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AN URGENT GUIDE FOR LOCAL AUTHORITIES ON DATA OWNERSHIP, SHARING AND CONTROL
Published: 30 July 2021.
This white paper has been produced with the support of Amazon Web Services (AWS) Institute.
Expert input gathered via two roundtables in 2020 was provided by representatives of the cities of Saint Quentin, Manchester, Belfast, Lisbon, Ghent, Association of Swedish Cities & Regions, Turku, Kiel, Istanbul and the Scottish Cities Alliance.
Written and compiled by Ed Synnott, designed by Jane McLaughlin, edited by Anna-Marie Casas, with the expert guidance of Lea Hemetsberger and Davor Meersman.
We are in a period of flux when it comes to the role of data within our cities.
As we move towards urban spaces being fully enabled by sensing, automating, and intelligent technologies, data becomes ever more valuable and central to the way we operate and govern our municipalities. Cities are facing choices that will determine our direction of travel within the ‘data economy’ for some time to come.
We are still experiencing the biggest global challenge since the 1940s in the form of the COVID-19 pandemic. Its impact will be felt for years to come, but it has also given cities a taste of the future: of a time when frequent rolling crises are the new normal.
So, what can our experience of the pandemic tell us and how can we better prepare?
The pandemic has taken a significant toll on communities, the economy and the way in which our cities work. Yet, in the face of catastrophe, we discovered that we can be more resilient, work at greater pace, and achieve the extraordinary with the innovative use of data when an existential threat afflicts our communities.
The urban response to the pandemic highlighted the need for data to support rapid action across the board. It is data that has helped track the progress of the disease and informed whether - and in which circumstances - defensive measures have been effective.
Much of the information so crucial to our new pandemic armoury did not originate within pre-existing data streams. Instead, an army of tech applications was freshly developed at lightning speed over the course of the emergency, and within a tech and data ecosystem that found its training wheels in the blink of an eye.
The pandemic has taught us that, not only do we need to be able to access more high-quality data in general, but that our capacity as cities to respond must always be agile - pivoting where necessary to new and emerging priorities with relative ease.
It is my pleasure to introduce to you our first white paper, bringing together the views and voices of key cities and experts on data ownership, sharing and control.
When, as a community of cities, we founded OASC we knew that our fundamental task was how to deliver on the promise of digital transformation for cities all the way from the city economy to the very societal fabric that makes us all who we are.
Underpinning this noble challenge was a problem that we needed to solve: how to make smart city solutions interoperable in a way that would allow solutions to scale from city to city via a common marketplace.
We’ve brought this into sharp focus, recognising that if we can understand what is minimally needed in order for cities to exchange solutions, services and data among themselves and their respective ecosystems, we can offer a common ground for cities wherever they are, and in celebration of all of their diversity.
Our Minimal Interoperability Mechanisms (MIMs) form this common ground.
MIMs help cities stand on the shoulders of their peers by using stuff that works in other places. Not tomorrow, but today.
We have grown from a handful of trailblazing cities to over 150 municipalities located all over the globe and we are still growing. The information needs of our cities grows along with us, and this white paper reflects a set of priority data-related issues that were identified over the course of two roundtables in 2020. It is just the start, as we respond to further city priorities over the coming year.
Thank you to city representatives for your expert input via the roundtables - we are nothing without our cities.
Davor Meersman CEO OASC
In 2020, OASC held two roundtables with city representatives to unpick the issues they faced with respect to data ownership, sharing and control, and to understand where they saw their own journeys taking them in responding to these challenges.
We would like to thank everyone who gave up their time and shared their expertise and wisdom, including:
Bobo Baudin, Association of Swedish Municipalities and Regions.
Ciara Campbell, Officer, Smart Belfast, Belfast City Council.
Alexandre Chaffotte, Smart City Manager, Saint-Quentin.
Deborah Colville, Head of Smart Belfast, Belfast City Council.
David Cunha, Head of Smart City, City of Lisbon.
Benjamin Ditel, Data & Tech Enabler, CDO Office, City of Kiel.
Burcu Özdemir, Smart City Director, City of Istanbul.
Bart Rosseau, Chief Data Officer, City of Ghent.
Adrian Slatcher, Senior Officer, City of Manchester.
Tarja Vuorinen, Foresight Manager, City of Turku.
Doug Young, Data Cluster Project Manager, Scottish Cities Alliance.
A future beckons in which urban spaces are fully enabled by sensing, automating, and intelligent technologies and data becomes ever more valuable and central to the way we operate and govern our municipalities. Cities are facing choices that will determine our direction of travel within the ‘data economy’ for some time to come.
We are still experiencing the biggest global challenge since the 1940s: the impact of the COVID-19 pandemic will be felt for years and it has given cities a taste of the future - of a time when frequent rolling crises are the new normal in the face of the linked climate and ecological emergencies.
The urban response to the pandemic highlighted the need for data to support rapid action across the board. It is data that has helped track the progress of the disease and informed whether - and in which circumstances - defensive measures have been effective.
As we re-tune our cities increasingly towards being more resilient, and to benefit from the opportunities brought about by ever increasing innovation, this agile approach will be our best response.
Yet, our capacity to be responsive is impacted by a range of additional factors: the relative size and capacity of cities to resource agile responses independently; the growing demand of cities for data and data-driven innovation and the ensuing ‘data crunch’; and, the increasing complexity of the challenges we face globally.
The urgency of finding pathways to support open and agile decision-making has never been greater, and the benefits never clearer.
So where to begin? Cities at the beginning of the data journey are often confronted with myriad choices: is it carrying out a root and branch review; carving out ‘priority’ data; enabling random innovation to drive direction, or something else?
We now recognise the question is better framed around the need to match priority issues to solutions (and therefore the data required in support).
Being able to learn from other cities, collaborate, benefit from ‘city-sourcing’ – whether this is on skills, legal, procurement or governance – is going to be critical for city readiness to meet global challenges on one hand, and on the other, to address a raft of internal barriers including dealing with ageing legacy systems, lack of internal knowhow and ongoing skilling, and meeting the price of costly upgrades.
The good news is there are now tools and mechanisms in place which allow cities to overcome traditional barriers to entry – and which facilitate more agile approaches that reflect individual city needs. Supported by a strategic approach to data governance, two basic planks can provide a platform for change: cloud-based services; and, the means by which solutions can become interoperable – through what are known as Minimal Interoperability Mechanisms (MIMs).
Urban managers wishing to innovate, need to be able to pick up solutions and try them on for size, adapt, implement or, ultimately, move on to a new innovation that suits better, without significant price tags attached: something which cloud-based solutions with the support of the MIMs, and within an effective decision-making framework, can offer.
