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Geographic Information Systems (GIS): About


Geospatial datasets are scattered throughout the internet. In this guide, we compile online sources into an index with an interactive interface. The objective is to make it easier for researchers to know what data is available for a given theme.

All sources in this guide contain location-based data. Many of them are in ready-to-use GIS formats such as shapefiles. Other formats include tables or graphics of maps; you may convert them into GIS formats either by joining with existing GIS data, or by georeferencing. If you have any questions about the use of this data guide and the data sources, please feel free to contact us.

The interface is made using a modified version of DynaTable.

Using the data guide

1. Click on each checkbox with your thematic keywords of interest. The list may take 1-2 seconds to load.

2. To filter the list by keywords found in description (eg. country etc.), type into the text box and press <enter>.

If necessary, click on column name to toggle sorting.

Before using, always assess if the data quality fits your purposeTo use the data, you may need GIS software; the leading commercial software is ArcGIS, and QGIS is a great open source alternative. 

A note about data quality

Scholarly work demands rigour in selection of data sources. In geographic research, spatial relationships are often the subject of study. The choice of maps are important, because distortions may lead to inaccurate interpretation of spatial relationships. In an age of speed and convenience, the internet offers a wide spread of data options, but uncritical data use may compromise the credibility of your work.

For an introduction to geospatial data quality, please refer to this report by W. Rasdorf (2000). For a start, he cited the US Spatial Data Transfer Standard which lists five components of data suitability assessment:

  1. Data lineage
  2. Positional accuracy
  3. Attribute accuracy
  4. Logical consistency
  5. Completeness

At the end of the paper an annotated bibliography listed further readings into various aspects of data quality.

For evaluation of non-spatial attributes, some preliminary questions include:

  1. Is the source authoritative?
  2. Is the level of currency suitable for the purpose?
  3. Is there undocumented bias in the data?
  4. Is it obtained from its undoctored primary source?