6.2.2 Potential Action 2: Big Data for planning and management Context Data-driven planning and management strategies will contribute to planning and management strategies at the city level which are agile enough to respond to the various opportunities and needs of stakeholders arising in the city. The flow of data and information arising from a broad variety of ICT-driven technologies offers ample opportunities for optimising, assessing and communicating on the progress with implementing smart city policies. Examples can be found with regard to capturing (big) data on mobility and electric transport, energy systems, smart metering, environmental sensing and control and data and information from peer-to-peer applications and social media. As yet, the most imminent aspects related to implementing this action concern opening up of databases which are currently in use at public services and city departments. This action will clearly contribute to the visibility of the benefits of smart city-policies. Making data available for development of new services can induce possible innovations in planning and management concepts. Besides, it is an important action as it makes benefits of policies implemented across departments more visible. Goal The goal is to support the implementation of data driven planning and management approaches in developing and implementing smart city projects. This in itself will contribute to visibility of smart city initiatives to the public and to a playing field across cities making it easier for companies to demonstrate benefits of their smart city solutions and technology. Deliverable Providing support for data-driven urban planning and management policies: i. Assessment of best-practices from cities implementing data-driven policies for planning and management; ii. Harmonized standards for sharing urban data and information. Preconditions Preconditions for success include: . City authorities are important in delivering commitment to open data-policy and supporting data-driven approaches to planning and management of smart city initiatives; . Public services to collaborate on opening-up their data stores and considering data-policy as part of the implementation of smart city initiatives; . Private sector can contribute and adhere to common standards for data-collection and exchange; . An important precondition relates to data-ownership and privacy-aspects any of which have to be resolved at national and EU-level, e.g. in the Framework of policies like INSPIRE. Methods and details of implementation A possible implementation could include: . Phase 1: Survey and collection of existing best practices on data driven planning and management policies at city level and benefits in developing and implementing smart city initiatives. . Phase 2: Focussed actions to assess impediments (judicial, operational) of using city-wide data in planning and management and propose solutions . Phase 3: Delivering concepts and business cases on how to maximize the use of city-wide (big) data and information in a collaborative planning and management approach . Phase 4: Testing and demonstration in a variety of cities on small-scale projects . Phase 5: Roll-out Monitoring To monitor progress, attention can be paid to the following set of indicators: . Number of cities implementing policies and projects to open up their data-stores. . Number of smart-city-initiatives having a feed-back of operational data and information into the planning and management process . Share of new bottom-up information services capturing progress and benefits of urban ”smartness” 6.2.3 Potential Action 3: Urban Simulation and Planning Context Cities can benefit greatly from quantified assessments and scenario exercises. These tools can help to better understand the impacts of policies and implementation strategies under different context conditions. This can cover a broad array of topics such as land use and urbanization, investments, energy saving and production, mobility plans, resource efficiency and variable socio-economic aspects. Pending issues relate to questions as to whether and how urban policies will contribute to an energy efficient and sustainable city, how to inform stakeholders on complex system interdependencies or how to arrive at smart decision-making? Urban simulation and planning models to capture the dynamics and impacts of urban development, including socio-economic aspects, will be a helpful tool in this context. Focussing on the use of energy-models and energy- mapping from district to city-wide scale, addressing all relevant sectors, can deliver early benefits. Goal The goal is to offer a common approach and methodology which can be used among cities to assess in a quantified way the effects of planning policies and implementation strategies on energy, mobility, socio-economic aspects and urban development. Deliverable i. Common models and approaches across cities for energy-models and energy-mapping from district to city-wide scale, addressing all relevant sectors ii. Early case studies of the use of digital platforms for integrated multidisciplinary collaborative design and planning (co-simulation and optimization of complex interactions in different domains, virtual environments for viewing and commenting designs, e-learning applications, user-oriented cognitive data visualisations). Preconditions Preconditions for various entities include: . City authorities are important in delivering commitment to innovative model-based planning initiatives through granting experiments for defining en developing proto-type tools and instruments . Public services to collaborate on opening-up their data stores and considering model-based planning as part of the implementation of smart city initiatives . Private sector can contribute to adhere to common standards