It is easy to be overwhelmed by the many challenges and opportunities facing cities. One way to begin is to take a single bite - rather than trying to ‘eat the whole elephant’. With this in mind, we suggest that cities wanting to start out on this journey consider some basic steps first that can be summarised in three steps:
PROBLEM IDENTIFICATION
DATA REVIEW
MATCH & PILOT.
This guide provides the pathways to support on this journey and information about how to get started. It includes real, practical examples from cities – an invaluable resource. When you are ready, we would love to include your examples too.
Share your story by getting in touch: you’ll be helping other cities on their journey. info@oascities.org
It’s easy in hindsight to identify what went right or wrong about our response to the pandemic, but as we re-tune our cities increasingly towards being more resilient, our capacity to respond to any fresh crisis in the future is impacted by a range of additional factors:
The relative size of municipalities: small towns are not in the same position as larger towns or even small cities in terms of investing in the infrastructure needed to work effectively with city data.
Demand for data: as the desire for more insight grows, all cities will be increasingly challenged by the impending data crunch. Indeed, as emerging challenges become ever more urgent and severe, our cities have an increasing thirst to match problems to solutions when it comes to technology and the data it can produce.
The complexity of challenges: there is increased demand for insights to be integrated and cross-cutting. From immediate, highly localised concerns to longer-term global challenges, we are facing interrelated and sometimes competing priorities.
Can we be more on top of how money is spent and the investment value it brings to the local economy? Do we really have a proper handle on how our local roads are used and what could be done to improve them for those living in their vicinity? Are we truly across what our investment in social care delivers and the ways in which we can improve quality of life for people in our care within existing budgets?
Longer-term challenges are beginning to emerge as priorities: how, for example, can we better understand and manage the urban heat island effect, or extreme weather events in the context of nature-based solutions and new biophilic design principles? How do we work more effectively with smart technology to drive down carbon emissions while elevating healthy mobility? What can we do to better support smart, healthy ageing while also managing our parks, rivers and air quality? What does our net zero strategy need to make it truly smart? Can we understand how our city systems are working and interacting - and what does this tell us about the big interventions we want to make?
As the size, innovation and complexity of challenges continues to press down on the capacity of cities to respond in a flexible way, the urgency of finding pathways to support open and agile decision-making has never been greater. Urban managers need to be able to pick up solutions and try them on for size, adapt, implement or, ultimately, move on to a new innovation that suits your city better: something which cloud-based solutions, within an effective decision-making framework, can offer.
This guide has been devised, drawing from the wisdom across our city and partner networks, to help city managers find the right route to being more open and agile in how cities own, manage and control data in the context of data and tech-driven innovation.
Cities at the beginning of the data journey are often confronted with myriad choices about where exactly to begin: is it carrying out a root and branch review; carving out ‘priority’ data; enabling random innovation to drive direction, or something else?
While approaches will vary from city to city, there are many factors at play and there is no one-size-fits-all solution.
One question that crosses the minds of urban managers is how much data is enough?
We now recognise that the question is better framed around matching priorities and challenges to solutions. What data is needed to provide an appropriate solution for the priority at hand, and how do we draw as much value from it? This approach can be a strategic and agile starting point - and also work for bigger cities as an ongoing, cut-through strategy.
Amid all the hype, and a market in which the pace of innovation continues to accelerate, it is easy to get lost between the technology pathways available now, what is being admired like a mature cheese (great now, but wait too long and its pull will definitely wain), and what is just around the corner that will most effectively harness and provide insights on much-needed urban data. From 5G to blockchain, it can be a confusing minefield to negotiate and one with long-term consequences for procurement, servicing, skills and more.
In a bid to find the best solutions, cities have dipped their municipal toes into the murky waters of dingy labs and grungy student digs, hackeries and maker spaces, and even into the plush offices of the big players to find solutions. Sensors and bits of kit have seemingly sprung up in urban spaces everywhere as we experiment with possible solutions, with some cities devoting time and effort to being urban-wide living labs. Cities have also dived into the well of information within their own estate: from rates payments to maintenance schedules and social care to kindergartens, councils have been exploring how they can get better value from exploiting and sharing data internally across operational and data silos.
City experimentation has produced rich innovation (and not just with the ‘sensed’ world, but with data from other sources as well). This has facilitated ways to share the spoils with other cities, including those that do not have the means to invest at the forefront of urban innovation.
The clear message is that cities no longer have to shoulder the burden of doing all the innovation themselves - we can learn from each other, and cherry-pick what we like from a wealth of solutions.
You may be thinking right now about all the data your municipality holds in non-digital, semi-digital, or digital - but not shareable - means. From procurement information to maintenance records for the council’s own estate, municipalities the world over still struggle to know what data they currently collect, how they gather it, and for what purpose. Being able to persuade internal colleagues about the importance of a data review is often the first step to uncovering a trove of information that could, ultimately, help bring better value to the city. This is regardless of whether the data is made open or not - or whether this is a city-wide review or within a specific operational area.
Recognising that not only do we all horde data (it is estimated that the average organisation stores more than 50% of the data it collects without ever using it), the data we possess is not always fit for purpose (incomplete, error-strewn, non-compliant, not standard or duplicative)[^1]. Sometimes it remains elusive or can’t be read - tied up in vendor systems and not sharable. Tempted to clean your house?
How did we get here? Simply put - we’ve invented loads of data-producing tech that is clogging up our digital arteries. And, as the pace of tech innovation accelerates, data production will continue to grow accordingly. New data generating applications are coming on stream at a faster pace every day. In the 127 years it took the landline to be the communication tool of choice in 95% of US homes, the mobile phone could have reached market saturation six times over - and the smart-phone 15-fold for that matter[^2].
Some cities are locking down data storage - preventing downloads from external emails and many websites[^3] partially in response to security concerns - but this understandable response serves to only delay the problem and may lock city teams out of important conversations in the meantime. The projections are grim for those hoping for a reprieve: by 2025, it was widely estimated pre-pandemic that global data storage will have increased by 400% from 2018 (for the geeks among you, that’s a rise from 33 zettabytes to over 175 zettabytes)[^4].
The story doesn’t stop there. The pandemic triggered a new wave of rapid tech adoption - not just in relation to our integrated health responses - but in a whole host of ways that enable us all to adapt to this new world: checking how busy your local street is[^5], for example - or creating improved ways to contact friends and family for virtual face-to-face time - and, of course, the now ever-present remote working video calls[^6]. The pandemic experience underscores the immense power of system-wide shocks to provoke dramatically altered ways of working and living (and therefore intense periods of innovation). The rate of growth in both innovation and the ensuing data being generated is seemingly exponential and has serious implications for cities - both positive and concerning.
