Richard J Self - University of Derby 1 Governance Strategies for the Cloud, Big Data and other Technologies in Education Richard J Self BA LLM MBCS FHEA Senior Lecturer in Analytics and Governance University of Derby

Context Emerging Technologies in Education Critical Governance Issues Data Protection Regulations Risks to Human Current Frameworks ISO 27K, COBIT, etc….. Additional factors 12Vs of Big Data Technologies in Education Key Governance Questions 2Richard J Self - University of Derby

Gartner Hype Curve Richard J Self - University of Derby

Gartner Hype Curve Richard J Self - University of Derby 7de80268

Emerging Technologies in Education Examples Evaluated 3D Printing Google Glass Social Networks Data Analytics (Learning and Academic) Biometrics Based on Student research and publications 5Richard J Self - University of Derby

Governance “Doing the right thing in the right way at the right time with the right resources to the right quality in the right place for the right reasons” (Self, Self and Chang, 2012) 6Richard J Self - University of Derby

Governance Frameworks ISO 27k ISO27001 – ISMS Certifiable process ISO Code of practice for information security controls Critical questions Completeness? Generic Big Data Issues – extra needed? 7Richard J Self - University of Derby

ISO Key Controls 1. Information security policies 2. Organization of information security 3. Human resource security 4. Asset management 5. Access control 6. Cryptography 7. Physical and environmental security 8. Operations security 9. Communications security 10. System acquisition, development and maintenance 11. Supplier relationships 12. Information security incident management 13. Information security aspects of business continuity 8Richard J Self - University of Derby

12 Vs of Big Data 3Vs Volume (size) Velocity (speed) Variety (sources/format) 9Vs Governance Variability (temporal?) Value (to whom?) Veracity (truth) Validity (applicable) Volatility (temporal) Verbosity (text) Vulnerability (security) Verification (trust?) Visualisation (presentation) 9Richard J Self - University of Derby

Volume (S, G) How much? Who? How? Storage Dangers Technology? 10 MountainsOceans (Teahupo’o) Brian Bielmann Wikimedia

Velocity (S, G) Infrastructure Need for immediacy? Time to analyse How fast? 11 TwitterWikimedia

Variety (T, S, G) What? Connections? Similarity? Original purpose? Data Structures Ownership 12 ges.wordpress.com/ cell-phones/ Twitter Fruit salad?Choices

Variability (T, S, G) Consistency In-consistency Periodicity Data Analyses Predictions 13 Frankfurt weather forecastseasons Wikimedia

Value (G) Define Value! Monetary? Understanding? Whose value? Functionality? Convenience? Questions Answers? 14 ApplicationsGold crystals Wikimedia

Veracity (T, S, G) Truthful when? Identifying the dross? Data Algorithms Data cleansing 15 YouGov Wikimedia We know we errFinding the Truth

Validity (E, T, S, G) Context? Where? When? Correlation or Causation? Data Algorithms / Models Prediction 16 UK Penny Black Wikimedia Logical Deduction / Induction Johnson, 2008

Volatility (T, E, S, G) How quick? Value left? Data Predictions Sources of expertise 17 Snapchat Wikimedia Salt Pans in France

Verbosity (T, G) Context Meaning / semantics Grammar Syntax Redundant Knowledge 18

Vulnerability (T, E, S, G ) Legal (e.g. DPA and Right to be Forgotten) Reputation Financial Data Policies Processes Access Who and what skills? 19 OWASP: relationship between threat agent and business impact Wikimedia

Verification (T, E, S, G) How? Reliability? Context? Data Algorithms and models 20 1 st Japanese Passport 1866Digital Signature process Wikimedia

Visualisation (T, E, G) Manipulation 2D / 3D Video Who chooses? Guidelines and standards? 21 As presented by the UK Treasury As corrected by Sir Andrew Dilnot Log scale Breached Official Guidelines

Case Studies Contributing Student Authors See Paper for references Richard J Self - University of Derby 22

3D Printing A. G. Aladawi, G. Allen, A. Bensbiet, D. Silva Caires Richard J Self - University of Derby 23

3D Printing Critical Risks Breach of IPR Printing dangerous / illegal items Solvents Vulnerability and Verification Critical Controls Access controls and logs Teaching ethics and civil / legal responsibilities 24Richard J Self - University of Derby

Google Glasses F. Kalra, L. Mawhinney Richard J Self - University of Derby 25

Google Glass ( use by academics) Critical Risks Privacy and Consent Communication with Smart Device Google Cloud (DPA 1998) Personal Safety Vulnerability and Verification Critical Controls Acceptable Use policy (informed consent required) Cloud storage policies 26Richard J Self - University of Derby

Social Networks M. Al Yousif, A. Clark, A. Nagra, P. O’sullivan K. Samarah Richard J Self - University of Derby 27

Social Networks Context Group work and staff / student channel Critical Risks IPR, cyber-bullying, invasion of privacy and sharing information Vulnerabilities and Veracity Critical Controls Private walled-garden Strict moderation 28Richard J Self - University of Derby

Data Analytics (Learning and Academic) A. Clark Richard J Self - University of Derby 29

Data Analytics (Learning and Academic) Context Sentiment analysis Predictive analysis (achievement) Critical Risks Use of social media, irony, semantics? Data Protection Veracity, Volatility, Vulnerability and Verbosity Critical Controls DPA compliance Verification of sentiment analytics algorithms 30Richard J Self - University of Derby

Biometrics M. Haroon, G. Ali Raza, Richard J Self - University of Derby 31

Biometrics Context Personal Authentication Critical Risks False Positive / Negative rates Enrolment DPA and security Veracity, volatility, vulnerability, velocity Critical Controls DPA compliance policies 32Richard J Self - University of Derby

Conclusions The 12Vs of Big Data Add value to ISO based Governance Can identify critical issues in applying emerging technologies in HE Can help develop understanding of suitable controls 33Richard J Self - University of Derby