Module Code: |
H8DG |
Long Title
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Data Governance
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Title
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Data Governance
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Module Level: |
LEVEL 8 |
EQF Level: |
6 |
EHEA Level: |
First Cycle |
Module Coordinator: |
Sophie Flanagan |
Module Author: |
ORLA LAHART |
Departments: |
School of Computing
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Specifications of the qualifications and experience required of staff |
Master’s and/or PhD degree in computing or cognate discipline. May have industry experience also.
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Learning Outcomes |
On successful completion of this module the learner will be able to: |
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Learning Outcome Description |
LO1 |
Analyse the concepts of data governance, data management and data strategies and critically evaluate them in the context of organizational data policies, processes and procedures. |
LO2 |
Comprehend the regulatory and legislative requirements around data management and stewardship, synthesize their implications for organisational data management, processes and procedures, and apply their implications for the collection, storage, use and dissemination of organizational data resources. |
LO3 |
Comprehend the ethical underpinnings of good data governance, in the context of an overall framework for data management and apply the resultant framework to emerging areas of technological development |
LO4 |
Analyse the range of internal and external stakeholders concerned with the design and implementation of an effective data governance strategy. Comprehend and evaluate the role and responsibilities across different organizational levels and functional areas related to the data management and governance functions such as Chief Data Officer. |
LO5 |
Apply a range of tools and techniques for the effective governance, management integrity and security of data resources in an organizational context and evaluate their application in the context of specific case studies and scenarios. |
Dependencies |
Module Recommendations
This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
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No recommendations listed |
Co-requisite Modules
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No Co-requisite modules listed |
Entry requirements |
Use programme level text
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Module Content & Assessment
Indicative Content |
Introduction to Data Governance
Course overview; Purpose of Data Governance; Evolving role of data in a modern organisation; Data risks; Costs, Benefits and ROI from data holdings; Relationship to other course modules.
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Concepts and Definitions
To cover the scope of Data Governance along with an explanation of other related concepts such as Data Strategies, Principles and Frameworks. Will consider Data Governance from Strategic, Functional and Operational/Technical levels within an organisation.
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Stakeholders, Roles and Responsibilities
To include information on the range of stakeholders (internal, external) that an organisation should be aware of as well as a more detailed exposition of the roles and responsibility of a range of data professional roles within an organisation.
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Data Protection Legislation and Regulatory environment
An outline of the key legislative and regulatory measures across a range of jurisdictions and the role of data protection authorities. Evaluate the implications of legislation for data professionals as well as illustrative Case Studies.
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Ethical considerations for data analytics
Rationale for studying ethical considerations in Data Governance together with exposition of ethical dilemmas, frameworks and case studies for addressing them.
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Data Governance – contemporary case studies
A range of contemporary data governance issues covering data protection, usage of social media data and technical area. A guest speaker with expertise in the area will make a keynote presentation (subject to availability).
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Assessment Breakdown | % |
Coursework | 100.00% |
AssessmentsFull Time
Coursework |
Assessment Type: |
CA 1 |
% of total: |
30 |
Assessment Date: |
n/a |
Outcome addressed: |
1,2 |
Non-Marked: |
No |
Assessment Description: Group assignment where each team has to argue a proposition related to the items covered in the first part of the course in a debate style format. |
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Assessment Type: |
CA 2 |
% of total: |
70 |
Assessment Date: |
n/a |
Outcome addressed: |
1,2,3,4,5 |
Non-Marked: |
No |
Assessment Description: Application of learning from course to analyse a case study organisation and design a data governance framework and strategy through the preparation of a report and infographic. |
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No End of Module Assessment |
Reassessment Requirement |
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.
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Reassessment Description This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.
