Information Science (Data Analytics) MSc
1 Year Full-Time | September Start

You will understand the conceptual basis for current database technology and will be able to apply such knowledge in implementing database applications.
You will be able to understand data modelling through the example of the relational model; be able to design and manipulate relational databases with relational algebra and SQL; normalise relational data structures. You will appreciate limitations of data models and the need for database programming to achieve complete solutions, write transactions and procedures for relational databases, specify security for operations, and apply business rules.

You will gain knowledge of advanced object models, their rationale, advantages and disadvantages, construct object-relational databases with nested capability, write user-defined types as ADTs and subtypes for inheritance, use object features in Oracle database system.

You will be able to learn and employ data warehousing techniques to integrate and consolidate data from different sources, which can then be used for business reporting and exploratory data analysis. In addition, you will realise the responsibilities of database designers with respect to professional, legal, security and ethical issues.

You will learn about the key principles of information organisation and retrieval, and put them into practice and demonstrate advanced information and data management skills in diverse environments. You will be able to critically reflect on the theory and practice as well as contemporary research into the issues and contexts of information organisation and interactive information retrieval. You will also develop creative, critical and reflective problem solving capabilities and a commitment to lifelong learning in the management of information and data in different contexts.
Topics include:
1) Information organisation and access
a) Context, concepts, approaches, tools, techniques and standards
b) Structured and unstructured information, web information
c) Research data

2) Interactive information retrieval
a) Indexing techniques
b) Information retrieval models
c) Information interactions in specific domains and contexts

3) Human information behaviour
a) Human information behaviour models
b) User interfaces
c) Usability an devaluation of information retrieval

The aim of the module is to provide you with the knowledge and practical skills for applying modern analytical techniques to business data. The module combines both theoretical and practical approaches so that you will have the skills to tackle problems in various realistic business settings.

This module is primarily concerned with examining and analysing (big) data arising from business(es) and to relate the extracted information to strategic, tactical and operational decision-making in organisations. You will covers topics such as:

• Data processing and big data
• Exploratory data analysis
• Probability and distributions
• Hypothesis testing
• Correlation and regression analysis
• Classification
• Distance measures
• Clustering

You will learn the necessary knowledge and skills to analyse, synthesise and evaluate information systems; and to appraise and use a range of appropriate information technologies for solving problems within a business / enterprise context. You will learn about modern data-storage paradigm and how contemporary business is making use of cloud computing technologies and services. The module will be taught from two complementary perspectives: the managerial perspective and from the perspective of a developer. From these perspectives you will learn how an appropriate incorporation of technology and innovation into corporate strategy and management can lead organisations to achieve profitable and sustainable competitive advantage. Throughout the module, key issues around security and ethics when implementing and using such technologies will be introduced and discussed.

You will learn about the techniques and methods used in applied, contract, academic and/or professional research. You will also develop your understanding of the theoretical philosophies underpinning research, as well as how to design and run research in an applied context. This will focus on the problems and issues that occur in establishing empirical knowledge in the information science area. You will explore various research philosophies and methodologies which can be applied to professional practice. You are also encouraged to apply models of reflective practice throughout the module.
Topics include:
1) The research landscape (research philosophies)
a) The epistemology and ontology of major research paradigms
b) Limitations of the research philosophies
c) The research hierarchy

2) Information Discernment
a) High level of Information Literacy in all domains
b) Developing critical arguments in support of the students own research
c) Identifying appropriate evidence from practice literature to demonstrate engagement with the profession
d) The ethical researcher
e) The reflective researcher
f) Developing research questions, aims and hypotheses

3) Research methods, data collection techniques and data analysis
a) The use of methods in research and implications of choice
b) Exploring methods, including; phenomenology, ethnography, case study, action research, Delphi study, experiments, quasi-experiments, survey etc.
c) Exploring techniques, including; questionnaire design, interviewing, focus groups, observation, diaries etc.
d) Data analysis, including; descriptive and inferential statistics, statistical modelling, multivariate techniques, constant comparative analysis, grounded theory and theoretical sensitivity.
e) Research data management
f) Writing research proposals

You will gain an insight into a range of theories, models, metaphors and frameworks regarding user behaviour in information environments.. You will learn how these can be harnessed to enhance the design process enabling interface designers to move towards user-centred design approaches. You will develop skills in the practice of analysing, monitoring and evaluating user behaviour.

You will be examining in depth theories and models of cognitive, social and emotional interaction in the technological environment and you will be exposed to current research in this area. Quantitative and qualitative methods including sentiment analysis will also be covered.

Tools such as eye-tracking devices, which can be used in the endeavour, will be demonstrated and you will be given an opportunity to evaluate their effectiveness.. Methodologies such as participatory design will also be analysed.

Related ethical and legal issues will be addressed on such issues as accessibility and assistive technologies, security and data protection, privacy issues and information governance.

In summary, the topics you will be learning about are as follows:
• Information behaviour from theory of least effort to co-creation of content
• The user experience and how to capture it
• Cognitive, social and emotional interaction in the technological environment
• Interaction design principles
• Persuasive technologies and behavioural design
• Participatory design methodologies and why they are useful
• Reflecting on wider use, inclusion and equality of access
• Ethical and legal aspects

The dissertation will develop themes relevant to your studies during the taught element of the masters degree programme and/or related to your employment. The selection of your topic rests with you and discussions with staff can help to facilitate your choice of topic. The dissertation process will enable you to use and extend the knowledge and skills acquired during the taught element of your programme, by carrying out a small-scale research project that must be relevant to the particular programme and may be:
• Empirical research;
• A problem-based project, set in a real setting;
• A theoretical based project involving a critical and systematic review and synthesis of the literature.

All approaches should be based on an appropriate research methodology.

The dissertation will normally include the following:

1. A justification of the choice of the topic;
2. Exhibition of knowledge and critical analysis of existing literature, evidenced by a comprehensive list of references/bibliography;
3. Some evidence of original work in the form of data collection, field research, observation and/or analysis - supported by a description and justification of the method(s) used;
4. Conclusions, with an assessment of their general applicability, supported by relevant analytical procedures.

Dissertation briefings will also be held in the second semester of the year in which you complete the taught element of the Masters programme, prior to you commencing work on your dissertation.

Academic skills when studying away from your home institution can differ due to cultural and language differences in teaching and assessment practices. This module is designed to support your transition in the use and practice of technical language and subject specific skills around assessments and teaching provision in your chosen subject area in the Department of Architecture and Built Environment. The overall aim of this module is to develop your abilities to read and study effectively for academic purposes; to develop your skills in analysing and using source material in seminars and academic writing and to develop your use and application of language and communications skills to a higher level.

The topics you will cover on the module include:

• Understanding assignment briefs and exam questions.
• Developing academic writing skills, including citation, paraphrasing, and summarising.
• Practising ‘critical reading’ and ‘critical writing’.
• Planning and structuring academic assignments (e.g. essays, reports and presentations).
• Avoiding academic misconduct and gaining credit by using academic sources and referencing effectively.
• Listening skills for lectures.
• Speaking in seminar presentations.
• Giving discipline-related academic presentations, experiencing peer observation, and receiving formative feedback.
• Speed reading techniques.
• Discussing ethical issues in research, and analysing results.
• Describing bias and limitations of research.
• Developing self-reflection skills.