Geospatial data represent measurements of the locations and attributes of phenomena at or near Earth`s surface. Information is data made meaningful in the context of a question or problem. Information is rendered from data by analytical methods. Information quality and value depends to a large extent on the quality and currency of data (though historical data are valuable for many applications). Geospatial data may have spatial, temporal, and attribute (descriptive) components, as well as associated metadata. Data may be acquired from primary or secondary data sources. Examples of primary data sources include surveying, remote sensing (including aerial and satellite imaging), the global positioning system (GPS), work logs (e.g., police traffic crash reports), environmental monitoring stations, and field surveys. Secondary geospatial or geospatial-temporal data can be acquired by digitizing and scanning analog maps, as well as from other sources, such as governmental agencies. The legitimacy of geographic information science as a discrete field has been claimed in terms of the unique properties of geospatial data. In a paper in which he coined the term GIScience, Goodchild (1992) identified several such properties, including: 1. Geospatial data represent spatial locations and non-spatial attributes measured at certain times. 2. The Earth`s surface is highly complex in shape and continuous in extent. 3. Geospatial data tend to be spatially autocorrelated. It has long been said that data account for the largest portion of geospatial project costs. While this maxim remains true for many projects, practitioners and their clients now can reasonably expect certain kinds of data to be freely or cheaply available via the World Wide Web. Federal, state, regional, and local government agencies, as well as commercial geospatial data producers, operate clearinghouses that provide access to geospatial data. Although geospatial data are much more abundant now than they were ten years ago, data quality issues persist. Good data are expensive to produce and to maintain. Proprietary interests simultaneously increase the supply of geospatial data and impede data accessibility. Standards for geospatial data and metadata are useful in facilitating effective search, retrieval, evaluation, integration with existing data, and appropriate uses. National and international organizations, such as the Open Geospatial Consortium (OGC) and International Organization for Standardization (ISO), develop and promulgate such standards. INSPIRE directive (Infrastructure for Spatial Information in the European Community) regulates geospatial data management
Explain the differences between geospatial data and other types of data
I, progress (GI-N2K)