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NCIRL reserves the right to alter the nature and timings of assessment
Module Workload
Module Target Workload Hours 0 Hours |
Workload: Full Time |
Workload Type |
Workload Description |
Hours |
Frequency |
Average Weekly Learner Workload |
Lecture |
Weekly Lecture |
24 |
Every Week |
24.00 |
Tutorial |
Weekly Lab |
12 |
Every Week |
12.00 |
Independent Learning |
Research |
89 |
Every Week |
89.00 |
Total Weekly Contact Hours |
36.00 |
Module Resources
Recommended Book Resources |
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Harkish Sen. (2019), Data Governance, 1. 6, Technics Publications, p.208, [ISBN: 1634624785].
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Mike Loukides,Hilary Mason,Dj Patil. (2018), Ethics and Data Science, 5, [ISBN: 9781492078227].
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Dama International. DAMA-Data Management Body of Knowledge, 2nd. 17, p.628, [ISBN: 9781634622349].
| Supplementary Book Resources |
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Katherine O'Keefe,Daragh O Brien. (2018), Ethical Data and Information Management, Kogan Page, p.344, [ISBN: 0749482044].
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Rupa Mahanti. (2019), Data Quality: Dimensions, Measurement, Strategy, Management and Governance, Quality Press, p.526, [ISBN: 9780873899772].
| Supplementary Article/Paper Resources |
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Fiesler, Casey; Proferes, Nicholas. (2018), “Participant” Perceptions of Twitter
Research Ethics, Social Media + Society, Vol. 1, Issue 4, p.14, [ISSN: 2056-3051],
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Samuel, Gabrielle Derrick, Gemma E. van
Leeuwen, Thed. (2019), The Ethics Ecosystem: Personal Ethics,
Network Governance and Regulating Actors
Governing the Use of Social Media
Research Data, Minerva, 57, [ISSN: 15731871],
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Siau, Keng Wang, Weiyu. (2020), Artificial Intelligence (AI) Ethics, Journal of Database Management, 31, [ISSN: 1063-8016].
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Kemper, Jakko Kolkman, Daan. (2019), Transparent to whom? No algorithmic
accountability without a critical
audience, 22.
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Hand, David J.. (2018), Statistical challenges of administrative
and transaction data, Journal of the Royal Statistical
Society. Series A: Statistics in Society, 121, [ISSN: 1467985X].
| Other Resources |
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[Website], Myles Suer, ITIL, and Roger Nolan
(2015).. (2015), Using COBIT 5 to Deliver Information and
Data Governance, 2015,
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[Website], Chrisden Hart. (2018), new-european-union-data-law-gdpr-impacts
-are-felt-by-largest-companies-google-fa
cebook,
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[Website], Association of Computing Machinery. (2018), ACM Code of Ethics and Professional
Conduct, Association of Computing Machinery,
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[Website], Committee on Professional Ethics of the
American Statistical Association. (2018), Ethical Guidelines for Statistical
Practice, American Statistical Association,
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[Website], IEE. IEEE Code of Ethics, IEEE,
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[Website], UK Government. (2018), Data Ethics Framework, UK Government,
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[Website], UK Government. (2018), Data Ethics Workbook, UK Government,
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[Website], European Union. (2016), General Data Protection Regulation
(GDPR), European Union,
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[Website], Fairness, Accountability, and
Transparency in Machine Learning. Principles for Accountable Algorithms
and a Social Impact Statement for
Algorithms, Fairness, Accountability, and
Transparency in Machine Learning,
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[Website], How To Break Anonymity of the Netflix
Prize Dataset,
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[Website], Google. Artificial Intelligence at Google: Our
Principles, Google,
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[Website], Daisuke Wakabayashi. (2018), California Passes Sweeping Law to
Protect Online Privacy, New York Times,
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[Website], The Trustees of Princeton University. (2020), Princeton Dialogues on AI and Ethics
Case Studies,
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[Website], Commission of the EU. (2020), Data protection as a pillar of citizens’
empowerment and the EU’s approach to the
digital transition - two years of
application of the General Data
Protection Regulation, Commission of the EU,
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[Website], Jamie Carter. (2016), Beyond the Atlantic: Data privacy laws
around the world, TechRadar,
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