Non Spatial data, Meta data definition, classification and example in web gis скачать в хорошем качестве

Non Spatial data, Meta data definition, classification and example in web gis

Defination of Non Spatial Data: Non-spatial data refers to information that does not have a specific location or geographic reference. This type of data does not have any inherent spatial relationship and cannot be represented on a map. Non-spatial data are stored in GIS as tables. Such tables are known as non-spatial (attribute) tables. A non-spatial table is represented by rows and columns in which each row shows a spatial feature and each column represents a characteristic. There are four typical data types that we use in GIS:  1.integer. 2.float/real. 3.text/string. 4 date. Metadata Metadata is basically textual data that describes data. It often includes elements such as data creation date, history of the data, data type, and common usages of the data. A Metadata can help users know what’s in your services, who created them, and what usage restrictions they might carry. Some organizations require specific items of metadata on any geographic information they publish. Metadata refers to data that provides information about other data. It provides context and additional information about a dataset or a file. Here are some examples of metadata: Title: A title is a descriptive name given to a dataset or a file that provides context about its contents. Creator: The creator refers to the person or organization that created the dataset or file. Date created: The date created refers to the date when the dataset or file was created. Description: A description provides additional information about the contents of the dataset or file, including its purpose and scope. Format: The format refers to the file type, such as PDF, CSV, or JPEG. Language: The language in which the dataset or file is written or presented. Keywords: Keywords are descriptive terms that are associated with the dataset or file to aid in search and discovery. Spatial coverage: Spatial coverage refers to the geographic area that the dataset or file covers. Temporal coverage: Temporal coverage refers to the time period that the dataset or file covers. Source: The source refers to the origin of the dataset or file.