Rural Open Data Standardization

Standardization Screws

An important yet often unrecognized aspect of open data is the standardization process.  It is easy to get excited about the many benefits of open data, the innovative technology involved, the new applications being developed, and the uncharted legal adventures that could follow; but the tedious processes of opening data aren’t as exciting.  Smart Cities are a hot new trend in the world of open data, geomatics, law, civil planning and politics.  An online search on open data brings up plenty of research on these topics, however, research on the actual standardization process is not as popular, especially for information on rural open data.  This is the topic that I tackled for my thesis for my fourth year, Bachelor of Geographic Information Systems program at Selkirk College.

I was fortunate to land a co-op placement at the Selkirk Geospatial Research Centre (SGRC), a research working within Selkirk College in the summer of 2016.  One of my tasks was to assess the quality and completeness of the data that had been delivered to the SGRC and the Rural Development Institute (RDI) for the Digital Basin Portal Project.  The Digital Basin Portal is an online web mapping application that brings spatial data from 28 communities and 5 regional districts in the Columbia Basin into one place.  You can find the Digital Basin on the RDI’s website.  There you will find anything from cadastral data, water consumption data, zoning data and the locations of parks and other amenities.  It is definitely a useful tool for many people or even just a fun map to explore.  It is definitely worth checking out.

The Digital Basin Portal can be looked at as a precursor to the Rural Open Data Project as it has already brought together many of the communities and regional districts we are hoping to be involved with this project.  These 33 separate government entities all delivered some of their own spatial data to the project so this could possibly the first step in opening up the door to opening up this data.

When the time came around to pick a topic for my thesis I was happy to continue working on the Open Data Project.  I chose to work on the standardization process because I had noticed that, during my assessment of the delivered data, that each community had their own ways of setting up the data and their own definitions of the data.  The data needs to be standardized for interoperability and compatibility (Russell 2014).

Here is a very brief summary of my findings of my research which are basically some guidelines to creating this open data standardization process.

The best data standards focus on both the schematics (how the dataset is structured) and semantics (meanings and definitions of the data itself).  The six fundamental aims of standardization (Aalders and Hunter 2009) are:

  1. Efficiency – avoid time-consuming duplication of data collection and processing
  2. Avoidance of Information Loss – standards help minimize information loss often occurring during data transfer
  3.  Portability of Applications – often specialized software is developed which is shared by users on different platforms
  4. Ease of Learning and Increased Productivity –  and money is saved when users share applications instead of developing their own
  5. Quality Improvement – clear and well-defined concepts
  6. Knowledge Transfer – clarify aspects of data usage and producers help each other when transferring data

The most effective way to create a standard involves engaging stakeholders in the public and private sectors, including the publishers and the users of the data (Jaquith 2016).  The type of standard that satisfies all of these requirements is an open data standard which bring together all stakeholders and satisfy the semantic and schematic requirements (Bloom and Sieber 2016).  The seven principles for open standards are:

  1. We start with user needs
  2. Our selected open standards will enable suppliers to compete on a level playing field
  3. Our standards choices support flexibility and change
  4. We adopt open standards that support sustainable cost
  5. Our decisions on standards selection are well informed
  6. We select open standards using fair and transparent processes
  7. We are fair and transparent in the specification and implementation of open standards

The standardization process for the data for the Rural Open Data project should begin early and included as many stakeholders (publishers and users) as possible.  The process should be fully documented.  Adopt any applicable existing standards (I have a couple resources in the list of links below).  If no standards exist, create one.  The toughest part of this whole process will probably be getting everyone to agree.  A proper voting system should be agreed on at the beginning of the process to proactively avoid this issue.

I enjoyed being involved in the Rural Open Data project and I’m excited to see what is to come.  With this project, I was fortunate to represent Selkirk College by presenting my thesis at the Spatial Knowledge and Information (SKI) conference in Banff.  I also had the opportunity to attend the Geothink - Smart Cities conference at McGill University in Montreal.  It was also great to meet many GIS and open data researchers and fellow students from around Canada.  The Rural Open Data project will bring many benefits to this community and I urge anyone to read more into it.  You can also check out some of my links and resources below.


Aalders HJGL and Hunter GJ. 2009. Spatial Data Standards.  Advanced Geographic Information Systems. Encyclopedia of Life Support Systems.

Bloom R and Sieber R. (2016). Open Civic Data Standards in Canada. Geothink.

Brooksbank C and Quackenbush J. 2006. Data Standards: A Call to Action. OMICS: A Journal of Integrative Biology. Mary Ann Liebert Inc. 10(2): 94-99 Available from

Chignard S. 2013. A Brief History of Open Data. [Internet] Paris Innovation Review: Paris Sciences & Lettres (PSL); Civic Data Standards [Internet]. (n.d.). John Hopkins University.

Jaquith W. (2016). We Need Data Schemas – So Let’s Create Them. U.S. Open Data.

Open Standards Principles­.

Russell A. 2014. Open Standards and the Digital Age. Cambridge University Press.

Sieber R & Johnson P. 2015. Civic Open Data at a Crossroads: Dominant Models and Current Challenges. Government Information Quarterly.



The Digital Basin Portal

Geothink Open Data Standards Project

John Hopkins University Civic Data Standards

Open Data Standards Directory