![]() It implies the use of a Geographic Information System (GIS) that can process a special type of data referred to as spatial data, geospatial data, geographic data or just geodata. Taking advantage of the information on where an object is located and how it is delimited leads to the field of spatial analysis. Performing scientific analysis implies the use of data and systems that can process this data to gain new insights into the characteristics and interdependencies of research objects. 1.2 Spatial Data Models (by Andreas Redecker) Most of the metadata is stored in XML files. ![]() Moreover, the format is machine-readable, easily and quickly searchable and convertible to other formats. XML files are used mainly for data exchange due to its simplicity, openness, and platform independence. XHTML, SVG, KML, Microsoft Office, OpenOffice and others). Since its introduction in 1996, XML has become a basis for many other formats (e.g. This abbreviation stands for eXtensible Markup Language (XML) using structured markup language with constructs such as tags, elements, and attributes. Data stored in XLS could be still opened in the newer Excel version. needs specialised software/plugins to be opened), while XLSX represents zipped XML file, and was introduced by Microsoft in 2007. Label XLS/XLSX is basically “only” a suffix for an Open Office XML scheme (OOXML). The data is stored in tables, which are organized in spreadsheet and sheets. XLS/XLSX extension are formats of Microsoft Office package, namely with Excel, and is one of the most used and widespread format. The format is interoperable, interchangeable and in most cases in the form of a plain text (storing both text and numbers). Most of the tabular software is capable of working with CSV. Individual records are separated by comma (in some case by a semicolon, blank space, or another tabulator) and the format is classified as a delimiter-separated format family. 1.1.2 CSVĬomma Separated Value (CSV) is a simple and standardised format for data storage. Thus, the greatest advantage of this format is its interoperability. txt file in most of the software and even with the simple text editors (like Wordpad). Since the format is mainly plain text (with very limited options for formatting), it is possible to open the. The text could be supplemented by the special symbols for row endings, blank spaces, and tabulators. This is the most common data format using plain text. Therefore, it is liable to mention the main characteristics of such formats. Some of the data providers offer several options regarding data formats. ![]() In this section, the most used data formats will be briefly introduced. Keywordsġ.1 Basic Tabular and Attribute Data Formats (by Vít Pászto) The whole chapter focuses on the major data models and sources, so it serves as a gateway to further exploration of existing data storages. At last, a remote sensing perspective on data sources is introduced, pointing out the most important Earth observation data. This part is mainly covering the economic (socio-demographic) topics. Emphasis is also given to the international and selected national data sources, both non-spatial and spatial. Since the geospatial domain is heterogeneous in terms of different data formats, the list of interoperability data sources and services is provided. It is then followed by the spatial data models, including vector and raster data core principles. The chapter starts with a summary of the most commonly used data models, starting with tabular and attribute formats. Description of such data sources is complemented with the basics from respective disciplines to provide a thematic context to the reader. This chapter is devoted to the overview of the data fundamentals as regards data models and sources accompanied by geomatics, remote sensing, and economy.
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