Occupy Sandy Data: Highlights and Preliminary Findings

With the aim of quantifying and visualizing the impact of the Occupy Sandy relief effort the Occupy Sandy data project began with an Open Data Day event on Feb 23rd, and work continued work at the hackathon

Physically collecting, digitizing, and sanitizing the various data sets from four different network sites (SI, Rockaways, Red Hook, and NJ) has been an incredibly challenging task on many levels.

Some of the cleaned and processed Occupy Sandy data was used for the Data Anywhere project.  Using the similar infrastructure and tool as the data sharing component of Data Anywhere, the aim is to develop longer term data solution for addressing some of the data management issues plaguing #OccupySandy and other relief organizations.  More details can be found here.

Other data was used for analysis.  For now, some highlights and preliminary findings from our partially processed and cleaned data collection are:

Over 300 assessment forms entered for the Rockaways and NJ Occupy Sandy network sites entered by participants and community volunteers in preparation for at at the Occupy Data hackathon.

Over 27,000 meal requests were filled by the Occupy Sandy Kitchen from Nov. 23rd through Jan 28th.

Over 60 New Yorkers volunteered through a web-based form to open their homes to strangers needing shelter right after the storm.

Almost 3,400 SI, Brooklyn, Queens and NJ residents assessed by Occupy Sandy network volunteers at only four network sites.  After eliminating incomplete records:

  • 25% percent of households with at least one senior reported medical issues that requiring assistance from a medical professional or prescription drugs
  • the most urgent needs among residents were financial assistance, repairs for water related damage, and basic supplies such as food and clothes, and at least one of these needs was reported by more than half of all residents surveyed.

Stay tuned for more updates!  Over the next few weeks we’ll continue to dive into what can seem like nebulous file directories looking for more data goodies, and map variables across multiple data sets for site and multi-level statistics and visualizations.