The UK Government's Hate Crime Action Plan (Home Office 2016) stresses the need to tackle hate speech on social media by bringing together policymakers with academics to improve the analysis and understanding of the patterns and drivers of cyberhate and how these can be addressed. Furthermore, the recent Home Affairs Select Committee Inquiry (2016) 'Hate Crime and its Violent Consequences' highlighted the role of social media in the propagation of hate speech (on which the proposers were invited to provide evidence). This proposal acknowledges the migration of hate to social media is non-trivial, and that empirically we know very little about the utility of Web based forms data for measuring online hate speech and counter hate speech at scale and in real-time. This became particularly apparent following the referendum on the UK's future in the European Union, where an inability to classify and monitor hate speech and counter speech on social media in near-real-time and at scale hindered the use of these new forms of data in policy decision making in the area of hate crime. It was months later that small-scale grey literature emerged providing a 'snap-shot' of the problem (Awan & Zempi 2016, Miller et al. 2016). In partnership with the UK Head of the Cross-Government Hate Crime Programme at the Department for Communities and Local Government (DCLG), and the London Mayor's Office for Policing and Crime's (MOPAC) new Online Hate Crime Hub, the proposed project will co-produce evidence on how social media data, harnessed by new Social Data Science methods and scalable infrastructure, can inform policy decision making. We will achieve this by taking the social media reaction to the referendum on the UK's future in the European Union as a demonstration study, and will co-develop with the Policy CI transformational New Forms of Data Capability contributions including: (i) semi-automated methods that monitor the production and spread of cyberhate around the case study and beyond; (ii) complementary methods to study and test the effectiveness of counter speech in reducing the propagation of cyberhate, and (iii) a technical system that can support real time analysis of hate and counter speech on social media at scale following 'trigger events', integrated into existing policy evidence-based decision-making processes. The system, by estimating the propagation of cyberhate interactions within social media using machine learning techniques and statistical models, will assist policymakers in identifying areas that require policy attention and better targeted interventions in the field of online hate and antagonistic content.

The Crown Prosecution Service defines hate crime as any criminal offence which is perceived to be motivated by hostility or prejudice based on a person's race, religion, disability, sexual orientation or transgender identity, with crimes based on xenophobia being recorded by the police as race or religious hostility. The Home Office (2017) shows there were 80,393 hate crime offences recorded in 2016/17, compared with 62,518 the year before, a 29 per cent increase. Crime Survey for England and Wales estimates, arguably a more reliable measure of hate crime victimisation due to their insensitivity to changes in police training/recording practices, show that hate crime, along with general crime, decreased between 2008 and 2015, before turning to show an increase in race and religious hate crime from 112,000 to 117,000 crimes (5 per cent) between 13/15 and 15/17. This is a significant turning point, as it reflects the first rise in hate crime recorded by the Survey in 10 years, while almost all other forms of crime continue to fall. While the increase in police recorded crime can be partially attributed to greater reporting, the Home Office report is unequivocal in detailing a genuine rise in hate crime, particularly around the EU Referendum. Research has also shown the changing nature of hate crime post-Brexit vote, with increases in the targeting of victims from mainland Europe (including non-Eastern Europeans), in new ways (e.g. 'gamification' of hate crime - 'Punish a Muslim Day', and online offences), with new consequences (e.g. leaving England and Wales for Scotland and other European countries) (Burnett 2017, Chakraborti 2017, Rzepnikowska 2018). The reported stark increase in prevalence and change in the nature of hate post-Brexit vote requires new governance models to be formulated. This response has begun, with the publication of the Home Office Hate Crime Action Plan (July 2016) that includes initiatives to increase reporting, secure places of worship, and to develop our understanding of the 'drivers of hate'. In addition, the Director of Public Prosecutions is planning for stiffer penalties for online hate abusers, and a review is underway on hate crime legislation in Scotland. These responses are clear indicators that the government recognises the changing nature of hate crime. Despite these efforts, fresh calls for government to re-examine how it deals with hate crime have been made in relation to improving reporting, victim services and community cohesion post-Brexit (Chakraborti 2017). Significant questions remain over the short- and long-term causes of this rise in hate crime, what the implications are for the governance of this problem, and the wider linked issues of segregation, community cohesion and fostering new shared principles of citizenship post-Brexit. For example, isolated data sources cannot tell us if the rise in hate crime was due to increased reporting by victims and witnesses, better recording by police, an actual increase in perpetration because of the vote and leave campaign, or a combination of multiple factors. Our underlying assumption is that better information about the patterns and drivers of Brexit-related hate crime is a precondition for better governance. This project will develop innovative methods, using linked survey, administrative, press and social media data, to address this. The design of new governance interventions requires robust analysis of all available data (not just police and survey data in isolation), linked in a way that allow longitudinal analysis by geography. Only with such data and methodological innovations can policy-makers be made aware of the most significant driving factors of Brexit-related hate crime.

