Flexible Querying of Imperfect Temporal Metadata in Spatial Data Infrastructures

Flexible Querying of Imperfect Temporal Metadata in Spatial Data Infrastructures

Gloria Bordogna (CNR-IDPA, Italy), Francesco Bucci (CNR-IREA, Italy), Paola Carrara (CNR-IREA, Italy), Monica Pepe (CNR-IREA, Italy) and Anna Rampini (CNR-IREA, Italy)
DOI: 10.4018/978-1-60960-475-2.ch006
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Abstract

Spatial Data Infrastructures (SDI) allow users connected to the Internet to share and access remote and distributed heterogeneous geodata that are managed by their providers at their own Web sites. In SDIs, available geodata can be found via standard discovery geo-services that makes available query facilities of a metadata catalog. By expressing precise selection conditions on the values of the metadata collected in the catalog, the user can discover interesting and relevant geodata and then access them by means of the services of the SDI. An important dimension of geodata that often concerns such users’ requests is the temporal information that can have multiple semantics. Current practice to perform geodata discovery in SDIs is inadequate for several reasons. First of all, with respect to the temporal characterization, available recommendations for metadata specification, for example, the INSPIRE Directive of the European community do not consider the multiple semantics of the temporal metadata. To this aim, this chapter proposes to enrich the current temporal metadata with the possibility to indicate temporal metadata related to both the observations, i.e., the geodata, the observed event, i.e., the objects in the geodata, and the temporal resolution of observations, i.e., their timestamps. The chapter introduces also a proposal to manage temporal series of geodata observed at different dates. Moreover, in order to represent the uncertain and incomplete knowledge of the time information on the available geodata, the chapter proposes a representation for imperfect temporal metadata within the fuzzy set framework. Another issue that is faced in this chapter is the inadequacy of current discovery service query facilities: in order to obtain a list of geodata results, corresponding values of metadata must exactly match the query conditions. To allow more flexibility, the chapter proposes to adopt the framework of fuzzy databases to allow expressing soft selection conditions, i.e., tolerant to under-satisfaction, so as to retrieve geodata in decreasing order of relevance to the user needs. The chapter illustrates this proposal by an example.
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Introduction

Infrastructures are complex systems in which a network of interconnected but autonomous components is used for the exchange and mobility of goods, persons, information. Their successful exploitation requires technologies, policies, investments in money and personnel, common standards and harmonized rules. Typical examples of infrastructures which are critical for society are transportation and water supply. In Information Technology, the term infrastructure could be related to communication channels through which information can be located, exchanged, accessed, and possibly elaborated.

The importance of Spatial Data Infrastructures (SDIs) has been recognized since the United Nations Conference on Environment and Development in Rio de Janeiro in 1992.

Geographic information is vital to making sound decisions at the local, regional, and global levels. Crime management, business development, flood mitigation, environmental restoration, community land use assessments and disaster recovery are just a few examples of areas in which decision-makers can benefit from geographic information, together with the associated Spatial Data Infrastructure (SDI) that support information discovery, access, and use of this information in the decision-making process.

In time, the role of discovery services of data with a geographic reference (geodata) has become a main issue of governments and institutions, and central to many activities in our society. In order to take political and socio-economics decisions, administrators must analyze data with geographic reference; for example, the governments define funding strategies on the basis of CO2 pollution distribution. Even in everyday life, people need considering data regarding the area in which they live, move, work and act; for example, consider a family wishing to reach mountains for a skiing holiday, and looking for meteorological data. In order to be useful, the data they are looking for should fit the area and period of time of their interest; they should trust in the quality of the data; if possible, they should obtain what they need with simple searching operations, and in a way that allows evaluating the fitness of the data with respect to their needs and purposes.

In 2007, the INSPIRE Directive of the European Parliament and of the Council entered into force (INSPIRE Directive, 2007) to trigger the creation of a European Spatial Data Infrastructure (ESDI) that delivers to the users integrated spatial information services. These services should allow users to discover and possibly access spatial or geographical information from a wide range of sources, from the local to the global level, in an inter-operable way for a variety of uses. Discovery is performed through services that should follow INSPIRE standards and can be implemented through some products (either proprietary or not) that declare their compliance.

Nevertheless, current technologies adopted in SDIs, and consequently the actual practice for searching geographic information, do not comply with the way users express their needs and search for information and hamper the ability and practices of geodata providers.

One main problem is due to the characteristics of the information on the available geodata, i.e., metadata. Metadata is an essential requirement for locating and evaluating available geodata, and metadata standards can increase and facilitate geodata sharing through time and space. For this reason considerable efforts have been spent to define “standard” and minimum core metadata for geodata to be used in SDIs. INSPIRE is nowadays a directive of the European community that comprehends metadata specifications (European Commission, 2009).

Nevertheless, such specifications are still incomplete and inadequate for they do not allow specifying all the necessary information on geodata as far as the temporal dimension, and force providers to generate precise metadata values, which are missing in many real cases (Dekkers, 2008; Bordogna et al., 2009).

This chapter, analyses the utility of temporal metadata on geodata and proposes a framework to represent its imprecise and uncertain values as well as to express its possible multiple semantics. .

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