TO AN ORGANIZATION Combining Strategy, Data Science and Information Architecture to Transform Data to Knowledge David Meza Chief Knowledge Architect NASA Johnson Space Center Connected Data London July 12, 2016
data, lessons learned, scientific research, medical analysis, geo spatial data, IT logs, etc., are stored nation wide • The data is growing in terms of variety, velocity, volume, value and veracity • Accessibility to Engineering data sources • Visibility is limited
implementing, and applying the intellectual infrastructure of organizations. • What is an intellectual infrastructure? • The set of activities to create, capture, organize, analyze, visualize, present, and utilize the information part of the information age.. • Information + Contexts = Knowledge • Information Architecture + Knowledge Management + Data Science = Knowledge Architecture • KM without applications is empty (Strategy Only) • Applications without KA are blind (IT based KM) • Data Science transforms your data to knowledge 8
have access to all the world’s information. This has never before been possible. Why is ubiquitous information so profound? It is a tremendous equalizer. Information is power.” ERIC SCHMIDT (FORMER CEO OF GOOGLE)
work previously done. Source: National Board of Patents and Registration (PRH), WIPO, IFA 54% of decisions are made with incomplete, inconsistent and inadequate information Source: InfoCentric Research Opportunity 1: Search in the Enterprise 46% Workers can’t find the information they need almost half the time. Source: IDC
• Master Data Management Plan is essential • Identify Critical Data • Develop Standards for Government and Contractor created data • Analytics is essential • Meta Data
that documents are mixtures of topics, where a topic is a probability distribution over words. LDA Model from Blei (2011) David Blei homepage - http://www.cs.columbia.edu/~blei/topicmodeling.html Blei, David M. 2011. “Introduction to Probabilistic Topic Models.” Communications of the ACM.
faster and more informed decision-making • Leverage lessons of the past to minimize waste, rework, re- invention and redundancy • Reduce the learning curve for new employees • Enhance and extend existing content and document management systems