Emergency services (Ambulance Service; Fire & Rescue Service) play a crucial role during flood response, as they participate in joint command-control structures and are central to rescue and relief efforts (Frost 2002). Emergency services are often legislated to meet defined response times. UK legislation requires that emergency responders comply with strict timeframes when reacting to incidents. Category 1 responders such as the Ambulance Service and the Fire & Rescue Service are required to reach 75% of 'Red 1' (high-priority, life-threatening incidents) in less than 8 and 10 minutes respectively from the time when the initial call was received. This includes blue-light incidents such as life-threatening and traumatic injury, cardiac arrest, road collisions, and individuals trapped by floodwaters. In 2015-16, only one England ambulance trust met the response time targets and 72.5% of the most serious (Red 1) calls were responded to within 8 minutes, against a legislative target of 75% (National Audit Office, 2017). Between 2007-2014, the highest percentage Scottish Ambulance Service achieved was 74.7% in 2013 (HEAT standard). Rising demand combined with inefficient call handling and dispatch systems are often cited as the reasons for missing the above targets. However, response times can also be affected by flood episodes which may limit the ability of emergency responders to navigate through a disrupted road network (as was the case during the widespread UK flooding in 2007). The impact of flooding on road networks is well known and is expected to get worse in a changing climate with more intense rainfall. For example, in Portland, USA under one climate change scenario, road closures due to flooding could increase time spent travelling by 10% (Chang et al. 2010). The impact of an increased number of flooding episodes, due to climate change, on road networks has also been modelled by for the Boston Metropolitan area, USA (Suarez et al., 2005). This study found that between 2000 and 2100 delays and trip-time losses could increase by 80% and 82% respectively. The Pitt Review (2008) suggested that some collaborative decision making during the 2007 event was hampered by insufficient preparation and a lack of information, and better planning and higher levels of protection for critical infrastructure are needed to avoid the loss of essential services such as water and power. More recently, the National Flood Resilience Review (HMG, 2016) exposes the extent to which a significant proportion of critical assets are still vulnerable to flooding in England and Wales. In particular, it highlights that the loss of infrastructure services can have significant impacts on people's health and wellbeing. This project will combine: (i) an established accessibility mapping approach; (ii) existing national flood datasets; and (iii) a locally tested, recent-expanded real-time flood nowcasting/forecasting system to generate accessibility mapping, vulnerability assessment and adaptation evaluation for various flood conditions and at both the national and city-region scale. The project will be delivered via three sequential Work Packages, including: (a) Mapping emergency service accessibility according to legislative timeframes; (b) Assessing the vulnerability of populations (care homes, hospices and schools); and (c) Evaluating adaptation strategies (e.g. positioning standby vehicles).

European cities face complex challenges that demand smart solutions. This project puts urban intermediaries, those people who can bring people and resources together in innovative ways, at the heart of smart urban development and sets out to understand how they create social innovation. We will carry out fieldwork in four European cities (Birmingham, Copenhagen, Glasgow and Amsterdam) where we will develop collaborative working groups, or 'living labs', which will be sources of data as well as sites for learning across projects, fields of practice, cities and countries. In sum, we will advance knowledge of how intermediaries innovate and generate smart urban development, by creating opportunities for collaborative research, dialogue and learning across Europe.

The primary responsibility for preparing for, and reacting to, major emergency situations in England rests with local emergency responders who act individually or collectively through Local Resilience Forums (LRFs, Defra 2013). ResilienceDirect was set up by Cabinet Office in 2014 to facilitate data sharing amongst LRFs for emergency response and planning. Nationwide fluvial, coastal, and surface water flood risk mapping by the Environment Agency provides information about potential areas at risk. However, emergency services (e.g. Fire & Rescue; Ambulance) face the challenge of responding to flood emergencies under fast changing and dynamic weather conditions. Surface water flood risk maps based on return period are useful for planning purposes. However their utility in flood emergencies is often limited due to the spatiotemporal heterogeneity of rainfall. This project aims to translate the recent development in high-resolution surface water flood modelling and numerical weather forecast into a real-time street-level surface water flood mapping service within the ResilienceDirect platform. In addition to surface water mapping, this project will also produce accessibility maps in real-time to assist the decision making of emergency responders. This will allow accessibility (e.g. time to travel) from individual emergency service stations (e.g. Fire & Rescue; Ambulance) to vulnerable places to be evaluated. The mapping results will help contingency planning by emergency responders ahead of potential flood events. Central support from Cabinet Office, the Department for Communities and Local Governments, Met Office and Environment Agency will ensure the wider impact of this project. The project will be demonstrated in Leicestershire, coordinated by the Leicester, Leicestershire and Rutland Resilience Forum and the 16 stakeholders it represents. Atkins will support applicability and link the project with three strands of activities in the company: surface water modelling, transportation modelling and resilience/ emergency mapping. Atkins will also help explore potential commercial applications of the project outcomes. Transport Scotland will support the project with knowledge of potential vulnerable areas (PVA) on the trunk road network in Scotland, aligned with known locations of flooding within their asset management system; Transport Scotland will help identify scope for expanding the service in Scotland beyond emergency responders, for utilisation on a national road infrastructure network, within the operations of Traffic Scotland.