently used for assessing the planimetric accuracy of geographic databases. We explain why they cannot be directly applied to the resources of the Web of data. Eventually, we propose an approach for assessing the planimetric accuracy of DBpedia resources, adapted to the open nature of this knowledge base.

Linking Spatial Named Entities to the Web of Data for Geographical Analysis of Historical Texts

In our work, we are interested in facilitating the exploration by scholars of the geography of texts: in particular, historical narrative texts describing routes. Semantic annotation constitutes the first step to enrich such text with the necessary information for producing analytical maps. The present article focuses on the disambiguation of spatial named entities (SNE) by the attribution of an identifier of the ever-growing Web of Data. This giant knowledge base (KB) provides qualitative spatial information about geographic entities, in particular spatial relations such as (:Paris :southOf :Lille), (:Paris :country :France). We thus propose a graph-matching algorithm relying on the A* algorithm and graph-edit distances for choosing the best referent in the KB for the SNE. We performed preliminary experiments and noted the clear gain in performance. We propose some examples of maps that are built semi-automatically. Finally, we draw conclusions and describe our plans of future work.

Ontology-Based Discovering of Geographic Databases Content

Nowadays, the amount of geographic data is permanently increasing. One key issue to take advantage of these data is to be able to evaluate their fitness for use and their complexity. We describe in this paper a system enabling a user to discover the content of geographic databases based on a formalization of their specifications, i.e. enabling the user to discover which entities of interest are represented in a given database, and how they are represented. The system uses a global ‘domain’ ontology describing the topographic real world entities, which can be queried by the user to express his/her needs. Some local (or application) ontologies are used to formalize the content of database specifications. They are annotated with concepts from the global ontology. The described system is implemented as a web application and includes a web mapping solution for the visualization of data samples.