Let’s take a look at the positives: new applications will take data sophistication to a new level at pace. Innovations beckon cities with much opportunity to truly transform service delivery, while enabling them to ‘talk’ to these applications so that the circle is fully complete. Innovations like smart materials that produce and generate quantities of data about the environment around them, increasing rates of automation, smart vehicles and road infrastructure, smart waste technologies and more could revolutionise the way we live - and cities are eager to be part of the innovation process.
It is clear that with innovation comes demand for data. Innovators want access to city data in order to create new applications that will improve urban areas. Cities are also thirsty for data - looking for insights into how to find increased value from existing data, new ways of integrating different streams, and from new sources, such as AI-enabled machine learning applications.
There’s a problem though: as new technology comes on board, those that can afford to embrace its benefits are able to race ahead, while those less able to are in danger of falling short of the economic, environmental and social edge that it brings.
Data is, of course, the currency of this new tech-enabled economy, both feeding and deriving in ways that could only be dreamed of a few years ago. Less affluent towns and smaller cities are therefore at an increased disadvantage.
It is not an exaggeration to characterise the tech and data crunch as a serious threat, in spite of the opportunities it also brings. There is a real risk that cities - particularly the small and less affluent ones - will be effectively cyber-buried under a mountain of data, increasingly excluded from digital conversations as the 2020s progress[^7].
So, what’s the solution to sharing the gains from innovation while keeping strategic goals on course (as if there was ever only one) and avoiding being buried under a mountain of data?
The experience of cities well advanced in open and agile practices provides a significant clue to how we can share the spoils, which, for now, delivers many benefits and continues to hold much promise: the cloud.
Cloud-operated urban and local data platforms have provided freedom and flexibility for many cities to achieve sophisticated analysis and insights on internal operations, as well as wider urban priorities, without having to invest in siloed infrastructure back at base. Cloud functionality has facilitated smaller cities and towns to access infrastructure for which they would be otherwise priced out, and has created opportunities for substantial savings within municipal operations that can be redirected to other pressing demands. Data lakes, machine learning, analytics, IoT and other tools to help unlock data - turning it from information into insight - are now available at the click of a button at comparatively affordable prices.
While cloud operations are by no means the only answer and - as OASC can attest, many cities are working positively within vendor-specific onsite environments - the cloud provides an opportunity for urban managers to explore addressing priorities in an agile way. Cloud-based solutions are being developed across the world, and many are replicable and interoperable. Access to cloud-based services can be utilised only when needed, so there is no long-term vendor lock-in for either storage or tools. This means we can, as urban managers, pick and choose between solutions with minimal disruption - trying them on for size, and adopting, or moving on to a new innovation where it seems a better fit.
‘OASC helps cities act with universal knowledge in the interests of societies everywhere.’ Davor Meersman, CEO, OASC
You may want an automated solution for managing municipal waste - or maybe it’s controlling moisture levels in parks. Perhaps it’s better managing the turnaround times for voids in housing management. Well, chances are that there’s a city close by or on the other side of the planet that has already implemented a solution that you like. If only your city could pick up this solution and integrate your data… This core need for interoperability between cities and solutions is the primary reason OASC exists and it is where the # Minimal Interoperability Mechanisms (MIMs) come in.
Recognising that innovations coming from publicly-funded projects usually hit a dead-end soon after the funding stops our founders came together in 2015 to create Open & Agile Smart Cities (OASC). What was missing was a market, where solutions could be shared between cities facing similar challenges, but had different cultural, economic, social, and technical structures. An initial group of 30 cities joined the new initiative and, soon afterwards, the movement began to grow - adding more and more members representing a diverse community, with currently more than 150 cities from 31 countries.
OASC embodies a singular, global, demand-side consensus on the minimal common ground for exchanging solutions, services and data between cities. We call this common ground the ‘Minimal Interoperability Mechanisms’ (MIMs). MIMs are used to scale local solutions globally and are adopted by local governments, supported by global institutions, backed by industry, based on open standards, technology agnostic, and universally accessible.
MIMs are catalysts for impact, helping local levels tackle global issues together:
adopted by local, regional, national, and international governments.
supported by the United Nations, the European Commission, and the World Economic Forum, and national governments
based on open standards, technology-agnostic, universally accessible, and cheap to implement.
backed by industry and part of technology platforms and roadmaps worldwide.
A key element to understanding data is recognising that data exists within international frameworks. MIMs have been designed to enable accessibility to data and its use irrespective of where it comes from. Like a superhighway, MIMs create the conditions in which data can be understood from one context to another - to be consumed by tools and applications implemented anywhere else - as long as the data is MIMs-compliant. In basic terms, it means that a cool application (smart route planning models for urban services, let’s say) developed in Brisbane can pick up a MIMs-compliant data stream from Antwerp. For Antwerp, the benefit is that the application can be used locally without further customisation - providing the same functionality it did in Brisbane.
Open and agile cities are attuning their data to align with MIMs, not only to use interoperable tools, but so that their data can contribute to a bigger picture: sharing data with cities right across the globe, using cloud-based services. MIMs are a necessary precondition for scaling up data from city to city, or from region to region, and for genuine replicability and interoperability of solutions.
An overview of how data can be collected and used in a city, from capturing data from sensors to aggregating and analysing it to create insights for the city manager.
Cities are increasingly appreciating that quality data has value collectively. Whether it’s being able to support mobility solutions or asset maintenance, private operators are interested in what we have to share. Unsurprisingly, when we peek over the fence at our corporate neighbours, we can see things that we would also very much like to access. What can mobility data tell us about how our cities are being used? Can traffic sensors give us better insight into air quality? Do nursing home operators collect information about the frequency of family visits - what could this tell us about intergenerational cohesion and support in the wider community?
‘I like to think of data in terms of people and place: there’s the people kind of data and there’s the place kind of data’. Adrian Slatcher, Manchester City Council
However, data sharing - and making data open for sharing - brings one particular thing into question: how much control do cities have over their own data; over the data they manage and that which they choose to share? Place-based data is sometimes the easiest to share, whereas people-based data is generally sensitive, if not completely off limits. Increasingly though, the two are intertwined, with new disruptive technology being deployed such as facial recognition software in public open spaces. The path to ethical and transparent, open data and data sharing can seem littered with privacy and ethical concerns.
Cities are finding that, even where sensitive data is not involved, it is not always straightforward to manage data as a valuable resource - with a number of internal and external barriers preventing a smooth exchange of data as and when it is needed (from internal skills deficits to legal issues when dealing with outside agencies).
