About - Advanced and Predictive Analytics Network in Local Government
About the Advanced & Predictive Analytics Network in Local Government (APAN)
This network is intended for practitioners working within local authorities in the area of data analytics and evidencing to inform decision making. Its primary focus is to encourage shared intelligence and transparency on the use of algorithms and predictive analytics by councils. We also encourage wider discussions and shared ideas in the area of advanced analytics more generally. It is funded by grant from the UK Government to the Local Government Association.
In time, we hope to form a steering group chosen by members to guide the focus and priorities. We will work in partnership with advisers from various expert organisations including the Centre for Data Ethics & Innovation (CDEI) to stimulate discussion and help answering questions and guiding our progress. The first version of the network's terms of reference are available online as a short downloadable pdf document. As the network develops, these terms are likely to evolve to best suit the suggestions and needs of the members.
The network is open to any local authority officials (especially data practitioners) using their gov.uk email address. We will also invite selected individuals from elsewhere based upon advice given by our membership. Other applications will be reviewed on a case by case basis.
The network currently centres on this online communications channel, though we will investigate arranging talks and other events and workshops if there is interest. This site contains two areas:
- The resources area where we (and any registered members) can upload and share materials to provoke discussion, review and re-use.
- The discussion area where members can converse with others in the network.
This provides an area to upload, search and review content related to advanced and predictive analytics. Members are invited to upload materials that they have found to be useful in their areas of work.
The upload process is straightforward, though users should be aware of the need to provide mandatory supporting information about their content as part of the upload process. This information includes: a sensible title, a short description narrative advising what the material is all about, a categorisation of what it is. Currently we expect the following types: algorithm, case study, blog, guide, report, tool, training, other. Users can either elect to upload the material for online hosting in this resources hub (deep links are available for wider sharing) or they can provide a link to material held online elsewhere.
We also encourage the tagging of materials with keywords and other categorisations offered by the hub to ease search and access by other members when they are making use of this online resource.
This provides an area where network members can interact with each other. The discussion forums are structured into threads to group similar subject areas and themes. Members can ask questions, describe their work, call for wider involvement and help or generally browse and learn from other experts who will provoke thought, suggest ideas and challenge approaches being taken.
We encourage an open and transparent network as we all learn together. However, in the early days of establishing this network, if you have any comments, worries or ideas that you wish to mention more privately to the organising team at the LGA then feel free to write to firstname.lastname@example.org