A health risk assessment for fluoride in Central Europe

Like many elements, fluorine (which generally occurs in nature as fluoride) is beneficial to human health in trace amounts, but can be toxic in excess. The links between low intakes of fluoride and dental protection are well known; however, fluoride is a powerful calcium-seeking element and can interfere with the calcified structure of bones and teeth in the human body at higher concentrations causing dental or skeletal fluorosis. One of the main exposure routes is via drinking water and the World Health Organisation currently sets water quality guidelines for the element. In Central Europe, groundwater resources that exceed the guideline value of 1.5 mg l-1 are widespread and effects on health of high fluoride in water have been reported. The aim of the current project was to develop a geographic information system (GIS) to aid the identification of areas where high-fluoride waters and fluorosis may be a problem; hence, where water treatment technologies should be targeted. The development of the GIS was based upon the collation and digitisation of existing information relevant to fluoride risk in Ukraine, Moldova, Hungary and Slovakia assembled for the first time in a readily accessible form. In addition, geochemistry and health studies to examine in more detail the relationships between high-fluoride drinking waters and health effects in the population were carried out in Moldova and Ukraine demonstrating dental fluorosis prevalence rates of 60–90% in adolescents consuming water containing 2–7 mg l-1 fluoride

The Academic SDI : Towards Understanding Spatial Data Infrastructures for Research and Education.

The demand for geospatial data across different disciplines and organisations has led to the development and implementation of spatial data infrastructures (SDI) and the theory and concepts behind them. An SDI is an evolving concept about facilitating and coordinating the exchange of geospatial data and services between stakeholders from different levels in the spatial data community. Universities and other research organisations typically have well-established libraries and digital catalogues for scientific literature, but catalogues for geospatial data are rare. Geospatial data is widely used in research, but geospatial data produced by researchers is seldom available, accessible and usable, e.g., for purposes of teaching or further research after completion of the project. This chapter describes the experiences of a number of SDI implementations at universities and research institutes. Based on this, the Academic SDI, an SDI for research and education, is defined and its stakeholders are described. The purpose, scope and stakeholders of the Academic SDI are described based on the formal model of an SDI developed by the International Cartographic Association (ICA) Commission on SDIs and Standards (formerly the Commission on Geoinformation Infrastructures and Standards). The results contribute to understanding the state-of-the-art in SDI implementations at universities and research institutes; how the Academic SDI differs from a ‘regular’ SDI; and which role players need to be involved in a successful SDI implementation for research and education

Geographic data as personal data in four EU member states

The EU Directive 95/46/EC on the protection of individuals with regard to the processing of personal data and on the free movement of such data aims at harmonising data protection legislation in the European Union. This should promote the free flow of products and services within the EU. This research found a wide variety of interpretations of the application of data protection legislation to geographic data. The variety was found among the different EU Member States, the different stakeholders and the different types ofgeographic data. In the Netherlands, the Data Protection Authority (DPA) states that panoramic images of streets are considered personal data. While Dutch case law judges that the data protection legislation does not apply if certain features are blurred and no link to an address is provided. The topographic datasets studied in the case studies do not contain personal data, according to theDutch DPA, while the German DPA and the Belgian DPA judge that topographic maps of a large scale can contain personal data, and impose conditions on the processing of topographic maps. The UK DPA does consider this data outside of the scope of legal definition of personal data. The patchwork of differences in data protection legislation can be harmonised by using a traffic lightmodel. This model focuses on the context in which the processing of the data takes place and has four categories of data: (1) sensitive personal data, (2) personal data, (3), data that can possibly lead to identification, and (4) non-personal data. For some geographic data, for example factual data that does not reveal sensitive information about a person, can be categorised in the thirdcategory giving room to opening up data under the INSPIRE Directive