The Art and Science of Big Data Education Anne L. Washington, PhD School of Policy, Government, and International Affairs George Mason University Wed August 12 2015 BDA EdCon 2015 - AMCIS 2015 Big Data and Analytics Education Conference 2015 21st Americas Conference on Information Systems 2015 -- Art and Science of Big Data Education - washingtona@acm.org 1
Agenda Creating data-driven managers Open data workshops experience Recommendations for training 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 2
Will history repeat itself? Ross & Weill (2002) Strategy without data Technology without strategy Management without authority Activity without productivity 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 3
Managers as data consumers Request data analytics Interact with data products Supervise data scientists 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 4
How to create data-driven managers? Training non-stem users Big data with everyday knowledge No private identifying information Complex but not complicated Domain neutral 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 5
Open data Sharing Licensing Technical standards Open government data documented mandated across time 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 6
Political Informatics Open government data for innovative academic research Social science scholars Computer scientists Co-PI John Wilkerson, University of Washington 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 7
Grant PI-NET Poli-Informatics Research Coordination Network Funded under NSF #1243917 http://poliinformatics.org Data challenges leading to workshops and training 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 8
EXPERIENCES 2015 -- Art and Science of Big Data Education - washingtona@acm.org 9
Data Challenges DC Financial Crisis Seattle Climate Change 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 10
Examples Transcripts Geospatial data Inter-related Documents 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 11
From data challenges to workshops Focus on interpretation 1. Context 2. Methods 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 12
1 Context What questions can data answer? Idealistic products Technical possibilities Data arrangement and connection Subject expertise 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 13
2 Method What questions can we ask today? Realistic implementation Technical strength / weakness Data category limitations Skills 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 14
RECOMMENDATIONS 2015 -- Art and Science of Big Data Education - washingtona@acm.org 15
Workshop Outcomes Broad inclusive conversations Common ground Knowledge-sharing Critical thinking 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 16
Challenges for big data training Thinking at scale Thinking across time Thinking like a network Leveraging technology limitations Working with data realities 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 17
Questions for interpretation When are data? (Borgman, 2015) Who are data? How are data? Why are data? What are data? 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 18
Conclusion Art of data Observations not facts Categories in context Science of algorithms Certainty Consistency 2015 -- Art and Science of Big Data Education - washingtona@acm.org >> 19
The art and science of big data education Anne L. Washington, PhD http://washington.gmu.edu washingtona@acm.org Assistant Professor School of Policy, Government, and International Affairs Organizational Development & Knowledge Management George Mason University, Arlington VA 2015 -- Art and Science of Big Data Education - washingtona@acm.org 20