Knowledge is Power

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Data and The Crowd

To assist with the organization and governance of Daemo and the Research cohort, transparency in data is critical. With so many channels of real time data, ideas, information and content flowing at a 24/7 clip, it is nearly impossible to manage it all, process it and identify and relate to those with shared viewpoints. Hence we propose a data gathering project in which we leverage the cohorts Data Scientists and those interested in Data analytics to build a dashboard/portal and or a data depository. By collecting data from the following: Daemo, Badge/Page rank, Git Hub, Wiki pages, Paper submittal word count, Hangouts, Meteor, Survey’s, Slack, Blossom/Idea bot, etc. we can achieve multiple goals simultaneously:

  • 1. We can help teach the cohort to extract data as part of a research agenda. We can teach coding, data mapping, and other skills crowd researchers need.
  • 2. We can present the real time data to the cohort. Such a portal or dashboard will help with knowledge share, continuity, orientation, project management and other community building benefits.
  • 3. Data collection will provide the raw material for paper writing. Subjects that can help the cohort better define the ecosystem of crowd research. We can define/own our own activities and investigate themes that differentiate crowd research from other crowd activities.
  • 4. We can consider using the cohort to build research/transactional tools for crowd research/crowd sourcing.

So, how do we execute?

  • a. We define milestones and fold into schedule;
  • b. in parallel with identifying participants, their areas of interest and conduct a skills census. Structure folks using DRI format, though this might be an opportunity to organize a cadre as a guild. Break tasks into HITS to run through Daemo, and rapid prototype solutions, tools , etc.
  • c. We can simultaneously engage the cadre in needfindings, solutioning and engage them in the organizational themes of crowdresearch….
  • d. When the data and theoretical/needfinding efforts collide we can write papers and advance the general understand of crowd research

Goals:

  • 1. Set the gold standard for tools and precedents for scalable crowdresearch efforts.
  • 2. Improve retention of researchers with interest in data science and machine learning.

Link

http://crowdresearch.stanford.edu/w/img_auth.php/9/95/Data_Dashboard.pdf