Big Data for Cleveland

ESE 697: Big Data and Emerging Cities

 

Presented by Alex Pawlowski

interact at slides.com/alexpawlowski/sci-bigdata

Big data

  • sufficiently large collection of information to require different tools to handle its complexity in order to reveal new patterns or behaviors of interest

Structured vs. unstructured

structured

  • focus on surveying
  • been collecting since 1790

unstructured

  • focus on software tools 
  • phone data → traffic congestion

data on its own has little value, each kind needs definition 

Goals

  • understand Cleveland's data needs
  • assess data Cleveland has
  • develop tools and methods that Cleveland staff can use
  • develop data methods other emerging cities can use

plan

  • review of how big data is used in small cities
  • assess and communicate community sentiment with social media
  • scenario-based data driven understanding of future growth enhancing mobility

 

SO FAR

  • Cleveland Social Media Accounts:

TWEETS

  • develop 4 scenarios of analysis to enhance different mobility modes:
    • today
      • baseline mobility patterns
    • 2035:
      • business as usual 
      • ↑ mobility + accessibility
      • car-free intercity zone

@planclevelandtn

/planclevelandtn

SCI Big Data for Cleveland

By Alex Pawlowski

SCI Big Data for Cleveland

Short summary of where the ESE 697 class has explored in assisting Cleveland to use data they have and what kinds of data they should seek to help their resident's needs for a sustainable future.

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