By: Valrie Grant, Managing Director GeoTechVision
In the last article we looked at how government through the use of policies can help to drive the use of spatial information or tools in the process of economic development. GI policies sets the stage for building out the nation’s spatial data infrastructure (SDI).Since, spatial data is used in both government as well as in the private sector for decision making and planning, a national SDI would facilitate the availability and access to spatial data for all levels of government, commercial and non-profit sector, academia and citizens. It allows data providers and users to participate in the growing use of digital spatial information for planning and decision making purposes.
What is Spatial Data
Infrastructure – SDI?
SDI is often used to denote the relevant collection of technologies, policies and institutional arrangements to facilitate the availability of and access to spatial data. SDI provides the mechanism that allow users to discover, understand, view, access, and query spatial information of their choice from the local level to the global level, for a variety of uses, such as environmental policy development and impact assessment, land use planning, Comprehensive disaster management and other business purposes. Infrastructure indicates a platform or technology facilitating the conveyance of such spatial information.
Open Data Model
As you would realize, various entities gather spatial data for different purposes. SDI must be built on an open data policy framework where government makes available to the public information in a presentable and easy to use digital form. In the context of spatial information, a properly developed GI policy framework would ensure that interoperability is a feature the technology infrastructure used for cataloguing and storing of spatial information. Spatial data collected by one government ministry should be accessible and available for other ministries to utilize. For example, the ministry of agriculture may gather spatial data on the farming communities across the country – what is farmed where, crop yield, farming practices etc.; the ministry of environment may need such data to see how farming practices are impacting the quality of water in rivers from farmland runoff; an investor who wants to get into agro-processing may need that very information to determine location for their agro-processing facility. This kind of access to spatial data can also spur entrepreneurial spirit as it can easily be used to see where there are business opportunities.
For example in the UK, the Ordnance Survey promotes Open Data. They provide a range of quality assured, regularly updated geospatial products that enables any user to analyse their data and build interactive websites and create visualization applications all for free. As long as you credit OS OpenData, you’re free to use these products in any way you wish, provided that it’s not against the law.
Imagine if you could have access to all the necessary Geospatial Data for Guyana, think of all the creative ways that such data could be put to good use.
Adapting to Geospatial Standards
Having an open data framework require adapting to geospatial standards. This means that all creators and users of spatial information must adhere to certain standards that allows the sharing and exchanging of geospatial data. For example, think of Metadata Standards which allows for data discovery. In the spatial dataset context, metadata is very important because it describe the What, Who, Where, Why, When and How of the data. Metadata is really data about data. Practically, this means that with the creation of any set of geospatial data, it must be accompanied with a set of metadata that describes, what the data is about, who created the data, where was the data created, why was the data created, when was the data created, how the data was created and any constraint in the use of the data set. Metadata creation can be tedious is probably the least attractive task in building out data sets in a GIS.
Metadata in essence describes critical characteristics of data including content, condition and quality. It is like the information you would read on the labels of a drink bottle. On the labels, you could learn everything about the bottle’s contents: the nutritional values of the drink, the number of calories, the ingredients, whether it contains preservatives, the weight, the company that packaged it and its location, and more. You then use that information to make a decision whether it is safe to consume this drink or not. Just like the labels on the bottle tell us what it contains, Metadata tells us what the data contains and we can make a decision on the fitness for purpose of that data
In developing a SDI, adhering to standards in collecting, and storing geospatial data prevents a situation where the same data objects coming from different sources contradict both in value and in representation and also allows seamless cross-sector combination of datasets from different sectors and different content.
Standards and Interoperability
Without properly defined standards, interoperability can pose a challenge in fully utilizing the benefits of SDI. For this reason, government policy must mandate the adoption of standards within the spatial information sector. The geospatial professionals working with government policy maker and international bodies can define what these standards for data sharing should be.
In addressing the possible issue of interoperability, three factors must be taken into consideration
- Using the right technology
- There must be a common understanding of data and metadata, i.e. certain generally accepted data definition standards must be used as reference in all applications
- Political support both from the public and private sector in adhering to these standards.
Developing a national spatial data infrastructure requires support from both professionals, government and private business. There are challenges, but the benefits far outweigh the challenges. Government must lead the way – by enacting policies, professionals must assist the process by adhering to standards and best practices, both government and businesses must be prepared to share data in an open data model.