for model-based planning and protocols for data-exchange from operational systems . Academia/RTO’s are important in developing proto-types for model-based planning, definition of common standards, guidelines to ensure compatibility. Methods and details of implementation A possible implementation could include: . Phase 1: Define demand, supply and benefits of model-based planning and the options for simulation tools across frontrunner cities and academia/RTO’s. . Phase 2: Prepare pilot phases in a defined number of cities to define and experiment with various approaches of model-based planning; include exchange of experiences and user feedback. . Phase 3: Delivering concepts and business cases on urban simulation and planning models to capture the dynamics and impacts of urban development in a collaborative planning and management approach . Phase 4: Roll-out - Enable the demonstration and promotion of leading Smart City-examples in the use of simulation models in integrated planning and management Monitoring To monitor progress, attention can be paid to the adherence of cities in model-based planning approaches in their smart city initiatives and action plans. These approaches should contribute to the agility with which cities and stakeholders can develop, test and implements plans and show the benefits in relation to long term city policies. 6.2.4 Potential Action 4: City communication and engagement Context This action relates to ICT enabling city governments in communicating and engaging broad stakeholder groups in their planning and management policies regarding city development. It therefore focusses on smart visualisation tools supporting communication on city governance issues, peer-to-peer-tools and social media to engage large, informal groups into city development and governance. Goal The goal of this action is to support cities in communicating and engaging broad stakeholders groups, most importantly citizens, in their integrated planning and management policies. It is one of the enabling tools to collect opinions, address stakeholder interests and to secure long-term support and involvement. Deliverable i. Demonstration of innovative peer-to-peer and citizen-to-government-platforms for exchange of ideas and opinions regarding city planning and management issues. ii. Common models and platforms to include integrated planning and management of cities as part of e-governance strategies. Preconditions Preconditions for various entities include: . City authorities are important in delivering commitment to innovative services and tools (apps) which enable visualisation and interactive communication on city plans and bottom- up initiatives. This can be done e.g. through organised hackatons and competitions and through promotion of innovative services for stakeholder engagement. . Private sector actors are also are important in delivering commitment to innovative services and tools (apps) which enable visualisation and interactive communication when it relates to their involvement in city services. They can further contribute by adhering to common standards and protocols for data-exchange from operational systems. . Academia/RTO’s are important in developing tools for visualisation and data-capture which are necessary to build user services. Methods and details of implementation A possible implementation could include: . Phase 1: Survey and collection of existing best practices and tools on communicating and engaging broad stakeholder groups in city planning and management policies . Phase 2: Prepare experiments and hackathons in across a defined number of cities to support development of ICT-enabled services for citizen involvement in city planning policies Monitoring . Number of cities to start including integrated planning and management into their (e- )policies; . Evidence of services informing stakeholders (citizens, private sector actors) on implementation of city policies, progress of projects and city performance related to key parameters and policies; . Evidence of services supporting peer-to-peer-initiatives and their success in bringing bottom-up processes effectively in the city governance and planning process. 7 Priority Area 'Knowledge Sharing' 7.1 Introduction Knowledge sharing between cities, and across sectors, is vital for smart city innovations. The SIP calls for swifter, more broadly applied, structured knowledge sharing, building on current good practices. 7.2 Potential Actions Consistent with the five main recommended actions within the SIP, the following list of ideas provide additional thoughts on how knowledge sharing across all sectors can be improved and better exploited to accelerate action, increase confidence in those actions, and add value generally. # Title Summary Link to SIP Action 1 Cross-Sector Exchanges (see potential) Implement short-term secondment between Cities-NGOs- Industry; crowd-source best ideas from alumni; review and repeat process. #2 enable 100 city- NGO-Industry transfers 2 Technical support for capacity building Provide means to ensure cities of all scales have adequate opportunity to build capacity to implement smart solutions at all levels of city administration #1 Increase knowledge transfer #3 Knowledge Brokers 3 Knowledge Brokers Appoint “knowledge brokers” in city administrations to facilitate transfer of knowledge between sectors and governance levels. Network these to improve the circulation of information about smart city solutions. #3 Knowledge Brokers. #1 Increase knowledge transfer. Apply to domains (eg Planning; Data…) 4 Readiness Check-Lists Develop “check-lists” for cities to evaluate their readiness for Smart City roll-out and identify potential need for change. #4 integrate knowledge sharing from outset 5 Bilateral Mayoral Exchange Bilateral city mayors’ meetings. This can be exchanges over half a day between two cities in a specific area, e.g. energy efficiency. Exchange of good practice at political level can lead to swifter change. #1 Increase knowledge transfer. Planning Policy and Regulation 6 Study visits; Peer reviews; Mentoring Increase exchange of experience between cities through study visits, peer reviews and mentoring schemes allowing cities to transfer knowledge and benefit from the expertise of others (building on established knowledge transfer platforms; also to disseminate results from the lighthouse projects, focusing on reliability and transferability). #1 Increase knowledge transfer. 