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Data Science for Migration Data

Data Science for Migration Data

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Data Science for Migration Data

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  1. Data Science for Migration Data Dr. Brand Niemann Director and Senior Data Scientist Semantic Community November 3, 2013

  2. Background • Key Questions: • Do you write code? NO • Work with data?  YES • Research migration issues? NOT YET • Work with migrants? NO • Report migration news? NO • You are invited to  our Datafest on November 2-3.  THANK YOU! I AM SURPRISED GIVEN MY REPLIES  • You can participate in-person or virtually. VIRTUALLY • The event will focus on  immigration to North America and Europe and human flows between and within countries in Latin America as well as on general population shifts within the United States and Canada. • Let's leverage the surge in mobile, social, computing power,  data analytics and address  the challenges and opportunities of migration in innovative ways!

  3. November 2, 2013 Requirements • Your project's name: Data Science for Migration Data • Your team's name: Semantic Community • Location: Fairfax Virginia • A brief description of what you are working on Data Science for Migration Data • A list of people on your team Brand Niemann Sr. and Brand Niemann Jr. • What prize category you think your project fits in (both local and global awards) Both • What you are starting with: existing codebase, libraries, etc. No, just the data and Spotfire

  4. AmericasDataFest: Migration My Note: Make this a Data Science Knowledge Base!

  5. Step 1: Knowledge Base in MindTouch My Note: The entire platform can be searched. My Note: The Semantic Community Platform includes MindTouch (Wiki), Spotfire (Analytics), and Be Informed (Be Free). This page can be search by Google Chrome Find.

  6. Step 2: Spreadsheet of Projects My Note: See What My Competitors Are Doing! My Note: All of these spreadsheets can be searched.

  7. Step 3: Spreadsheet of Data Sources My Note: Surveying and Prioritizing the Data Sources! My Note: The Semantic Community approach is consistent with the European ISA Recommended URI Design and Management Principles.

  8. Step 4: Select Data Sources My Note: Screen Scrape, Download, & Prioritize

  9. Step 4: Knowledge Base in Spotfire My Note: Selected Data Sources and Their Visualizations. My Note: These Visualizations Are Dynamically Linked.

  10. November 3, 2013 Requirements • A summary of your work: • For projects focused on data and data analysis: A step-by-step explanation of how you reached the result(s) My Note: See Slides 5-9. • Any links such as to a code repository, Google docs, etc. My Note: See Slides 5-7 & 9. • Screenshots will be much appreciated. My Note: See Slides 5-9.