How to make an inter library loan request

The guide takes you through the various steps required to request a book, journal article, conference paper, thesis or other documents that the library does not hold in stock.

E-Book Cataloguing

A brief guide to cataloguing e-books including Marc 21 fields used and AACR2 coding.

University of Southampton Inter-Library Loan (ILL) Form

A form for obtaining material from other libraries or institutions. Any type of material included.

Introduction to the Library for 1st Year ECS Students

There is an accompanying quiz in Blackboard on the INFO1010 page, and a link to a survey. (Look under Course Documents)

Programming Principles: The Java Library

In this session we point you at the Java Library, and go into some more details on how Strings work. We also introduce the HashMap class (a very useful type of collection).

Worksheet for library bibliometrics training

This is used in our Gradbook / Staffbook courses and covers the key web addresses and guidance for activities.

Hartley Library Search Planner

This 2-page planner will help students search databases more effectively using Boolean logic

Predicting sense of community and participation by applying machine learning to open government data

Community capacity is used to monitor socio-economic development. It is composed of a number of dimensions, which can be measured to understand the possible issues in the implementation of a policy or the outcome of a project targeting a community. Measuring community capacity dimensions is usually expensive and time consuming, requiring locally organised surveys. Therefore, we investigate a technique to estimate them by applying the Random Forests algorithm on secondary open government data. This research focuses on the prediction of measures for two dimensions: sense of community and participation. The most important variables for this prediction were determined. The variables included in the datasets used to train the predictive models complied with two criteria: nationwide availability; sufficiently fine-grained geographic breakdown, i.e. neighbourhood level. The models explained 77% of the sense of community measures and 63% of participation. Due to the low geographic detail of the outcome measures available, further research is required to apply the predictive models to a neighbourhood level. The variables that were found to be more determinant for prediction were only partially in agreement with the factors that, according to the social science literature consulted, are the most influential for sense of community and participation. This finding should be further investigated from a social science perspective, in order to be understood in depth.