Determining what data is in your city’s best interests to control, being able to prioritise value over quantity, and being able to respond agilely within council to new opportunities as they arise requires a depth of understanding in key business areas across the administration.
Some larger cities have been able to invest in their data and digital resources with strategic leads in place and governance strategies well-evolved. Others are less able to invest and could benefit from a more collaborative approach. Working out what data your city owns, what it wants to control or manage, and what it would prefer others to manage is key to getting optimum value from your data.
G20:
There’s no place like the top, and so it is worth mentioning the G20 Global Smart Cities Alliance and its newly launched Open Data Model policy. OASC was pleased to be a founding partner of the Alliance which was launched at the G20 in Japan in 2019 ‘around a shared set of principles for the responsible and ethical use of smart city technologies’. The G20 GSCA adopted this Open Data Model Policy in 2020.
London
London is a good example of a city that has had the capacity to invest from the top down - with a Chief Digital Officer and team to support a strategic approach as well as a city-wide resource to wrangle data - the London Office of Technology and Innovation - a collaboration between London governments that offers a range of resources available for others to use.
The Swedish Association of Local Authorities and Regions
The Swedish Association of Local Authorities and Regions provides a prime example of what smaller cities can do when they collaborate, combining their resources to create a governance structure and infrastructure to support their shared open data goals. The work is in the context of a root and branch approach taken by the Swedish government nationally, and reflects a deep integration of open data principles.
Smart Flanders Checklist
Smart Flanders checklist is an excellent place to start if you are looking to understand what might be missing from your city approach. Both pragmatic and comprehensive, it addresses all the key elements for a city looking to open its data as part of a smart city strategy. If you are looking for something a little more detailed, the Smart Flanders Open Data Charter might fit the bill.
Smart Flanders Checklist https://smart.flanders.be/kennis-en-instrumenten/checklist
Eindhoven Smart Society IoT Charter
Eindhoven’s smart society IoT charter provides a clear set of principles to support cities in adhering to values when working with data from external sources and all that cities subsequently do in the data economy.
https://data.eindhoven.nl/explore/dataset/eindhoven-smart-society-iot-charter/information/
Being able to purchase services linked to data is a specialism in itself and one that all but the larger cities can typically afford. Smaller cities, in particular, struggle to come up to par when buying this level of expertise. Collective solutions, from which smaller towns and cities can benefit, are beginning to emerge. Consider reaching out to cities that have already achieved good results.
Cities have reported being relatively deskilled when it comes to the detail of data manipulation - often contracting out the task to third parties like learning institutions; while this works for some, others want to take a more nuanced approach - ensuring in-house staff have a range of both technical and strategic data skills to enable a varied approach dependent upon the context.
London's LOTI Innovation in Procurement toolkit
CITYxCITY Academy:
Free online learning resources on data, data-driven innovation and tech for cities. https://citybycity.academy/
CITYxCITY Academy |
Cities that have previously invested may find themselves in vendor lock-in for specific services without the financial wherewithal to drive a new back-at-base path - and are therefore looking for ways to reroute data, or wrap legacy systems with less costly cloud-based interfaces.
Broadly, these challenges can be classified into the ongoing issues cities have in managing their data resource, including a focus on internal challenges, and in working with partners, citizens and other cities, such as:
Strategy and insights go hand in hand and, for cities that have outsourced data management, they are often caught in a defined loop of insights production - unable to vary the demands without cost implications. The power of data is in the insights it can bring, particularly when integrated with more than one source, and cities want to have more flexibility in understanding highly complex issues through different lenses.
A number of companies, large and small, offer a range of tools that support analysis and insights - either in domain-specific areas or across a range of city data.
Free online learning resources on data, data-driven innovation and tech for cities.
CITYxCITY Catalogue
CITYxCITY Catalogue offers a springboard into an array of solutions compiled by cities for cities, or products and tools that can help with your city’s data infrastructure needs.
Smart Flanders Checklist
Starting with the Flanders checklist might help to develop your own data maturity model.
CITYxCITY Catalogue
Be sure to check out what is available on the CITYxCITY Catalogue.
CITYxCITY Catalogue |
Be sure to check out what is available on the CITYxCITY Catalogue. |
While internal challenges can be all-consuming, external challenges for cities are also very real and include:
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To negotiate with commercial partners
Commercial negotiations are never easy and cities tend to be at a disadvantage as their legal teams are generally not focused on this type of deal. Yet there is hope; cities can learn from innovators and the possibility of pooling wisdom is tantalising.
While the following are just two examples, OASC is looking for ways to broaden cases and support for cities in negotiating with commercial service providers for shared data. Watch this space.
The City of Lisbon
The City of Lisbon is one such authority that has successfully negotiated to receive data from a corporate provider (in relation to a city bike scheme), as part of its urban data platform.
The City of Ghent
The City of Ghent also successfully negotiated to receive data from waste contractors to tackle fly-tipping.
Data-driven innovation is throwing up a raft of new ethical dilemmas with which cities are having to wrangle. Data that is consumed by AI or machine-learning devices to generate further insight is a hot topic right now. AI-informed operations are being particularly deployed at spatial level, for example, via traffic cameras or to better understand crowds.
One key concern is the extent to which algorithmic learning and decision-making is safe, unbiased, accurate and effective. So, too, is the value of individual privacy in an increasingly surveilled world. Innovators are driving towards solutions for many of these challenges by moving the dial from citizens having to be actively across all engagement with actors seeking to use their data, to spaces in which a person’s intentions are effectively carried through myriad interactions online or via other forms of digital/AI engagement.
In the new data economy, cities are asking searching questions about which data is acceptable to monetise, and which is not. It is possible that some unintended consequences could emerge from data exploitation decisions that leave cities in a legally and morally grey area. The ethical debate surrounding data and tech-driven innovation will continue to evolve as new challenges emerge. While cities are unlikely to want to put themselves at the centre of these debates, it is critical that they continue to engage with the conversation, recognising when consensus has been reached on key elements, and being able to respond appropriately.
Some cities are working ahead of the curve - creating principles to guide their interaction with AI-based innovation and applying it to real-world solutions. OASC will soon produce further guidance on AI - watch this space.
Barcelona
Barcelona’s work provides a useful starting point. https://ajuntament.barcelona.cat/digital/en/blog/barcelona-promotes-the-ethical-use-of-artificial-intelligence
Amsterdam AI Registry
Helsinki AI Register
MIMs
For our take on transparency, please take a look at MIMs 5 - it’s all about transparency and has been adopted as the common ground for working in a transparent manner.
