Computer Science Themes

This theme aims to provide students with an overview and understanding of a number of advanced web technologies, which are being used to facilitate the move from a web of documents, to a web of documents, data and applications. The theme will cover technological aspects, such as languages for representing documents (HTML/CSS), for working with semi-structured data (XML/XSLT) and for knowledge representation (OWL/RDF), along with the theory and methodologies behind the use of such languages. The theme also discusses human factors issues surrounding the Web and investigates the use of advanced web technologies to support science. This is not a course aimed at those who wish to build web sites, but is for those students who are seeking a deeper understanding of the technologies that are being used to support the continuing evolution of the Web.

The Data Management theme is concerned with the technical challenges of the stewardship and engineering of the data lifecyle from its generation to possible disposal. With the transition to the "information age" and the "knowledge economy", data has become both increasingly central and critical to all activities. The concerns of managing petabytes of data (1016) are now moving to exobytes and even zetabyes of data (1021) - it is estimated that 161 exabytes of data were produced in 2006, with 1 ettabyte of aggregate data projected for 2010. Aspects of concern in the data lifecyle include provenance, modelling and representation, storage and processing, mining and analysis, presentation and availability. Specific topics include the design, maintenance and query processing of both structured and unstructured databases as well as knowledge discovery and learning from data and Semantic Web technologies and ontologies.

The amount and complexity of data being produced and processed by modern technologies is growing rapidly. Computer applications are increasingly required to adapt and learn from these vast data resources. At Manchester, researchers are using machine learning and advanced data analysis techniques to mine huge document collections, create realistic animations from motion capture data, adaptively optimise multi-core processors and understand the complexity of the genome. Although these seem like very different applications, it turns out that they can all be tackled with a core set of common algorithms, drawn from the fields of machine learning, probabilistic modeling and optimisation. In this theme students will investigate the principles, algorithms and technologies underlying these core disciplines while being exposed to relevant applications such as natural language processing, data visualization, text-mining and bioinformatics.

Logics provide the practical and theoretical foundation to a wide variety of areas, such as semantic technologies, the development of ontologies for the semantic web and other semantic applications, agent technologies for the modelling and verification of communicating intelligent agents, the design and verification of security protocols, and formal methods used in the development of complex software and hardware systems and program analysis. Ontologies provide a means for establishing standard representational vocabularies for modelling different domains through the definition of concepts and properties and relations between them. Ontologies are used in semantic applications such as the semantic web, biomedical domains, health informatics and the life sciences. In all these areas general representational languages, modelling tools and logical reasoning methods are essential to turn data into machine understandable ontologies and automated formalisms that enhance quality assurance and support the development, operation and verification of systems.

This information-centric theme is designed for computer scientists who have the desire to drive technology into effective use in business. Information systems are pervasive in every aspect of industry, business and society and therefore there is growing demand for people who have a high level of technical knowledge and are prepared for a leadership role, utilising entrepreneurial and management skills in the solution of business problems. This theme will provide the technology competent graduate with the additional skills required to take up this challenge.

Students take 3 of the 5 course units below; 2 course units in semester 1 and 1 in semester 2.

This theme aims to provide students with an overview of the current state of the art in computing to support mobility for telecommunications (mobile phones), PDAs and laptop/netbook systems. The theme discusses the example wireless systems and the different ways they work, the design of low-power hardware for battery driven applications and the way in which distribution is supported and exploited in mobile applications running on mobile operating systems.

In the universal move to multi-core processors, microprocessor manufacturers have presented the software industry with its most serious challenge ever. Essentially all CPUs are now multi-core, and the number of cores in the CPU is increasing inexorably. The consequences of this multi-core revolution are profound because parallel computing now needs to be handled as the norm, rather than the exception; today's programmers need parallel programming skills that are currently possessed by very few. This theme introduces students to the complexities of parallel computing by reviewing hardware developments and by providing programming techniques and tools that can alleviate the ensuing problems of correctness, reliability and performance of modern parallel systems.

While a large-scale application of the Internet and telecommunication technologies has made our daily communications and data and services accesses faster, cheaper and at anytime, regardless of national and/or geographic boundaries, it also routinely generates enormous amount of information that is transmitted, processed, stored, and managed on networked systems on a global scale. Information recorded electronically on a networked system is particularly vulnerable to security threats, such as theft, manipulation or misuse of valuable or confidential information, deliberate damage to systems and services, and fraud and forgeries in e-business dealings. These threats could endanger national security, business interests, and personal privacy. The field of Security, namely the study of countermeasures to address these serious security threats, is therefore of paramount importance to our quality of life. This Security theme is aimed at introducing the technologies, standards, policies, procedures and practices that can be used to secure information, computer systems and networks. It embraces a range of technologies such as cryptography, computer security, and network security, and also includes risk assessment procedures and the study of how security can best be managed.

The impact of Software Engineering on everyday life is ever increasing, as software becomes all pervasive. This theme starts with an overview of existing approaches to Software Engineering, evaluating their pros and cons, and then provides an introduction to two particular approaches at the forefront of Software Engineering research and practice, Pattern-based and Component-based Software Development.

The Text Mining theme covers the major topics required for writing general purpose natural language processing systems. Natural language processing draws on ideas and techniques from a range of areas--linguistics, for the fundamental notions of how languages work; and machine learning, for acquiring patterns of usage from text. The units that make up this theme provide students with the background required for developing systems that can understand and generate natural language texts for a variety of purposes.