Hackpads are smart collaborative documents. .

Chris Given

972 days ago
  • 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 
Chris G
  • DC Public Schools Facilities - a bird's eye view of the condition of school buildings and gathering additional insights into planning and needs.
Greg B
  • DC Open 211 -  building an open platform for of health and human service directory information. Help us model Eligibility criteria, systems design, and user-test a resource directory database
Shiladitya C
  • Social Media Sentiments - Analysis of social media sentiments around major domestic/international events e.g. military strikes, Presidential elections, World Cup Final
Tai J
  • Campaign Clarity  - Creating an influence index from the sway that corporations and lobbyists hold over political candidates.  
Sara G
  • College campus crime reports: Creating a place where students/parents can research their college's campus crime statistics and whether their college has been audited or fined, all in one place.
Jana M
Rob B
  • 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.
 
972 days ago
Unfiled. Edited by Peter Jones , Jason Quisberth , Curtis Morales , Chris Given 972 days ago
Chris G What's Happened?
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.
 
 
 
(Chris: Add this to Dropbox folder for the project?)
 
Curtis M Comment API:
 
 
Peter Jones (@petercarrjones) peter.carr.jones@gmail.com
Jason Quisberth (@Jaybaby00) 61quisberth@cardinalmail.cua.edu
 
972 days ago
Unfiled. Edited by Ashley Douglass , Sandra Moscoso , Chris Given , Mike Sandfort 972 days ago
General Education Funding Equality 
Ashley D DC Fiscal Policy Institute
Aiming for more equitable distribution of funds in DC public schools
 
Considering: 
At-risk funds
Budget
 
Questions to consider: 
What is spending per-student in different schools for GENERAL education (not special populations)
Need to define general education? Has been done in the budget…
Want to link the budget/funding with the actual spending
 
Data Sources:
 
Sandra M Types of Analysis:
  • Schools by Ward, School type, and 40 lowest performing schools 
  • General ed per student - Mary Levy's spreadsheet, this is main map/graphic on site
Sandra M
  • Special education per student - can filter out these funds or add them back in - interactive
  • Title funds per student - can filter out these funds or add them back in - interactive
  • ELL funds per student - can filter out these funds or add them back in - interactive
  • Per Pupil Funding Minimum (included and excluded)
 
 
Chris G Soumya Bhat: bhat@dcfpi.org
Mary Levy: marylevy41@verizon.net
Mike S Mike Sandfort cute_moniker@yahoo.com
Chris G Chris Given: cmgiven@gmail.com
 
  • TotalFY15 = TotalLocalFY15 + TotalFederalFY15 + TotalAfterSchlFY15
  • TotalLocalFY15 = GenEdFY15 + SpecEdFY15 + ELLFY15
  • AtRiskFY2015 ~= $2079 x ProjAtRisk (Chris)
 
Sandra M Possible visualizations: 
  • 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
  • darker colors the higher you are in spending
  •  
 
1336 days ago
Kat T Current 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.
 
 
  • This is the sample dataset with the anonymized GIS coordinates for use at Open Data Day: 
  •  
 
We may need to call the people who performed the survey.
Gabriel K Gabriel: 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 W Charlie: Just to tack on here, we need some way to reference hhserial in the WEIA date to a set of lat/lon coordinates.
 
  • Philippines Road Safety and Transit Data Hack
Team Members
Holly Krambeck (hkrambeck at worldbank dot org) 
Li Qu (lqu at worldbank dot org)
jeepneysurvey . Travis Korte (tkorte at datainnovation dot org)
Aaron Dibner-Dunlap (aaron dot dibnerdunlap at gmail)
Sara Thurman (srthurman at gmail)
Dave Johnson (davj56 at gmail)
Thore Fechner (t.fechner at uni-muenster dot de)
Carlos Morales (carlos at dbsinc dot us)
 
Project #1: Analyzing Road Safety Data
 
  •  
Project #2: Using the Philippines Transit Information Service (GTFS Database) to Inform Planning
Problems 
 
 
jeepneysurvey . Philippines Open Data Day Solutions
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 G Recommendations 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.
 
Chris G Status
Created a JSON in a visualization-ready format: https://github.com/cmgiven/feeder-patterns
 
While all data could be useful, the key is the find applications that can actually be implemented with the resources (developer man-hours) that we have available.
 
Rahul M Quotes for Tom
  • "OSSE's willingness to share data helps me as a future parent to gain confidence and invest in DC Public Schools." Rahul Mereand-Sinha
 
Resources
 
Robert B
  • Feeder Patterns
  • EA2004-EA2011 Feeder Data Compilation (from @jburwen):
 
 
...
1336 days ago
Contact: Tommy Shen (Gimperion@gmail.com)
 
Jonathan R "Thanks for providing awesome data for us to hack with OSSE! Pulling together an analysis of feeder patterns along m " - Jonathan Robinson
 
Brian B "Amazing work OSSE!  Thanks for releasing this data" -Brian Brotsos, future DCPS Parent
 
Andy R "Thanks - this is great stuff for parents looking to work with DC on schools issues!"
 
Robert B "Thanks for providing " - 
 
MaryBeth "Thank you for releasing data, providing support for families across DC!"
 
 
Chris G "OSSE has set a high bar for responsiveness to the open data community with this release of new data. All DC agencies should take note!" - Chris Given
 
 
 
 
Neighborhood Cluster Information 
Cluster Reference with Cluster numbers, cluster names, lat/long centers: https://docs.google.com/spreadsheet/ccc?key=0AvlO64xJLb3SdFNKZGcyWjFnOWVlMjlYUjVNeW10ekE&usp=sharing
Profiency rates by neighborhood cluster: https://app.box.com/s/lrvjw9hvdgvtti5vih1j
 
1339 days ago
Unfiled. Edited by Harlan Harris , Chris Given 1339 days ago
Harlan H ODD DC Edu Presentation Nodes
The plan: Create notes here on things to talk about for a presentation to domain newbies. Let's do this as an outline format, with some web pages to walk through, not a script...
 
  1. the school system
  1. history
Chris G
  1. dc politics 101
  1. introduction of charters
  1. where are we going?
Harlan H
  1. demographic challenges
  1. choosing schools
  1. school boundaries and feeder patterns
Chris G
  1. huwhaa?
  1. Student Assignment and School Boundaries Review Process
  1. what types of data are collected
  1. assessments (DC CAS, NAEP, LEA-specific assessments)
  1. attendance/enrollment
  1. discipline/school climate (not much)
  1. others
  1. what's available where
  1. OSSE/LearnDC
  1. PCSB
  1. others
Harlan H
  1. open data catalogs
  1. advocacy groups
  1. 21st Century Schools Fund
  1. DC School Reform Now
  1. Reading list
  1. WaPo
  1. Greater Greater Education
  1. EdWeek?
  1. others
 
 
 

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