Data Science for RDA Climate Change Data Challenge and Meetup Dr. Brand Niemann Director and Senior Data Scientist/Data Journalist Semantic Community Data Science Data Science for RDA Climate Change Data Challenge July 15,

Announcements The 6th Plenary RDA hosted in Paris from September 2015, features a special focus on research data for climate change, leveraging on the UN Climate Change Conference (COP21) to be held in Paris in December As a part of this special focus Cap Digital & RDA have created a special Data Challenge designed to connect Climate Change related Data Sets with startups, SMEs and larger organizations with practical application for these data. Please join the NITRD FASTER Community of Practice on July 15, 2015, for an informative presentation and discussion with Dr. Francine Berman, Chair, RDA/US and Edward P. Hamilton Distinguished Professor of Computer Science, Rensselaer Polytechnic Institute. Dr. Fran Berman will describe the Research Data Alliance (RDA) and its community, and give a look ahead at future directions for the RDA. In 2013, the Research Data Alliance (RDA) was formed to build and adopt infrastructure that accelerates data sharing world-wide. Two years later, the organization has attracted nearly 3000 members from over 100 countries and all sectors. The precipitous growth and enthusiasm for the RDA emphasizes the global need for data infrastructure and coordination, and indicates the community’s high expectations that RDA has the potential to meet those needs. 2 See slides and bookletslidesbooklet

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5 Data Science for RDA Climate Change Data Challenge Goals: Goal 1: Digital Catalog Goal 2: Data Audit Goal 3: Individual Data Sets in Spotfire Goal 4: Integration/Applications Goal 5: Meetups/Data Science Publication/MOOCs

6 SpreadsheetSpreadsheet: Digital Catalog

7 Web PlayerWeb Player: Goal 1 Digital Catalog

8 SpreadsheetSpreadsheet: Data Audit

9 Web PlayerWeb Player: Goal 2 Data Audit 1.I could not readily find the actual data sets for 18 of the 64 data sets. 2.The URL for the very important DOE Buildings Data Book does not work (I think this is being revised or removed permanently) of the remaining USCDINASA 40 data sets come from the National Transportation Atlas Database. Why not use all 36 as a more authoritative and consistent data set? 4.Why was a contractor brought in to manage the White House Climate Data Initiative and is now a private consultant on climate data (Climate Data Solutions LLC), listed as the contact person 5.The obvious other data that can be used is the 557 data sets at Data.gov/Climate and the data sets in the President’s National Climate Assessment, which many others and our Meetup have already worked with. 6.I could not find the 3 data sets from Cap Digital (numbers 22-24), the sponsoring organization, and their web site Cannot Be Translated into English.

10 Web PlayerWeb Player: Goal 3 Individual Data Sets in Spotfire Example Data Set 64: USGS Small-scale Dataset - Railroad and Bus Passenger Stations of the United States Shapefile

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12 SpreadsheetSpreadsheet: National Transportation Atlas Database

13 Data Science for the National Transportation Atlas Database: Inventory Amtrak Stations (ZIP - 69KB) Border Crossing Ports (ZIP - 24KB) Data of dams 50 feet or more in height (ZIP - 799KB) Railroad Grade Crossings (ZIP MB) My Note: Two Shape Files Travel Monitoring Analysis System (ZIP - 1.1MB) Freight Analysis Framework, version 3.4 (ZIP MB) Hazardous Material Routes (ZIP - 8.9MB) Highway Performance Monitoring System (ZIP - 795MB) My Note: Problem Reading Shape File-Contacted BTS National Highway Planning Network (ZIP MB) Railway Network (ZIP MB) Web PlayerWeb Player: : Goal 3 Individual Data Sets in Spotfire-NTAD Inventory

14 Web PlayerWeb Player: Goal 3 Individual Data Sets in Spotfire-NTDA-Amtrak Stations

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Conclusions and Recommendations Dr. Renata Rawlings-Goss, Big Data AAAS Fellows at NSF:Big Data AAAS Fellows at NSF I am working with OSTP to coordinate a grassroots data science Meetup organizers meeting this fall (November 6-7, 2015). We have currently coordinated conference calls with large data science meetups ( ,000 members) around the country. I think it would be particularly fruitful to have future discussion with you about the role of Federal Big Data Working Group. Your work sounds very connected to what we are thinking of for meetup groups. My Suggestions: Involve the NSF Data Science / Big Data Community in the NSF EarthCube Community. Data Communities need to collaborate with Data Scientists (e.g., our EarthCube Data Science Publications).EarthCube Data Science Publications Have the largest Data Science meetups mine our Meetup content for government data sources (our GitHub and Data Hub), government data problems to work on, and partner with government agencies to co-host Meetups (e.g., our USDA Data Science MOOC).USDA Data Science MOOC Participate in our new collaboration with RDA on Data Science for RDA Climate Change Data Challenge and our Federal Big Data Working Group Meetups!Data Science for RDA Climate Change Data ChallengeFederal Big Data Working Group Meetups 16