This is a liveblog written by Rahul Bhargava at the 2017 UN World Data Forum. This serves as a summary of what the speakers spoke about, not an exact recording. With that in mind, any errors or omissions are likely my fault, not the speakers.
UN created the Committee on Geospatial Information Management (GGIM), which brought the topic to the fore within the UN. They’ve worked across countries on standards and solutions. In addition, they wanted to make sure that this was married to statistics. This panel will talk about the challenges and benefits of this integration in their countries.
SDGs and Geospatial Perspectives – Tim Trainer
Tim Trainer is the Chief Geospatial Scientists for US Census Bureau. SDGs are geospatial, statistical, and require both international collaboration and multi-stakeholder partnerships. There is a IAEG-SDGs that is a working group on geospatial information to support the SDGs. For instance, they are looking at Tier III indicators that could move up to tier II if there were better geospatial information.
Digging into the SDG targets, take target 11.7 as an example, which is about “safe, inclusive, accessible, green and public spaces”. Each of these doesn’t have a well-agreed upon information. To meet the target within the goal, we need a good definition of each term and we need to know and interrogate the data. We have to decide if the data is “good enough”. This pushed us to ask about the preferred state, what we’ve got, what can be helpful, and what is harmful.
Statistical data in the US can be broken down by county, census track, and census blocks (9 million of them). In Europe they don’t need small area geography like that. On top of that you pull in the statistical measures. To do this type of integration, you need to assess, extract, link, create and develop; all mostly manual processes.
Relaving Unknowns in Statistical Information – Derek Clarke
Dr. Clarke is the National Mapping Organization in South Africa. Tabular information is very elementary, and often human unfriendly. Mapping increases that and allows for visual comparison. The level of details (region vs. sub-region) can indicate how useful some data is for development planning
Geospatial information is most commonly represented as a map. Dr. Clarke talks through an example map that show a sparse distrution of schools across a large area, with mountains and rivers between them. Integration reveals unknowns in the statistical information.
South Sudan has both the geospatial and statistical bureaus in the same department.
Distracting Peple with Truth – Greg Mills
Greg Mills works at Vizzuality, a socially conscious data design company. Even though we talk about data and integration, our starting point is with people. Greg shows videos of birds performing a mating dance; expressing its genetics through dance to find a mate. Another way to think is that it is expressing truth. At Vizzuality we try to create that dance, but with data. Further, we try to equip others to dance better. Some people learned to dance not the truth, which has been happening a lot lately.
Greg wants to share a few techniques that they use to help:
- “Design is to decide” – when you are integrating you make choices, and passive choices don’t turn out too well. Another idea is pgressive disclosure. The Global Forest Watch is their example of this. They start with the pink to show where the forest is gone. Then you can dig into protected areas afterwards. So you hook people and then draw them in.
- The “one-stop-shop” isn’t necessarily the best way to share your information. Greg shares a map created with Carto to show where UK tourists spend money in Spain on holiday. Most of these things are built to be embedded in other places.
- Maps aren’t the only way to convey information. The Soy Deforestation map is an example of this. They augment maps with other forms of information. With a SanKey diagram they see the flow of trade and then people can filter by attributes.
- A key challenge is to find data, bring it into a workflow, and create things with it. With the NYC Mayor, they are creating a central place to determine what their priorities are – a data dashboard for NYC. The key was a simple way to connect data across departments. They call this “data highways”.
The Data Revolution – Sharthi Laldaparsad
Sharthi has worked at Statistics South Africa for over 20 years. Sharthi argues that the data revolution is about connecting geospatial and statistical information. StatsSA has been doing this integration for years now. We’ve got standard geographic frames / building blocks, with reliable sampling frames. South Africa has a national development plan based on a well-functioning statistical system.
The Global Statistical Geopsatial Framework has 5 principles. These range from standards to usability. Unfortunately some datasets in South Africa don’t always includes the geographic indicator they have defined.
Policy analysis builds on this integration. Will this tell us what the priorities are? Population maps show how South Africans love the city. Another map, of buildings completed, can show how the pattern of construction has stayed the same – uneven. Looking at new VAT registrations you can see how and where businesses are being created. These are the types of maps you need to know how to grow the economy and create jobs (a policy goal).
Q & A
In terms of governance structure, who is responsible for the data?
There is an issue of cost, accessible, and accuracy. The free satellite data for sub-Saharan Africa is out-of-date, for example.
Is there a plan or project to represent the SDGs spatially?
What about leveraging the private sector data, and citizen-generated data?
Sharthi: The National Spatial Data Infrastructure (NSDI) is under the department of Rural Development in South Africa.
Dr. Clarke: Yes, they wanted it to be more centrally placed.
Tim: In the US our statistical responsibility is distributed. The Census Bureau is the largest, but for instance the Transportation department has its own. The same is true for Geospatial data. The census bureau manages the boundary lines, an address list, and the road network. The last might be surprising, but they need to code every respondent to an address, which is based on the street network. Regarding the GGIM, the expert group on SDGs formed a working group and just met for the first time in August. Then in Dec they met to dig into which Tier III SDG indicators could benefit from geospatial information. For example, If you need to know the rural population that lives within 2 kms of a road, you have to have some geospatial information like housing units and roads.
Dr. Clarke: In response to mapping sub-Saharan Africa, agreement that Africa is poorly mapped. Often there is better data out-of-country than in-country. The national mapping organizations are poorly funded. This doesn’t help collect and maintain the geospatial information. For satellite imagery, there are efforts to collect it and provide it to the country. We hope the situation will improve. At the same time, in Equatorial Africa, all you’re going to see clouds for most of the year. Imagery like a sense in an aircraft will give you better answers there.
Tim: This is an example where partnerships could be a win. The census scanned the web looking for localities that had contracted their own local imagery. After that test they contracted with another organization that had a well-maintained database of this, which is much better. Engaging with the private sector can benefit you.
Greg: Regarding accessibility of data, just today we’ve been talking about huge numbers of publicly available datasets. So why are they not used more? Partially this is because our human structures don’t match data structures. We have to understand those in order to improve this. There is a gap that needs to be filled.
Data Therapy 