Working in spaces where there is an evolving regulatory and standardisation environment - legislation, regulation, standardisation… the MIMs are all evolving, which is great news for better defining the so-called rules of the road, but cities are keen for greater clarity about what to expect and when. Working in isolation is particularly tough for smaller cities – or for those where the challenges are less common.
OASC |
OASC is a key source of guidance for its members on standards, MIMs and regulations. |
The new challenges thrown up through the process of innovation – including disruptive tech; this, alongside a changing regulatory environment, makes innovating more risky than it needs to be.
Cities are looking for ways to de-risk innovation so that they do not fall foul of ethical and legal principles. Working with Living Labs and other learning and deliberative structures that are designed to sandbox risk is a helpful way to overcome this.
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Living in EU
The Living in EU programme will provide information and support on digital transformation, and currently offers the opportunity to join groups for collaboration on shaping ethical and legal principles for Europe.
<b></b>Living-in.eu<b></b>
European Network of Living Labs (ENoLL)
At a more applied level, the European Network of Living Labs (ENOLL) offers a way to work with innovators with the know-how to do so safely and ethically.
<b></b>www.enoll.org<b></b>
Innovation can and does provide enormous new benefits that were hitherto unobtainable: the capacity to seek the wisdom of the crowd through a touch of a button, or to engage in deeper forms of transparent democracy through citizen-centric processes is made possible through the power of data.
The ability to offer profound transparency in what have been largely opaque and complex spatial decision-making processes, for example, is a radical transformation in city governance. There is so much potential to innovate in cities, it is a virtual data goldrush. Data development rights - facilitating ‘airspace’ development over data fields - is one such rich seam of exploitation.
As cities recognise the data they have and the value this brings, there will be opportunities to lock this worth into the city’s future, rather than locking out future generations. OASC will work with cities to help them garner the most value, ethically and safely.
It is perhaps unsurprising to reflect that city priorities for the next 3-5 years all revolve around using cloud-based services to help cut through the ‘noise’ of legacy issues, and being able to take full advantage of innovation as it comes on stream.
Cloud-based approaches are evolving just like other areas of the data and tech-driven innovation revolution.
Core concepts include local data spaces - places where towns and cities (and other organisations) can store data for use by stakeholders, and where data integration occurs on a tactical basis - generally in a user-pays format.
Where to look for more tips and guidance:
Tend to be spaces where an organisation or several can include data within the space or lake - and in a range of formats and states of completion/hygiene. This enables users to work with data at different stages and from a range of different sources. The lake acts in an agile methodology as an unstructured store - meaning that the data is not necessarily curated, but ensures that it can be used randomly in many different applications.
Where to look for more tips and guidance:
Where there’s a lake - there’s a lake house! Along with data lakes, providers are realising that the tools to collate and analyse data are also handy to understand data in various contexts (in essence, supporting its curation).
Open Data Portals provide generally curated data for public consumption. Many cities have established portals, and some cities have worked together to create regional portals. The advantage of portals offering data across more than one town or city is that when a stakeholder is looking for energy-related data for example, they can see data from a range of city contributors - thereby making benchmarking and other interoperability-related tasks far easier.
Where to look for more tips and guidance:
Takes the concept of the cloud and creates the conditions for data to be at least temporarily stored, manipulated and even generated within a local device. This helps to reduce latency in operations and increase cyber-security. A number of applications now deploy edge-to-cloud technology for these purposes.
Urban/local data platforms and open innovation platforms are spaces that combine the benefits of open data portals with the analysis and insights capability of dashboards. Cities are increasingly attracted to the capacity to manage insights generation through platforms and systems offering a way for integrated data to be created and analysed. These can be on a city by city basis, for a region or for multiple cities.
We’ll be collating more detailed information on urban/local data platforms soon - watch this space.
Rapid pandemic data analysis
This technique has been used to produce rapid data analysis as part of the COVID-19 pandemic. See, for example, this project from Leeds.
https://lida.leeds.ac.uk/research-projects/local-data-spaces/
ODALA
See the ODALA project to create a data lake for smart cities and communities in Europe.
https://oascities.org/odala-developing-the-future-of-smart-cities-communities/
City of Kiel Open Data Portal:
Istanbul - an example of a mega city's open data portal:
The truth is that open and agile cities are evolving all the time, and so is the ecosystem that supports them. What once was the sole purview of a handful of city pioneers is now a burgeoning community of city managers, ready and willing to embrace the future mindfully - and with environmental, societal and economic resilience at the core of their approach.
Like with all good stories, the heroes are never truly alone, and so it is with open and agile smart cities: there is a veritable array of innovators, SMEs, infrastructure providers, financiers, citizen groups, learning institutions and corporate partners that make up the ecosystem helping to keep cities networked, engaged, enlivened and inspired.
Some of the most effective solutions have emerged from within the ecosystem: collaborative working across cities…(Finnish data lakes is just one example) and it is these solutions that demonstrate the power of multi-lensed connection.
OASC is by cities, for cities - and, with this firmly in mind, it has set its sights on bolstering the power of cities and city ecosystems to meet their challenges head-on as we march further into the data and tech-driven age.
OASC is partnering with a number of enterprise organisations that contribute to the open and agile smart city ecosystem to continue our work in developing the tools and support that cities need.
Over the next 12 months, we will engage with cities and partners to:
Co-create innovation at scale through EU and other large-scale programmes;
Continue building out the OASC CITYxCITY Catalogue and Academy;
Hold the CITYxCITY festival - enabling all sections of the ecosystem to gather in a series of deep dives on the issues, use cases and innovations that drive our movement forward;
Find new ways to support cities, including through our City Chapters;
Produce more papers like this one, shining the light on Digital Twins, Data Trusts, AI and more.
If you are interested, OASC is free for cities to join and complimentary services are provided, contact us at info@oascities.org.
It is easy to be overwhelmed by the many challenges and opportunities facing cities. One way to begin is to take a single bite - rather than trying to ‘eat the whole elephant’. With this in mind, we suggest that cities wanting to start out on this journey consider three basic steps first:
Knowledge is power.
You can't manage what you can't measure.
Start with a problem looking for a solution, not the other way around.
Select a challenge that could be solved through better quality data, or additional information, or through insights derived from the information the city already has access to.
What kind of problem could you focus on and what are the drivers - is it improved efficiency, better budget bottom line, or improved customer service?
Aim for something that is not going to take years to resolve and with clear data boundaries; a distinct issue that - with the help of some good data informatics - will garner support and be matched to a solution is an ideal starting point.