7 One-Stop Smart City Solutions Tool Develop web tool at EU and national levels to enable city staff, developers and business to access and exchange ideas on new solutions. #5 One-Stop web tool 8 City Advisory Board Establish City Advisory Boards including cities, industry (with R&D and market knowledge) and research community, to fit priorities along entire project chain to research needs. Stimulate critical discussion of outcomes of the EIP SCC among the research community. For instance, the EERA JP Smart Cities is a platform for such discussion and dissemination. #1 Increase knowledge transfer. Integrated Planning 7.2.1 Potential Action 1: Cross sector staff exchanges The connections, contacts and communication between the main sectors involved in and concerned with smart city developments require strengthening. City administrations, companies (large to SMEs), relevant NGOs and academia need to better exchange and communicate. Much greater mutual understanding of needs and challenges is required to ensure they are anticipated and matched by available and forthcoming solutions. Study visits, peer reviews and mentoring programmes happen on a regular basis between cities across a wide range of areas with good results in terms of inspiring new developments and change. To scale up smart city development, a concrete and practical cross-sector approach to knowledge sharing is required. Goals Goals could include: . Create a better understanding across sectors of current and future needs as well as available solutions, with a view to facilitate learning processes and mutual understanding; . Build informal partnerships across sectors to scale up smart city development; . Ensure that knowledge about what works and what doesn’t is shared between cities and across sectors. Deliverables One concrete deliverable concerns short-term staff exchanges annually between cities, industry and relevant NGOs. Involvement of academia in the development of the exchange programmes and to capitalise on outcomes would be an asset. This action can start in 2014. Preconditions Preconditions for success include: - European networks (cities, business (incl. SMEs) and academia): to publicise the opportunities available with the programme and ensure engage of their members. Disseminate outcomes of the programme widely. - City administrations: to engage in developing a visiting programme, to host and send participants, to evaluate outcomes for own smart city developments. - Business/industry: as above. - NGOs: as above (where relevant) - Academia: To support cities and business in the process and ensure that the programme capitalize on benefits. Facilitate contact with programme alumni to ensure best practice is extracted. Methods and details of implementation - Advertise the possibility for participating in cross sector staff exchanges widely across the EU through e.g. networks. Clarify cost implications and benefits to potential participants. - Develop a short guide for staff exchanges which explains the elements to consider making the staff exchanges valuable and a win-win programme for all parties. - Gather expression of interest from cities, industry and NGOs and match them up according to their areas interest within smart city developments. To keep costs down, consider to match partners also according to geographical proximity. - Ensure that expectations to the exchanges are clarified with all parties before kick-off. - Crowd source the best ideas from the program’s alumni and make them publicly available. Monitoring Quantitative: - Number of staff exchanges taking place annually - Number of organisations, public and private, participating - Number of best practices identified Qualitative: - Feedback from participants in exchange programs - New or adapted/changed smart city developments in city administrations or industry following participation in the program 7.2.2 Potential Action 2: Technical support (in kind) for knowledge sharing/capacity building in city administrations and business Context At local level, knowledge sharing is about getting the right work processes in place to ensure that information is transferred between different administrative departments of a city administration. Members of staff must be equipped to recognize relevant smart city solutions and work processes must facilitate knowledge sharing internally. City employees must also be qualified to communicate smart city developments and solutions to the citizens, local business and other stakeholders to ensure that information trickles down administrative systems and to other sectors. In some places this will require an up-skilling of employees and a review of work processes. Technical support for capacity building, communication and knowledge sharing in city administrations can help ensure adequate capacity to promote smart city developments and eventually boost the uptake of solutions locally. Technical support delivered through local partnerships can be a win-win situation for all partners involved increasing engagement and ownership. Goal The key goal is to ensure adequate capacity to promote and deliver smart city developments within city administrations