SPATIAL DATA QUALITY Hayati TATAN 1 , M.Orhan ALTAN 2 1 General Command of Mapping, Information Systems and Support Department Cebeci 06100, Ankara, Turkey 2 ITU, Civil Engineering Faculty, Department of Geodesy an Photogrammetry Maslak 80626 Istanbul, Turkey Although the primary objective of any Geographic Information System is to produ ce information in support of decision making on geo-related issues, it is overemp hasized that the quality of such decisions is subjected to the quality of the spatial data upon which they are based. Since the quality is defined as confirmation to t he specifications from the producers point of view and fitness for use from the users point of view, spatial data quality seems to be a subjective measure to dea l with. The increasing use of spatial data with new computer technologies needs not only positional accuracy but also other quality parameters, such as feature an d attribute accuracy, consistency, completeness, up-to-dateness (currency) and li neage. This paper introduces the spatial data quality concept together with error sources and explains spatial data quality standards covering quality terminology, spatial data quality model (parameters & measures), acceptable quality levels an d spatial data quality evaluation model. 1. INTRODUCTION The main goal of any Geographic Information System (GIS) is to produce information in support of decision making on geo-related issues [Tatan, 1991]. The quality of such de cisions is influenced by the quality of spatial data upon which they are based. In other w ords bad information produced from spatial data of poor quality may cause wrong decisi ons, while spatial data of good quality reduces the risk that wrong decisions will occur. The term quality has a number of definitions. In Websters Encyclopedic Dictionary, qual ity (from Latin qualis) is that which makes or helps to make anything such as it is; a disti nguishing property, characteristic, or attribute; (logic) the negative or affirmative charact er of a proposition [Buttenfield, 1993]. This definition implies that data quality possesses an affirmative attribute, measured in terms of similarity to a chosen model (i.e. accurac y) and a negative attribute, measured in terms of discrepancy (i.e. error). In ISO 8402, quality is defined as totality of characteristics of a product that bear on its a bility to satisfy stated or implied needs [Caspary, 1993]. In ISO 15046 which is the only I SO standard on Geographic Information which is still under development by ISO Techni cal Committee (TC) 211 [Ostensen, 1999], spatial quality is one or more characteristics of geographic data that describe the extent that it is fit for use. Having all these definitions into consideration, spatial data quality is may be defined a s totality of indicators showing affirmative or negative distinguishing properties and char acteristics of geographic data which describe confirmation to the specification and fitnes s for use, from the producers and users point of view, respectively. From this definition, spatial data quality seems to be subjective measure, which has been interpreted differe