How can a SDI be used for policy decision-making in the Arctic?

March 14, 2017 Gordon Plunkett

Geospatial data is voluminous and can be used as a tool for making more informed decisions. In particular, geospatial data is currently being used to carry out a project related to a Spatial Data Infrastructure for the Arctic. Read this blog to find out more about the project and how spatial data is used in policy development. 

Natural Resources Canada (NRCan) and the United States Geological Survey (USGS) are working together to plan and carry out a project related to a Spatial Data Infrastructure for the Arctic. The objective of the project is to show how geospatial data can be used as a tool for making more informed decisions and providing more efficient administration of the Arctic region.

The Open Geospatial Consortium (OGC) was engaged to manage the project and Esri Canada decided to get involved and help work on some of the objectives of the Arctic Spatial Data Pilot Project (ArcticSDP). Esri Canada chose to work on the policy issue of food security in the Arctic and to show how spatial data can be used to assess and monitor general policy issues.

It was decided that a policy “workbench” would be developed, which would allow policy workers to stay current on the issues, examine causes and effects, plus monitor any policy initiatives. Policy, in general, is developed through the completion of various steps. Spatial data can often be used during each step of the policy development process. The following table shows the steps that are most often taken in policy development, implementation and evaluation. It also shows the role that spatial data can play in each step of the policy-making process.

Policy steps

Role of spatial data

1. Issue identification

Who, where and why are people affected?

2. Policy analysis

By collecting and analyzing (cause & effect) relevant spatial data, does the data backup the issue?

3. Consultation

Who should be consulted about a solution and where are they?

4. Policy instrument development

Based on the consultation, are there spatially related policy applications?

5. Building support, coordination & coalitions

Who will be responsible for the policy implementation and where are they?

6. Program design

Based on their location, who needs to make the final policy decision?

7. Policy implementation

Who needs to know about the policy, who implements the policy and where are they?

8. Policy evaluation

Continue to monitor (collect new data) and evaluate (analyze data) to ensure the policy is working.

Clearly, spatial data is a key element in policy making, but how does one find the appropriate data and then use it for policy decisions? Data-sharing mechanisms are thus a prerequisite for the use of spatial data in this process. One of the goals of this project is to show how data that is available as a web service can be easily found, accessed and subsequently used in the context of food security policy.

So, if someone is going to develop a demonstration food security policy workbench for the Arctic, what data and processes need to be included?

Given that the project was just a demonstration and that it was also focused on web services, it was decided that ArcGIS Online would be used for implementing the workbench. ArcGIS Online has many advantages to developing a workbench, including:

1) users only need a web browser

2) no programming is required to add data layers from the web

3) the application can be easily shared with a team of individuals

4) the user interface is simple to use

Landing page for the Arctic food security policy workbench. It was built using a tabbed web mapping application template on ArcGIS Online. Each tab links to various information for the Arctic food security policy makers and because it is cloud based, the workbench can be accessed simultaneously by many policy workers, in any region.

One of the demonstration’s more important tabs showing significant interoperability is the Reference Maps tab, which has four layers integrated using four separate types of web service. These layers are as follows:

1) the US national transportation network, using a Web Feature Service (WFS) from the US National Map

2) the Canadian transportation network, using a Web Map Service (WMS) from NRCan

3) the Alaska ice forecast, using a Keyhole Markup Language (KML) file service from the US Weather Service

4) the Arctic SDI basemap, using a Web Map Tile Service (WMTS) hosted by the Norwegian Mapping Authority

Arctic Reference maps using four different OGC Web Service protocols, which are WFS, WMS, KML and WMTS

The results of the project will be presented at USGS at the Arctic Spatial Data Pilot Project demonstration event in March 2017.  Will there be any surprises demonstrated at the event? There may be, but clearly, the ability to create a web application that is very easy to use, has a simple user interface and can bring data in from around the world with the click of a mouse will be something that should get the attention of government and other policy makers everywhere.

 

About the Author

Gordon Plunkett

Gordon Plunkett is the Spatial Data Infrastructure (SDI) Director at Esri Canada. He has more than 30 years of experience in GIS and Remote Sensing in both the public and private sectors. He currently sits as a member of the Community Map of Canada Steering Committee, GeoAlliance Canada Interim Board of Directors, the Open Geospatial Consortium (OGC) Technical Committee, the Canadian General Standards Board (CGSB) Committee on Geomatics, the University of Laval Convergence Network Advisory Committee and the Advisory Board to the Carleton University Geomatics and Cartographic Research Centre. During his career, Gordon has worked on projects in more than 20 countries and has contributed to numerous scientific conferences and publications. At Esri Canada, he is responsible for developing and supporting the company’s SDI vision, initiatives and outreach, including producing content for the SDI blog.

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