and local business. Furthermore, such action should help ensure a local level playing field of knowledge of political, legislative, regulatory and administrative framework conditions for smart city developments. Deliverables i. Local smart city partnerships which stimulates knowledge sharing and capacity building between partners. ii. Smart skills staff training programmes in city administrations. Research organisations and academia can use their up-to-date knowledge to prepare comprehensive and practical guidelines, training documents and best practice examples. iii. Outreach programmes to local start-ups and SMEs with information about public support for smart city business development. Preconditions - The city administration must be on board to analyse its needs around work processes, up- skilling and other staff developments for better deployment of smart city solutions; - Cities must streamline administrative processes and devote sufficient administrative capacities to support these processes; - Local business and research institutions should be partners in delivering the technical support to up-skilling city administration employees; - Industry partners that develop and supply new products materials and solutions should be partners in delivering the technical support to up-skilling city employees; - Research institutions, city administrations and industry can join forces to ensure that local start-ups SMEs get the right level of information about business support available. Methods and details of implementation - Gather good and bad practices about existing local smart city partnerships. - Establishment local multi sector smart city partnerships, where they are not already in place. They can be led by the city, business or research institutions but should be with a view to ensure and integrated approach to smart city developments. - The smart city partnerships work with their local city administration to assess the city’s needs and potentials, including within the city administration. - The city administration develops a smart skills training programme for members of staff to enhance its work processes and increase the capacity of the administration around development, implementation and communication of smart city solutions. - The training programme is delivered in cooperation with the members of the smart city partnerships. - The city administration and the relevant research institutions develops an outreach programme to local SMEs to ensure they are informed about local smart city development needs and public support available for start-ups and SMEs. - The smart city partnership develops a communication strategy to ensure knowledge about smart city solutions relevant for the local development is shared with all local stakeholders. Monitoring - Number of new smart city partnerships; - Number of new smart skills training programme in city administrations; - Number of city employees that have been through the training programme and their feedback- Number of local outreach programmes to start-ups and SMEs. Increases in uptake of smart city solutions locally . 8 Priority Area 'Baselines, Performance Indicators and Metrics' 8.1 Introduction There are more than 150 credible city indicator systems in place4, covering all manners of geographical, thematic as well as other criteria. Not surprisingly, they all tell a different story about a city's performance. Most cities do seek to compare their performance over time on some form of consistent basis; a comparison between cities, on the other hand, is a much harder task for each has a different context. If we are to confidently advance towards our agreed 20/20/20 targets some form of common measurement framework should be in place. Although it may be complex, and although cities do indeed differ contextually, we should rise to this challenge. 4 http://www.jll.com/Research/jll-city-indices-november-2013.pdf Initiatives like the Global City Indicators Facility (GCIF), or the European Reference Framework for Sustainable Cities provide a sound basis of institutionally supported measurements. Yet there is presently no single, broadly-accepted indicator framework that reflects the ‘smart city’ approach – one that addresses cities systemically and can help cities understand better the inter-dependent nature of city systems and services; one that can help us demonstrate in an unambiguous manner how cities best use modern ICTs to improve quality of life, foster sustainability and boost competitiveness and innovation; and one that can help cities collect an improved set of data to underpin such measurements. All this requires indicator systems, data bases and statistical standards that should be developed in close collaboration between European cities, the academic community, industrial partners, standardisation institutes and statistical offices. 8.2 Potential actions The table below outlines a number of actions that would support the development and European- wide application of such an indicator system: # Title Summary Link to SIP Action 1 EU smart city Indicator framework (See example action below) Develop and pilot an EU-wide smart city Indicator framework as a collaborative exercise; adopting/adapting existing measurement assets; and establish a means to achieve wide-scale adoption. #1/2/3 develop/deploy indicator system 2 Constituency building (See example action below) Activities related to the development of indicators, consensus-building, dissemination of results, getting the buy-in, e.g. organise a European scientific conference on smart city indicator systems and monitoring tools. #1/2/3 indicator system Knowledge sharing 3 Metrics Standards Develop and align standards for European energy, mobility and ICT data to enable comparison at local levels (within cities over time; and between