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A collaborat ive environmen t for geography THE BIG BOARD

The Big Board

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The Big Board. A collaborative environment for geography. A motivating example. A cross institutional team is assembled for a community-focused study of the historical residential segregation of the city of Asheville N.C. ( including redlining and urban renewal}: - PowerPoint PPT Presentation

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Page 1: The Big Board

A collaborative environment for geography

THE BIG BOARD

Page 2: The Big Board

A cross institutional team is assembled for a community-focused study of the historical residential segregation of the city of Asheville N.C. (including redlining and urban renewal}: Asheville (Priscilla Ndiaye, Southside Advisory Committee

chair) Duke (HASTAC, iiD) UNC (SALT lab) RENCI

Funded by: NARA / NSF Duke Bass Connections / Duke iiD

A MOTIVATING EXAMPLE

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Study of urban renewal involves compiling Pictures Testimony Primary sources from city records Census data Crowdsourced data about individual sites

And putting it together

THE PROBLEM

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Maps are a natural method for understanding the changes across entire neighborhoods browsing the available records

But GIS systems fall short on Displaying unstructured data Allowing interactive collaboration

HOW TO PUT IT TOGETHER?

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A collaborative mapping platform focused on Real-time collaboration Linking together unstructured data Providing a platform for domain specific extensions /

plugins that aid collaborators

THE BIG BOARD

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OVERLAY DATA FROM THE WEB

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DRAW, ADD, EDIT, SEARCH ANNOTATIONS

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PERSISTENT, INTERACTIVE CHAT-ROOM

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DISPLAY AND COMPOSE

UNSTRUCTURED DATA IN A

WORDPRESS-LIKE ENVIRONMENT

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RENCI Geoanalytics is a cyberinfrastructure for geographic data. Digest data from disparate data types Serve unified API through OGC web-services Publish data through a CMS like interface Provide styled maps Provide framework for interactive web and mobile

application development using geography

ENABLING TECHNOLOGY: GEOANALYTICS

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Big data Implement a few methods in Python, adapt to a new

datatype NoSQL stores like MongoDB, Cassandra, Redis Specialized data e.g. timeseries on irregular grids

Native support for time-series and versioned dataWeb and mobile-web infrastructure

Quickly develop geography-enabled web appsAnalytics

Use an interactive Python environment over the web to explore data with MatLab like tools

GEOANALYTICS’ STRENGTHS

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Decision support for Emergency management Public policy Public health Epidemiology

OTHER APPLICATIONS OF THE BIG BOARD