DCPS Participatory Budgeting Web App - tool for parents and students to inform DCPS about preferences for school budgets AND help DCPS aggregate preferences to make data-driven decisions (@ODDChallenge)
Ebola Data Jam - inventorying health systems in Liberia, Sierra Leone for eboladata.org
DC Tree Map: Last year we combined DC tree data from public works and Casey Trees into dctreemap.org (running on CartoDB). This year we're merging those same (and updated) data into Azavea's OpenTreeMap platform.
Data was found and cleaned. The shell of a web app was created. We learned about Leaflet and created a basic map. Shapefiles were snatched from opendata.dc.gov and converted to GeoJSON. We spun up an API to collect and process feedback and school photos.
Schools in a geographic map - show color variation/bands for different thresholds of per pupil spending in 4 tiers- below $9,000, $9-10,000, $10-11,000, $11-12,000, over $12,000 for general education spending
Kat TCurrent Status[as of 4pm est Sat feb 22nd]: There were two datasets provided for comparative analysis: the household surveys, and contextual geographic context such as precipitation patterns, chicken poultry density, roadways, etc. Unfortunately the household surveys were not geocoded, and so the datasets cannot be compared at this time.
General consensus is that there is a lot of interesting information contained in these datasets, and we can see how it would be useful to compare and to map, but there is not enough information to complete the task.
We may need to call the people who performed the survey.
Gabriel KGabriel: Agreeing with Ann and Eliot. While the sample data of Ghana provides some interesting reference material for Ghana GIS data, I'm not seeing anything that links it explicitly to the WEIA Index data. I would wonder how to do this in an interesting enough way while maintaing survey privacy at the household level. Perhaps regional-specific data could be used, have that geocoded, and then layered?
Charles WCharlie:Just to tack on here, we need some way to reference hhserial in the WEIA date to a set of lat/lon coordinates.
The Team has come up with a number of innovative ideas to address these two challenges! Here is what we are working on:
(1) Improving accessibility to the road safety data through a visualization tool
Thore and Dave are developing a web-based tool that traffic management agencies and the public can use to understand road accident patterns in their cities. By understanding these patterns, traffic management agencies can more effectively deploy traffic enforcers (by time of day and day of week, based on accident likelihoods), and city governments can allocate scarce funding resources to improving those intersections.
(2) Transit network redundency visualization
Since this is the first time a transit system map has been produced in the Philippines, Sara and Aaron are going to help the Department of Transportation and Communications (DOTC) visualize the network in terms of route overlapping and redundancies. As the DOTC considers how to rationalize the network, as a starting point, they can look at the most and least served corridors in the city.
(3) Corrolating accidents with transit route density (and identifying key locations for investing in formal station construction)
Sara, Aaron, and Carlos are working with Thore and Dave on corrolating accidents with specific transit corridor locations. If there is a corridor with a lot of redundant jeepney routes (which are hailed -- no formal stops) and we see patterns of accidents around certain locations, then the Metro Manila Development Authority and Land Transport Franchise Bureau can target these locations for building formalized stations that would keep passengers safe.
(4) Determining probability of accidents by location in Cebu, using accident and traffic volume datasets
Li and Travis, data analysis gurus, are refining the way we analyze road safety data. Rather than just show intersections that experience the most accidents, he is helping us show those intersections that experience the most accidents relative to the traffic volumes along those corridors.
Sound interesting? Come join us!
DO LAW ENFORCEMENT EFFORTS HAVE AN EFFECT ON THE AVAILABILITY OF FAKE DRUGS IN DEVELOPING COUNTRIES?
Recommendations on how to display map data for individual layers and to show multiple impacts in a way that a decision-maker can quickly assess what is most important for their city or community
Sohee GRecommendations thus far (Please feel free to add more!) :
Zander Furnas, Researcher - Sunlight Foundation
Ryan Schuster - NOAA
In terms of processing “severities”, creating a baseline “severity” for its data point and then comparing the marginal difference in impacts based on the local v. country baseline will allow the users to compare severity
Ricardo Saavedra, Founder + Developer - Vizonomy
Even if the Atlas keeps the quintile model to assess severity, the tool may contextualize certain overlaid impacts through formulating a scenario for each “synthesized’ case
Hover windows per data point that compares the “severity”
Other visual aids to explain the dark grey areas, like diagrams
The danger of creating a “fruit basket” is that the represented synthesized severities may be misleading the viewers
Other design recommendations:
Use less than 5 colors if possible -
Make it downloadable for the Google Earth use (*.kml)
A side bar that shows how each processed layer (climate impact) varies from the national/regional standard would be sufficient to help people
Thore Fechner, Institute for Geoinformatics - University of Munster
Visually representing different severities on a map is possible;
It is a matter of aggregating the data based on what the users’ needs are; identifying that would be the priority
Then, it is necessary to put data into a standardized format (i.e. WCS, WPS, WCPS) in order to achieve visual layering
After these steps are achieved, visually representing different climate impacts and their severities can be done
Given the scale of the Atlas and what it is trying to achieve, it will take some time to design/ collect/ process data
University of Munster has a team that manages this type of problem, and usually takes an entire year doing this
Visualizing projection is also possible - as long as data is in the standardized format. For Europe to have a standardized data format for all of its geo-data, it took them ~ 15 years
There will be new data released in the days before the event -- we need people to dive into/catalog/visualize/explore this data.