cities) Standards Open / big data 4 Smart City Competitions & With focus on improvements of a city with respect to a baseline, implement competitions and awards to instil a #3 ongoing monitoring Knowledge sharing Awards greater emphasis on performance within cities (e.g. between city districts, involving citizens directly), and between cities – all based on a respected measurement framework. Open / big data 5 Smart City KPI Uptake Establish a business model that ensures the uptake and sustenance of the smart city indicator framework; particularly for cities with limited resources/capacities #3 ongoing monitoring Implementation 8.2.1 Potential Action 1: Develop and provide data for an EU-wide Smart Cities indicator framework Context The European Innovation Partnership (EIP) on Smart Cities and Communities seeks to support cities in becoming more energy-efficient, in using more renewable energy and reducing their greenhouse gas emissions by stimulating technological innovation, engaging citizens and providing innovative concepts, processes, methods and tools. To create transparency and build confidence, all such actions need to be quantifiable against clear baselines such that wins can be clearly evidenced – to a city's leadership and its citizens. To this end, a comprehensive indicator system, based as far as possible on real data, is needed. In recent years, several indicator systems and assessment methodologies related to specific aspects of smart cities have been developed on the European level. Relevant initiatives and projects are, for example, the Covenant of Mayors, the Green Digital Charter, CIVITAS, CONCERTO, Urban Audit, ESPON, the Reference Framework for Sustainable Cities (RFSC) as well as others. However, there is still no integrated indicator system that supports reliable progress-monitoring in all fields relevant to smart cities, both within a city over time, and in between cities. Goals To develop an agreed indicator framework that enables cities to self-evaluate their progress over time towards “smartness” and compare themselves to other cities in a more reliable manner. To adopt or adapt existing measurement assets in order to make data collection and use less onerous. To achieve broad acceptance and sustained use of the framework, encouraging use by all kinds of cities and their industry and partners from academia. Deliverables i. Smart City Indicator Framework & Toolkit: aligned with actions established through HORIZON 2020. This should addresses the systemic nature of cities and integrate ICT/‘smart’ elements within the framework; ii. Agreed Top-Level ’Smart Indicators’: that can be used consistently and with confidence to demonstrate progress towards the 20/20/20 energy and climate targets; iii. Data Protocol: there will be data gaps (because the framework will be based on data from other projects and databases with only few cities represented in all of these) - cities should therefore be invited to commit themselves to update and complete their datasets and help themselves and others closing data gaps; iv. Dissemination method and means of sustainability: the more cities that apply the indicator system (and share their experiences and data with other cities), the more profound the insights into barriers and success factors for smart city development will become. Preconditions - Collaboration between European cities, the academic community, industrial partners, standardisation institutes and statistical offices; - Cities provide the data in a standardized format, and data is opened up; - Protocols are established to manage sensitive data; - A regular cycle of data updates is established. Methods and details of implementation Implementation of two key elements are covered: (i) the Indicator Framework, and (ii) the Data Protocol The following six-step approach is proposed for the Indicator Framework: . Step 1: Scoping of indicators: mapping of areas where indicators are needed and their nature (e.g. environmental). Identify in detail the action areas where we want indicators with a preliminary list of such indicators; . Step 2: gap analysis of existing indicators from experience and research. This phase should look as well to what barriers may exist in the KPI area; . Step 3: develop the missing indicators: through standardisation bodies or others; . Step 4: agreement on the indicators: a European scientific conference could be the means to get there; . Step 5: define the baseline and pilot KPIs: Through voluntary actions to see practical feasibility of indicators set for cities. This phase could also shed light on data availability, knowledge-levels of the user, practical meaningfulness of the data indicators in the urban context; . Step 6: Create the ecosystem required to enable the use of KPIs through methodologies for data collection, data usage, assessment, training to city staff, creating the necessary availability of data, removing barriers identified during the gap analysis. The following four-step approach is proposed for the Data Protocol: - Step 1: Analysis of Status Quo o What measurement systems are typically used by cities? And what ‘smart’ measurement approaches are in use? o Which data has already been collected by the city? o Which data is missing to fulfil the requirements of the indicator system? o In which format should the missing data be collected? - Step 2: Data collection and data standardisation and integration - Step 3: Transfer of missing data to European Framework - Step 4-n: Regular (e.g. annual) data update Monitoring - Use by European cities (number of) – of different types - Qualitative feedback of use at strategic and operational levels - Adherence to regular data updates - Quality of data (standard format, metadata) - Data gaps and restrictions in data availability should be documented and analysed.