IDEAS Factory - Global View

The aim of this project is to scope a form of dash-board that gives policy makers an integrated view of the state of the UK, both at the current time, and into the past. If we are equipped with a better view of the UK, we can ensure that it is more resilient to shocks.We might like to have policy makers who are aware of the implications of their actions on others and who understand how independent parties relate to each other. Since relationships change we might also hope our decision makers are up-to-date. Ideally they would be sensitive to subtle changes in the UK today and understand how changes could affect predictions of the future and relate to experiences in the past. But to really have a good perspective on the whole of the UK is next to impossible for any one individual. Our proposal investigates how novel tools from network science, statistical inference, text mining and signal processing can help those making policy decisions.Our scoping project aims to use three types of raw materials: 1) a set of key, live, social, environmental and economic signals, 2) live streams of phrases and keywords extracted from the internet, 3) a collection of interested parties. A signal might be any time-varying quantity and relevant examples are oil prices, internet traffic or rainfall. The keyword information might inform us about what people are searching for on the internet and which terms are suddenly popular.We can ask how the signals relate to each other at the moment by using tools from statistical inference. We can, after a fashion, draw a network map where any pair of signal labels are linked by a line if the signals are related. Since we have records into the past, we can also find similar maps, or networks, for earlier periods. These networks of how relevant signals connect could be useful for policy makers who are trying to understand how different features of the UK relate to each other (like how oil prices depend on how rainy it is). However, having a sequence of networks, or a set of unfolding signals, can be made more useful if they can be associated with known events. Alongside the quantitative signals that we record, we will also record our keyword data which allows us to give a qualitative signature for each period of time. We can then use the keywords, coupled to the quantitative data to attempt to make statistical predictions about keywords, networks or signals in the future. As well as making predictions, one can also attempt to search the past for similar events or carefully scan the present to see if there is anything unusual about current signals, network or keywords.This is a one year scoping project with the aim of establishing a firm base for future development and further grants. Our plan is to assemble the basic algorithmic, human and data components over the year and scope out the possible ways in which these components can be harnessed. We will first establish what specifics policy makers might want from this tool and extend our existing network of interested parties. We will then collect and label relevant signals and write computer programs to use the internet to return to us both timely keywords and meaningful phrases. Given the signals, we will advance methods to infer sequences of networks. We will then scope out how we can use our tool to: detect subtle changes in the UK; make predictions about future networks, signals or keywords; and associate current information with past periods in the UK for which we have data. A major aim is to consider ways in which data of this kind can be visualized and made useful for policy.

Impact plans are designed to demonstrate how proposed work 1) stimulates economic performance globally and especially in the UK 2) increases the effectiveness of public services and policy 3) enhances quality of life. We believe that the research programme proposed here does indeed promise to make a strong contribution to all three. Our feasibility study is designed to prototype a free tool and database to be used by policy makers to improve decision making before, during and after stresses to the UK's infrastructure. By aiming to improve policy by conditioning it on the relationship between disparate sectors we also hope to help UK economic competitiveness; this in turn should improve quality of life. A robust tool to help decision makers anticipate and confront challenges would also make the UK a safer, healthier, place in which to live. Different organizational units, whether they are government departments or firms, can act as if in independent silos; an awareness of interdependence could yield more co-ordination. This research is targeted at policy makers within the central UK government but the same information and tools could have relevance for other beneficiaries. Local government, individual health care trusts, charities, think tanks and even funding agencies like the EPSRC itself can benefit from understanding how different socio-enviro-economic indicators relate to each other: having a dynamically updating map that highlights related quantities should be of broad relevance to planners. Given a successful template, such maps could readily be established for other countries. In a commercial setting, firms might be interested in which other firms are coupled to their share prices and also how these depend on the behaviour of commodities, weather, government debt etc. The tool proposed could also be valuable for consultants who seek to help organizations and governments become more effective. As part of this scoping project we will consider how we can detect changes, associate the current set of observations with past ones and make modest predictions about the future. The ability to identify subtle changes is of high relevance to those who, beyond needing an approximate map of the UK, want to actively monitor the UK to forestall any potential problems: as noted, our contacts in the treasury, department of transport and in security have a particular interest in tasks of this kind. Similarly forecasting and association with the past will allow policy makers to make guesses about possible events in the future. We will arrange meetings at the beginning, middle, and end of the project with stakeholders in government and with those that assist government. In particular we have contacted members of the Treasury (Alex Tuckett), the Department for Transport (Jordan Giddings), the Institute for Public Policy (Andrew Hull - currently seconded to the Ministry of Justice) and Oxford Policy Management (Matthew Powell - also at the Office for National Statistics). We will establish what policy makers might want from a tool of this kind and garner suggestions/access to relevant datasets and suggestions about other possible stakeholders. We will circulate a summary paper of our findings as well as publishing it and putting it on our websites. We have also joined the Futures' Analysts Network organized by Foresight and intend to present our work in this forum. We will make you-tube style videos for each of the papers that we write. We will also create an accessible project website. As regards engagement, NSJ has lectured publicly on Signal Processing and Complex Systems. GT has spent most of his career working within government and has given numerous presentations on topics on criminal psychology and forensic mental health to people from a wide range of backgrounds. Since the software and data will be made freely available, the most direct commercial exploitation will first come via our respective mechanisms for consulting.