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Geospatial data and metadata

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What is geospatial data?

Spatial data in general refers to the location, shape and size of an object in space. Geospatial data is a subset of spatial data.

Geospatial data is data that pertains to an object on Earth. Any data that is created or captured with an associated geographic component is known as geospatial or spatial data. This means information which represents the location, size, and shape in space of an object or element. This information can be represented by numerical values in a geographic coordinates system.

Specialised software applications, such as GIS software, can be used to access, manipulate, visualise and analyse geospatial data.

Why is geospatial data and metadata so useful?

Despite the growing volume of geospatial data available from variety of sources, and the ease of identifying this data, discovery and utilisation still remains a challenge for researchers because of limited metadata. From the end user's perspective, detailed metadata is required to gain information about the data’s provenance, custodianship, as well as a clear understanding about the copyright and reuse conditions, all of which engender confidence in the research outputs and evaluate the potential reusability of the data.

The inclusion of metadata to enable the transfer or sharing of data is now a standard practice in the spatial communities. This metadata ensures that users of the data are aware of its geographic indexing, limitations, restrictions and of its suitability for use into their research.

What are the elements of geospatial metadata?

Metadata is the part of the dataset which provides context to the data content. Much data may have a geospatial component in its metadata even though data itself is not considered to be geospatial data. 

For example, the records in a dataset may contain locational metadata such as geographic data in the form of coordinates, address, city, statistical or post code. This can in a range of forms or formats like static maps, aerial images and satellite/sensor data, GIS layers or files and other tabular data, e.g. rivers, lakes, wetlands, roads, parcel boundaries, statistics, socio-economic models, health data and more.

Other metadata elements that are particularly relevant to the capture, storage and application of geospatial datasets include:

  • lineage (provenance) – who, how and when a dataset was created
  • detailed abstract, contact and resource information, themes and keywords
  • metadata that describes the age, accuracy, content, currency, scale, reliability, authorship and custodianship of an individual dataset
  • standards used in the creation of the dataset.

What are those metadata standards?

There are many metadata standards currently available for geospatial data. In the Australian context, ANZLIC – the Spatial Information Council is the peak intergovernmental organisation that provides leadership in the collection, management and use of spatial information in Australia and New Zealand.

The ANZLIC metadata profile was developed to facilitate the interoperability within and between Australian and New Zealand agencies and jurisdictions and is based on the ISO 19115 international standard. ANZLIC metadata standard:

  • describes all aspects of geospatial data and provides a comprehensive set of metadata elements to the end users
  • is widely adopted in the industry, academics, research and government to further value add to the spatial data in offering better discoverability possibilities and maximise the re-use.

The ISO 19115 schema is the preferred international standard for spatial resources. It can be generated by the following open-source tools:

  1. ArcGIS
  2. ANZMet Lite
  3. GeoNetwork
  4. Other software and tools.

Benefits of standard metadata 

  • value adds the products/data sets
  • wider discoverability, interoperability and access
  • increases the reliability and confidence
  • reduces the duplication of datasets or projects,promotes data reuse
  • develop partnerships, institutional engagements within the multidisciplinary communities.

Further reading