User-Centred Methods for Measuring the Value of Open Data

A project to identify metrics for assessing the quality of open data based on the needs of small voluntary sector organisations in the UK and India. For this project we assumed the purpose of open data metrics is to determine the value of a group of open datasets to a defined community of users. We adopted a much more user-centred approach than most open data research using small structured workshops to identify users’ key problems and then working from those problems to understand how open data can help address them and the key attributes of the data if it is to be successful. We then piloted different metrics that might be used to measure the presence of those attributes. The result was six metrics that we assessed for validity, reliability, discrimination, transferability and comparability. This user-centred approach to open data research highlighted some fundamental issues with expanding the use of open data from its enthusiast base.

2015 Exam Report: ‘Open Up’ Digital Democracy Commission’s Report

The Speaker’s Commission on Digital Democracy has published its report ‘Open Up’. The report recommends how Parliament can use digital technology to help it to be more transparent, inclusive, and better able to engage the public with democracy.

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.

The Open Web of Things as a means to unlock the potential of the IoT

Abstract: There is a lot of hype around the Internet of Things along with talk about 100 billion devices within 10 years time. The promise of innovative new services and efficiency savings is fueling interest in a wide range of potential applications across many sectors including smart homes, healthcare, smart grids, smart cities, retail, and smart industry. However, the current reality is one of fragmentation and data silos. W3C is seeking to fix that by exposing IoT platforms through the Web with shared semantics and data formats as the basis for interoperability. This talk will address the abstractions needed to move from a Web of pages to a Web of things, and introduce the work that is being done on standards and on open source projects for a new breed of Web servers on microcontrollers to cloud based server farms. Speaker Biography -Dave Raggett : Dave has been involved at the heart of web standards since 1992, and part of the W3C Team since 1995. As well as working on standards, he likes to dabble with software, and more recently with IoT hardware. He has participated in a wide range of European research projects on behalf of W3C/ERCIM. He currently focuses on Web payments, and realising the potential for the Web of Things as an evolution from the Web of pages. Dave has a doctorate from the University of Oxford. He is a visiting professor at the University of the West of England, and lives in the UK in a small town near to Bath.