The City of Belfast took this approach when it tackled business rates. The city worked with internal stakeholders to share data across silos, allowing the matching of ratepayers to business addresses more effectively. Using a range of machine learning tools, the project delivered results quickly. The impact was a rise in rate payments and an effective business case for internal stakeholders on why data sharing can add value to the city’s bottom line.
https://smartbelfast.city/story/using-machine-learning-to-aid-rates-collection/****
Once you have selected a priority issue for the city (eg. business rates), finding out what data is being collected, how and by whom is key to understanding the landscape of the problem.
Establish a broad sense of whether the data is quality (error-free), how much cleansing is required, whether it can be shared, and how much of it is likely to be useful.
Does the problem require a solution that helps to resolve data challenges, or is data that is ready and available necessary for the solution (or both)?
For example, in the case of the City of Belfast, the solution meant matching data across silos so that missing information was resolved. This required city teams to share data for the first time in order to match it. The outcome was that ratepayers were charged appropriately and fairly - and the city could recover missing revenue.
Once you have worked out what kind of solution(s) you need, consider the ones available on the OASC CITYxCITY Catalogue. You may also find that other cities are willing to talk about the solutions they have implemented.
Design the pilot so that it is clearly sandboxed from other city operations with a manageable timeframe, budget and dedicated resources so that, once the results are through, they are clear and demonstrable. They will act as your call to action for seeking further value from your city’s data.
Your pilot should give you all the evidence you need to make the case internally for using city data to extract greater value (whether this is financial, insights driven, or operational).
As a member organisation, OASC is always keen to hear from cities about their experience of trying out new ways to be open, agile and smart. We are cities after all!
Get in touch: info@oascities.org
If cities thought things were fast-moving, communities are also under a veritable tidal wave of new information and ways of transacting everyday life that threatens to swamp all but the most able and aware.
The digital divide is such a serious concern that it is being taken up at national and international government levels - with worries that it is impeding productivity and worsening inequalities. Cities are no exception, and with a focus on citizen-centric innovation, they must find ways to keep people engaged and involved, without tech and data becoming a barrier.
In the course of producing this guide, OASC cities have also highlighted some additional priorities that will bring considerable additional capacity to cities and city networks, including:
The capacity to ‘see’ the city in digital and miniature spatial form as an aid to strategic and spatial planning and decision-making is a goal shared by most cities within OASC, and for the EU as part of the Digital Europe Programme. For some, this is a virtual 3D model of the city, ascribed with core data values, like construction timelines, built form composition, zoning and other planning aids. For other cities, the digital twin is something they hope will enable dynamic decision-making through the integration of data sets from across the city into something that could act as a scenario or diagnostic toolkit. For example, enabling the overlaying of carbon scenarios on new development plans, or the calculation of health benefits from nature-based solutions...and so on. While digital twins have been around on a small scale for a few years now (having been successfully deployed in the engineering world to resolve complex design challenges since 2002), the capacity to create city-wide digital twins is something that is only emerging now as a reality for cities everywhere.
Where to look for more tips and guidance:
Digital twins will be addressed as the topic of a separate white paper - please stay tuned.
Data, application and tech marketplaces offer cities an exciting opportunity to engage with innovators that wish to purchase access to data in order to deliver a product or service. Tools developed to support data integration or data consumption into specific products can also be bought and sold in city data marketplaces - enabling a virtual ecosystem of tradeable virtual goods to exist that supports the strategic goals of cities. They provide one way for cities to have greater control over how data they own is used. Some city conglomerates are looking to create their own marketplaces, often linked to data lakes. In the meantime, the OASC CITYxCITY Catalogue is a good example of a functioning marketplace.
Partnerships with corporations, learning institutions and third sector organisations are key to OASC cities in developing ways to work more smartly with data. Partnerships offer cities the opportunity to do what they do best, while allowing others to bring their best game to the table. Whether this is through data-sharing agreements, skilling, insights development, data lakes or any of the other tools and approaches, cities are recognising that there is no viable option to ‘go it alone’ in the world of data-driven innovation. Cities are looking for ways to best shape partnerships that offer value to both parties without ‘giving away the farm’.
In our view, this is the way forward in securing the best outcomes for cities in the data economy. Rather than competition, which depletes competitive resources, strategic co-operation provides a platform for cities to learn from each other and to collaborate on projects and platforms - facilitating ways to address challenges such as size, budget and skills across a pool of aligned administrations. Many OASC cities are benefiting from city co-operation arrangements, including the Scottish Cities Alliance, Swedish Cities and Regions Association and cities in Finland (eg. Turku and Helsinki).
Where to look for more tips and guidance:
Unsurprisingly, this features at the top of the list for some cities. Whether this is working on how to disentangle from legacy systems, or driving better governance through existing programmes, cities are keen to embrace data-driven innovation with a fresh approach to how they control the data they own, and the data they consume or share.
The opportunity to leapfrog from legacy to cutting-edge is now available, including by taking a tactical approach to priority issues (small cities, in particular, can benefit from laser focus rather than broad-brush when escaping the drag of legacy issues). A key pathway is through cloud-based services.
Where to look for more tips and guidance:
Digital Innovation Hubs
Reach out nationally to see what is available near you - and if you are in Europe, a good place to head to is your nearest Digital Innovation Hub. https://s3platform.jrc.ec.europa.eu/en/digital-innovation-hubs-tool
CITYxCITY Academy
The CITYxCITY Academy is one way to help cities work with communities to share knowledge and engage people in different walks of life and sectors.
Digital Twins
The Finnish Six Cities Strategy
Open and Smart Services - known as ‘6Aikia’ - is an excellent example of the way in which co-operation is being applied strategically to collectively solve complex challenges with open data at its core. Operating across the six largest cities in Finland, the strategy has three focus areas: Open Innovation Platforms; Open Data and Interfaces; and Open Participation and Customership.
https://6aika.fi/wp-content/uploads/2015/11/6Aika-strategia_päivitys_2015_EN.pdf
Saint Quentin
Saint Quentin is an example of a city that was able to create a cloud-based function to manage water usage in parks and gardens as well as other services across the city. The city decided that it wanted to use a context broker within the cloud rather than via a back-at-base vendor system, enabling a flexible approach.
https://data.europa.eu/fr/news/cef-context-broker-saint-quentin
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As a member organisation, OASC is always keen to hear from cities about their experience of trying out new ways to be open, agile and smart. We are cities after all!
📧 Get in touch: info@oascities.org
AI Artificial Intelligence is defined as the capacity for a computing system to perform tasks that would normally require a human to undertake them (e.g. reading, language-translation, decision-making).
