Computer Science

COMM412DA - Data in Business and Society (2023)

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MODULE TITLEData in Business and Society CREDIT VALUE15
MODULE CODECOMM412DA MODULE CONVENERUnknown
DURATION: TERM 1 2 3
DURATION: WEEKS 11
Number of Students Taking Module (anticipated) 90
DESCRIPTION - summary of the module content
Data science is revolutionising many aspects of society, with major impacts on industry, business and the public sector. These rapid changes raise many important issues concerning ethics, privacy and governance. In this module you will learn about the social context of data science and how data is used to inform business practices. You will also consider the ethical issues that can arise from machine learning and analysis of “big data”, as well as the legal frameworks and legislation relevant to collection and use of data by organisations. This module provides essential background for any data scientist or data manager whose use of data might affect people or organisations.
 
Pre-requisites: COMM414DA Introduction to Data Science (Professional) 
Co-requisites: None
 
This module is a part of the dual-qualification MSc Data Science (Professional) / Level 7 Research Scientist Apprenticeship programme. It cannot be taken as an elective by students on other programmes. 
 
The apprenticeship standard and other documentation relating to the Level 7 Research Scientist Apprenticeship can be found here: https://www.instituteforapprenticeships.org/apprenticeship-standards/research-scientist-v1-0
 
AIMS - intentions of the module
This module aims to:
 
— Explore how information and analytics can support the development of strategy in organisations, in ways that are responsive to broader social concerns in the UK and internationally;
— Encourage critical approaches to data definition and collection methodologies with the aim of creating accurate links between real-world problems and data driven solutions;
— Enhance responsiveness to data protection and dissemination policies at local, national and international level;
— Provide skills in engaging data providers and customers to ensure compliance with regulations and legal systems;
— Ensure awareness of social embedding of data collection, analysis and re-use practices, with attention to potential challenges in advertising, implementing and assessing data science services (and particularly Big Data) for the general public as well as specific stakeholders (government, local authorities, competitors in industry, lobby groups).
 
The module will draw on recent scholarship in data studies and case studies based on a variety of contexts. The module will offer an opportunity to acquire knowledge of data handling practices and their implications for business, and enhance data management skills for those pursuing careers in planning and analytics. The module provides training in ethical and societal implications of data management strategies, and applications within business planning.
The module will engage you in independent research to produce an individual essay reflecting on data management issues within your own business.
 
In addition to its academic aims as part of the programme, this module has specific aims as part of the Level 7 Research Scientist Apprenticeship. The full list of Knowledge, Skills and Behaviours that must be demonstrated to complete the Apprenticeship can be found here: https://www.instituteforapprenticeships.org/apprenticeship-standards/research-scientist-v1-0
 
This module will deliver content that may be used to evidence the Knowledge, Skills and Behaviours set out below. Primarily: K1, K3 and K6. Secondarily: S4, S6.
 
Knowledge (K), Skill (S) or Behaviour (B)
K1: Subject specific knowledge: A deep and systemic understanding of a named / recognised scientific subject as found in an industrial setting, such as biology, chemistry or physics, found in the nuclear, food manufacture, pharmacology or energy production sectors, at a level that allows strategic and scientific decision making, while taking account of inter relationships with other relevant business areas / disciplines.
 
K3: Ethics, regulation and registration: All current relevant national and international regulations needed to carry out the role. This will include scientific regulation, health and safety and laboratory safe practice, anti-bribery and anti-corruption. Ethical scientific practice and the employers processes and procedures surrounding professional conduct. How to identify, record, mitigate and manage risk. The impact of failure and how to manage risk on the business. The benefits of equality of diversity in the workplace.
 
K6: Data management: How to safely store and handle data in line with national and international data protection and cyber security regulations that apply to the role. How to manage and store data in line with employer processes and security approach. How to create an appropriate data management plan.
 
S4: Communication Skills: Write extended reports and critique others' work across a range of documentation, e.g. protocols, consent forms and scientific reports. Deliver oral presentations and answer questions about their work and/or the work of their team. Utilise interpersonal skills, communication and assertiveness to persuade, motivate and influence. Discuss work constructively and objectively with colleagues customers and others; respond respectfully to and acknowledge the value of alternate views and hypothesis.
 
S6: Critical Thinking: Conceptualise, evaluate and analyse information to solve problems.
 
INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)
On successful completion of this module you should be able to:
 
Module Specific Skills and Knowledge
1. Understand key terms and concepts in data science and information management and be able to relate these to a typical business situation.
2. Critically evaluate current approaches used for collection, management, communication and analysis of commercial, operational and sustainability data, and how this data is used to support decision-making.
3. Apply ‘Design Thinking’ techniques to the analysis of specific business challenges and use these to identify required data and information flows.
4. Develop and use communication techniques to share original content and insight with a general management audience.
5. Understand how to manage data storage, archiving, dissemination and re-use in order to improve long-term sustainability and customer base of business.
6. Understand how current legislation and intellectual property regimes affect data management practices.
 
Discipline Specific Skills and Knowledge
7. Apply theoretical arguments, frameworks and concepts from data studies to the analysis of business and management scenarios. Link theoretical constructs and organisational practices.
8. Critically articulate how different organisations and individuals approach practice and why differences exist.
9. Demonstrate a critical awareness of the contributions of different stakeholder perspectives and data management practices to delivering sustainable solutions.
10. Demonstrate an integrated and holistic perspective when generating solutions.
 
