Extending INSPIRE Metadata to imperfect temporal descriptions ∗

When looking for geodata in a Spatial Data Infrastructure (SDI), the user expresses precise selection conditions on the values of metadata in discovery services. In order to obtain a list of results, corresponding values of metadata must exactly match such conditions. This practice suffers from several drawbacks. First of all, with respect to the temporal characterization, available recommendations for metadata specification of the INSPIRE Directive are inadequate to satisfy the several semantics of the temporal conditions. To this aim, we propose to extend the metadata to enrich the description of geodata, with the possibility to indicate temporal metadata related to both the observations and the observed event as well as of specifying the temporal resolution of observations. Furthermore, we introduce a proposal to manage temporal series of geodata observed at different dates. In order to represent the uncertain and incomplete time knowledge on the available geodata, we allow the specification of imperfect temporal values which is not considered nor managed within INSPIRE. Last but not least, as far as the discovery service providing searching facilities on metadata catalogs, we propose to allow expressing flexible selection conditions, i.e. tolerant to under-satisfaction, so as to retrieve geodata in decreasing order of relevance to the user needs, as it usually occurs on the Web when using search engines. This contribution discusses the above limitations and the related solutions, expressed in terms of formal and operational methods taking into account imperfect temporal metadata values and flexible search conditions. Proposals will be illustrated with examples taken from an already existing European SDI. ∗ This work is licensed under the Creative Commons Attribution-Noncommercial Works 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA. Article under Review for the International Journal of Spatial Data Infrastructures Research, Special Issue GSDI-11, submitted 2009-04-03