AI-enabled machine learning Machine learning is based on the idea that we require information in order to make informed decisions. The more information we have, the greater chance we have to make a better decision (at least in theory). Machine learning uses algorithmic processes to incorporate new information into decision-making as the AI progresses. This is used to refine task parameters, to understand the impacts and influences on outcomes, to increase the accuracy of outcomes, and to perform tasks for which there is too much information to process (i.e. beyond human capability). Typical examples of AI-enabled machine learning are tools that can be customised to a person’s individual preferences, or that crowdsource information to identify risk or other parameters. Much controversy surrounds some machine learning tools in relation to the accuracy of the algorithmic processes, due to concerns that bias can be inadvertently built in at the outset by the humans who set the initial design challenge (unconscious bias). Within cities, AI-enabled machine learning is particularly applied to information derived from sensors (e.g. to monitor air quality patterns, noise monitoring, crowd behaviour etc).
Biophilic design principles for cities Principles that draw on the way in which humans relate to nature while being immersed in it, observing it and being ‘of’ it. The principles inform individual building design as well as, fractally, at city scale (access to air, light, water, animals etc). At a deeper level, biophilic design links closely to biomimicry, which replicates natural engineering found within certain organisms to achieve specific results (e.g. nutrient transport, shade, hydration, network communication) and is often applied when designing climate-resilient solutions. These two concepts, applied together, at city scale meet the conditions of being in, drawing on, being of, and observing nature as part of an urban experience.
Blockchain A cryptographic means by which a distributed ledger can be created, using a series of time-stamped, cryptographic blocks of data. The system is considered highly secure as it does not require a centralised authority or server. Typically, they are managed by peer-to-peer networks. Due to their high level of security, blockchains are used by cryptocurrencies. There are many potential applications for blockchain distributed ledger technology beyond cryptocurrencies. Blockchain technology is highly energy intensive and this remains a key concern about its widespread usage.
City systems Understanding the city in terms of city systems requires a system-thinking analysis. City systems within this framework are a series of interconnected pathways, from nature to the economy. Within this approach, all systems have interconnections but some systems have greater interconnectivity with others (e.g. energy, water, waste; food, waste, water; health, transport, air quality). Systems theory is also used widely in digital applications and smart city systems draw on both digital/computing and on ‘city-as-a-system’.
Complexity (in the context of city systems) A concept that reflects that city-as-a-system highlights that no problem can be solved by one actor alone due to the interconnectedness of city systems. A siloed approach can do more damage than good if the knock-on effects into the wider system are not fully understood. Complexity therefore requires a multi-stakeholder, multi-system approach to resolve challenges at scale.
Context broker A piece of software designed to gather reachable context data. It harmonises different data sets using standard data models so that they can be read and accessed by analysis and visualisation tools.
COVID-19 The viral disease that results from being infected by the virus SARS-COV-2. The virus was first discovered in China in 2019 and spread quickly across the globe. It was declared a pandemic by the World Health Organisation in March 2020.
Data Any collection of information that is grouped together. For example, the different pieces of information on an invoice is data about a financial transaction. When ordered, data can be considered a data set.
Data aggregation The process of gathering data from multiple sources and presenting it in a summarised format. Data aggregation can comprise multiple datasets within an organisation or from across organisations.
Data (and tech) Driven Innovation (DDI) A term that refers to the innovation processes occurring because of data emerging from a particular area. New data and insights might reveal the need for new solutions. A good example is the DDI that has occurred as a result of the pandemic - where epidemiological insights have driven innovation in tech applications (e.g. test and trace apps) as well as non-technical solutions (e.g. restaurant seating).
Data economy An economic concept for describing the way in which data has a monetary value based on its application. The ubiquity of data that has value means it can be exchanged widely and for many purposes. The data economy alludes to a system of exchange where the data itself becomes the ‘currency’.
Data ecosystem (cities) The series of components required by an organisation to use data intelligently. This includes infrastructure and applications to deliver analysis and insight capacity and usually the application of AI. Within the context of an open data ecosystem, the range of technologies and applications required spans many organisations that are working within the ecosystem.
Data lake A space within which an organisation or several that can include data in a range of formats and states of completion/hygiene. This enables users to work with data at different stages and from a range of sources. The lake acts in an agile methodology as an unstructured store - meaning that the data is not necessarily curated, but ensures that it can be used randomly in many applications.
Data maturity The level to which data is being used and integrated into an organisation’s strategic approach to achieving its goals. Data maturity implies that data is being reviewed and refreshed regularly across the board.
Data sharing The process by which data is shared to enable multiple users to access it without the original data being altered. This implies a way to lock the data so that it cannot be altered or manipulated at source.
Data silo A collection of data that is isolated from other data within an organisational or governance field. The silo’s isolation means that other data sources are unable to interact with the data within the silo, creating a barrier to data analysis and insight. The silo might arise through physical, governance or management factors and may be proactively established or created by default.
Data spaces (and local data spaces) Places where towns and cities (and other organisations) can store data for use by stakeholders, and where data integration occurs on a tactical basis - generally in a user-pays format. This technique has been used to produce rapid data analysis as part of the COVID-19 pandemic.
Data visualisation The act of portraying data in visual terms to highlight a data insight or to demonstrate data analytics (e.g. as a graph, chart, diagram or even as an animation).
Digital divide Describes the difference between those who are able to take advantage of the digital economy and those who cannot. The digital divide is increasing and is now considered an urgent challenge for communities worldwide.
Digital literacy One of the key contributors to where individuals sit in relation to the digital divide. Age, affordability, skills, access to education and employment are all critical elements in determining whether a person is likely to be digitally literate, and the extent to which they will remain literate throughout their lifetime.
Edge computing The capacity for computing power to be deployed ‘at the edge’. The edge is defined as being at the edge of the cloud or in a localised location. Computing power deployed locally enables tasks to be directed with lower latency because the computing power is physically closer to the activation site.
Extreme weather events A range of weather phenomena that are unusual and extreme for the local climatic conditions in terms of frequency, type, and severity - or where the event is rare yet typical, but its severity is not (e.g. increasingly severe hurricanes within areas that already experience them).
5G Refers to the fifth generation wireless network. The 5G network is being rolled out in cities globally and is expected to deliver transformative change to the data and telecommunications industry by increasing the amount of data that can be uploaded or downloaded at any one time 10-20 times faster than is currently available under 4G technology.
Healthy mobility A concept that puts the person at the heart of transport solutions. Healthy mobility therefore refers to any mode of human transport that promotes health for the user, such as walking and cycling, and that forms a substantial part of the journey (e.g. a 15 minute walk at the beginning and end of a commuter mass transit journey). In designing for healthy mobility, the quality of the urban environment is considered to determine whether a person is able to use the route safely, securely and regularly (e.g. lighting, trip hazards, air quality etc).