Personal and Key Transferable / Employment Skills and Knowledge
11. Analyse and draw conclusions from unstructured problems and scenarios.
12. Demonstrate analytical skills both with regard to data and to the design of information flows in organisations.
13. Demonstrate cognitive skills of critical and reflective thinking.
14. Demonstrate effective independent study and research skills.
SYLLABUS PLAN - summary of the structure and academic content of the module
The module will cover:
 
— How businesses use data to build, understand and report their strategic goals 
— Applying current concepts in data and analytics to real examples
— Using ‘Design Thinking’ to create information management systems
— Understanding the legal, ethical and governance considerations around use and analysis of data in social and business contexts. Specific topics will include:
— Data projects. Using design thinking techniques to understand organisational problems in data management and scope solutions to these. 
— Workshop on “what are data?”. Big data, small data and the challenge of capturing the long tail of research.
— Group discussions around research project topic. 
— Workshop on data storage and archiving.
— Workshop on data dissemination, curation and Open Data, the limits of automation, and the challenges of making data accessible and re-usable.
— Presentations on research projects, group discussion of data challenges within different types of businesses with varying customer base.
— Data protection and legal frameworks for data collection, storage and analysis.
LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 40.00 Guided Independent Study 110.00 Placement / Study Abroad 0.00
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled learning and teaching activities 40 Interactive workshops, discussion sessions, lectures
Guided independent study 110 Reading, personal research exercise, writing
     

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Summary of KSB evidence 500 word report All Oral

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 100 Written Exams 0 Practical Exams 0
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Written essay 100 1500 words, to be delivered at the end of the module All Written comments and marks

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-assessment
Written essay Written essay All Within 8 weeks

 

RE-ASSESSMENT NOTES

Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be required to re-take some or all parts of the assessment, as decided by the Module Convenor. The final mark given for a module where re-assessment was taken as a result of referral will be capped at 50%.

RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Basic reading:

 

ELE: http://vle.exeter.ac.uk/

 

Web based and Electronic Resources:

 

Other Resources:

Science International (2015). Big Data in an Open Data World.

Hey et al. 2009. The Fourth Paradigm . Microsoft Publishing.

Hine, Christine. 2006. ‘‘Databases as Scientific Instruments and Their Role in the Ordering of Scientific Work.’’ Social Studies of Science 36 (2): 269-98.

Dove, Edward S., Yann Joly, Anne-Marie Tassé, Paul Burton, Rex Chisholm, Isabel Fortier, Pat Goodwin, et al. 2015. “Genomic Cloud Computing: Legal and Ethical Points to Consider.” European Journal of Human Genetics 23 (10): 1271–78. doi:10.1038/ejhg.2014.196.

Dove, Edward S., David Townend, Eric M. Meslin, Martin Bobrow, Katherine Littler, Dianne Nicol, Jantina de Vries, et al. 2016. “Ethics Review for nternational Data-Intensive Research.” Science 351 (6280): 1399–1400. doi:10.1126/science.aad5269.

Burton, Paul R., Madeleine J. Murtagh, Andy Boyd, James B. Williams, Edward S. Dove, Susan E. Wallace, Anne-Marie Tassé, et al. 2015. “Data Safe Havens in Health Research and Healthcare.” Bioinformatics 31 (20): 3241–48. doi:10.1093/bioinformatics/btv279.

Boulton, Geoffrey, Brian Campbell, Brian Collins, Peter Elias, Wendy Hall, Graeme Laurie, Onora O’Neill, et al. 2012. “Science as an Open Enterprise.” 02/12. London: The Royal Society Science Policy Centre.

Reading list for this module:

Type Author Title Edition Publisher Year ISBN Search
Set Schutt, R. and O’Neill, C. Doing Data Science: Straight Talk from the Frontline O'Reilly 2014 [Library]
Set Boyd, D. and Crawford, K. Six Provocations for Big Data. A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society Electronic Elsevier 2011 [Library]
Set Kitchin, R. The Data Revolution Sage 2013 [Library]
Set Richards, M., Anderson, R., Hinde, S., Kaye, J., Lucassen, A., Matthews, P., Parker, M., Shotter, M., Watts, G., Wallace, S., Wise, J., The collection, linking and use of data in biomedical research and health care: ethical issues . Nuffield Council on Bioethics, London. 2015 [Library]
Set Fleming LE, Tempini N, Gordon-Brown H, Nichols G, Sarran C, Vineis P, Leonardi G, Golding B, 4 Haines A, Kessel A, Murray V, Depledge M, Leonelli S. Big Data in Environment and Human Health: Challenges and Opportunities. Oxford University Press. [Library]
Set Leonelli, S. Data-Centric Biology: A Philosophical Study Chapter 2 Chicago University Press 2016 [Library]
Set Borgman, Christine L. Big Data, Little Data, No Data . Cambridge, MA: MIT Press. 2015 [Library]
Set Provost & Fawcett Data Science for Business”, O'Reilly 2013 [Library]
Set Mayer-Schonberger V. & Cukier K. Big data: a revolution that will transform how we live work and John Murray 2013 [Library]
CREDIT VALUE 15 ECTS VALUE 7.5
PRE-REQUISITE MODULES COMM414DA
CO-REQUISITE MODULES
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Thursday 06 July 2017 LAST REVISION DATE Tuesday 24 January 2023
KEY WORDS SEARCH Data science, data practices, social implications, sustainability, business models, customer interactions, business planning