Housing management voids The process by which housing providers manage properties becoming vacant in the cycle of total housing management for a portfolio.
Insights (related to data) Data insights are created when information is gathered to create data, which is analysed, usually in relation to more than one data set or source, when patterns are identified and an insight is revealed that was otherwise obscured. Data insights require data analysis (or analytics) in order to reveal patterns and trends within the data.
Nature-based solutions (in the context of cities) An umbrella term encompassing solutions to a range of urban and nature-based challenges drawn from and incorporating nature as part of the solution. The concept relies on understanding how natural systems work to resolve naturally occurring challenges, and to incorporate this logic and design into the wider urban field. This is often undertaken in conjunction with interconnecting solutions resulting in multiple social, environmental and place-based benefits (e.g. borrowing elements of natural floodplain dynamics in designing urban flood responses in regard to urban rivers and canals).
Net Zero Strategy A strategy for a city to drive down greenhouse gas (GHG) emissions deriving from activities and consumption within the city to as close to zero as possible, while addressing remaining emissions via technological and non-technological means of taking carbon dioxide out of the atmosphere. The timeframe for achieving net zero is crucial in understanding whether the strategy will materially support global efforts to change the trajectory of global warming. Some net zero strategies have been criticised for setting net zero targets over a timeframe perceived as being too late to prevent excessive warming.
Open and agile (in the context of cities) Refers to data being ‘open’ for others to use, including by the city itself. Agile, as a concept, is grounded in computing project management approaches where new stages can commence before the previous phase has been completed or as and when required - breaking tasks into short bursts and allowing for results to be incorporated quickly. Agile approaches are often used in innovation to speed up outcomes (e.g. testing different parameters in parallel and incorporating the learnings from varying streams while the innovation is still being tested. Open and Agile Cities are those that work transparently with data, fostering innovation within an ecosystem of actors. It is closely linked to the concept of Open Innovation.
Open data At its core, this is data that can be freely used, re-used and shared by anyone. To be able to fulfil this criteria, the data needs to be made available (i.e. published) and can be accessed by people or a machine. The format for publishing and accessing open data is not straightforward. Many organisations purporting to provide open data publish it in formats that are not digital (i.e. non-machine readable), making it difficult to re-use the data through analysis or aggregation.
Open Data Platform Similar to Open Data Portals in that they are publicly available websites from which open data can be accessed. However, Open Data Platforms tend to include data analysis and visualisation in, for example, a dashboard format. These can be applied to any sets of data (health, mobility, sustainability) with cities being one of many organisational types establishing and using them.
Open Data Portal Websites established by organisations that generate and/or own data that could be considered ‘public’ in that it is in the public interest for it to be made available. The portal might host data about a range of attributes linked to a specific topic or topics, generally for public consumption (e.g. policing, health, environment, housing etc). Many cities have established portals, and some cities have worked together to create regional portals. A critical underlying reason Open Data Portals have been established is the commitment of information providers to the implicit or explicit right of the public to access information in a democratic and transparent way. Not all Open Data Portals provide fully machine-readable data, or provide all data as machine-readable. This limits their usefulness in creating interoperable opportunities for re-using the data.
Pandemic A global or country-wide epidemic with infectious disease affecting a large population/s as determined by the World Health Organisation.
Resilient The capacity to withstand shocks to the system, or to create a new stable state following a system shock. Resilient cities are those which, through adaptive capacity, can withstand such shocks. With its origins in ecology, the term is widely applied in systems theory, and additionally in computer science. Redundancy within a system (the capacity to draw on extra resource, storage etc) is one way to create adaptive capacity. Single points of failure are avoided in resilient systems.
Sensing, automating and intelligent technologies Devices that undertake these functions separately or in combination: sensing - can identify external stimuli (e.g. temperature, moisture, movement); intelligent - can create information from this data to inform decisions on the next action(s) that can be made independently of human involvement; automating - can undertake tasks that otherwise would require human control (e.g. turning on/off devices, activating an activity such as cleaning or searching).
Sensitive data Data that cannot be made open or fully open, and which may only be shared with limited users due to its nature. The data could be considered sensitive for a range of reasons including that it is commercial, personal, IP-related, legal/security related, of national importance etc.
Shared data Data that can be accessed by multiple users at the one time without altering the original data. Shared data can be ‘open’ in that it is available to all users. It can also be ‘closed’ in that users of the data must have the required permissions to access the data, but it cannot be made public or be accessed by users beyond those who have access permissions.
Smart (in the context of cities) While many definitions exist, the OASC concept of ‘smart’ can be summarised as a city that is enhanced by a range of interoperable, replicable, ethical technologies and data driven insights (impacting city systems, health and wellbeing, economy, nature and society). The concept is not divorced from ethical values and recognises city diversity in terms of culture, technical, economic and social structures.
Smart, healthy ageing Healthy aging puts the person at the centre of their aging process, looking for ways to improve health and quality of life, or to minimise negative impacts over time. Smart, healthy aging focuses on ways tech and data can enhance healthy ageing strategies (e.g. smart materials used in clothing to minimise temperature disruptions, personal alarms and reminder devices, personalised services for navigation and completing everyday tasks).
Standard data model An agreed format for organising data with particular attributes (e.g. a standard data model exists for air quality, noise, velocity etc).
Tech As opposed to the more general term ‘technology’, tech refers to technology applied within the data-driven space. This includes tech deriving from quantum, edge, IoT, hybrid computing, and in relation to telecommunications (5G/6G). Applications can be across any field of activity (e.g. finance, health, agriculture, urban design) and can be aimed at individuals or at other scales (e.g. company through to supply-chain).
Urban Heat Island Effect (UHI) The micro-climatic impact of stored heat within the thermal mass of urban areas (paving, roadways, building surfaces) creating large areas of elevated heat after the radiant heat of the sun has disappeared. The concept is widely recognised as a key contributor to human health impacts from climate change in cities, although UHI can exist without being caused by a changing climate. Mitigating actions include those that reduce the cause of UHI and lessen its impact (active and passive cooling of cities, people and animals).
Urban/Local Data Platform Spaces that combine the benefits of open data portals with the analysis and insights capability of dashboards. They can be synonymous with Open Data Platforms, but not necessarily. For example, Urban Data Platforms may not be fully open, and, as the name suggests, are focused on metropolitan areas. Variations on nomenclature (naming) can occur to encompass data platforms that reach across cities, towns and rural hinterland (hence, ‘Local Data Platforms’ or ‘Community Data Platforms’).
Zettabyte A measure of digital data storage capacity, defined by a single byte. A zettabyte is 1 sextillion bytes.