Data for Good #1 Understanding where we live

Tuesday 24th April 18.30 – 20.30
Federation Street, Manchester M4 4BF

Register on Meetup here

There is a huge amount of data that is collected by the UK Government and others that describes the communities in which we live. This data informs policy decisions at a national and local level. Datasets such as the Indices of Multiple Deprivation have been described as the ‘billion pound dataset’ because of its importance.

Outside of the world of data analysts and academia these datasets are relatively unknown, yet they can be incredibly useful to anyone who is interested in their communities, wants to develop evidence for funding applications or is thinking of developing a business in a certain area.

Data for Good #1 follows on from our So you think you know your country? events and gives deeper insight into some of the data available. The seminar will introduce the world of statistical geography and some of the datasets and tools you can use.

As the event is going to be more hands on, access to a laptop would be advantageous, but not essential.


Manchester Youth Hack # 8 The Open Data Manchester Challenge

Manchester Youth Hack is a two day coding competition where young people get to try coding in a friendly environment with professional mentors. The next event is 24-25 March.
If you are interested in getting involved more information can be found here

The challenge

On three floors of Federation House there are sensors measuring temperature, humidity and movement producing a dense dataset of many thousands of data points. The data allows the performance of the building to be monitored to save energy and money, but what else is it showing? Something has happened and no-one is quite sure what it is.

We will be making available two weeks of sensor data from the sensor network that has been created as part of our Knowable Building Framework. What will the data reveal?.

Knowable Building Framework – building consent – Rennes workshop

En français

The Knowable Building Framework is a consent building framework for the release and sharing of data from sensor data captured in buildings. The Rennes workshop took place on the 18th January with 22 participants who had an interest in energy, internet of things, environment and civic technology. The meeting took place at Telecom Bretagne (IMT Atlantique).

The focus of the discussion was broadly split into technology- looking at the types of sensors being deployed in the pilot project and the data being created- and human- how the data could be used to affect behavioural change and the implications of having a dense sensor network in a building.


The Knowable Building Framework pilot in Manchester is located in an office building with sensors on a number of floors. The sensors measure temperature, humidity and motion on two floors and another floor also measuring light. The sensors are discrete and battery powered using a LoRaWAN (Long Range Wide Area Network) to send data to an intelligence platform that displays measurements on a dashboard. The information can then be used to determine time of activity within a building and how different areas are used; temperature variation over time allowing the ability to adapt heating so that it is more inline with occupancy; and humidity within areas which can be used to identify underlying issues with ventilation and damp. The light sensor modules allow the detection of room lighting.

Placement of sensors

Placement of the sensors within the building was based upon the need for the system to optimally collect data. Zones on floors, entrance areas, meeting rooms are covered. Importantly the sensors were placed in what could be considered common usage spaces i.e. spaces that were owned and operated by the building company for the benefit of all tenants and users. Areas where a tenant had exclusive access were excluded.

Preliminary insight gained from the network

A small number of sensors has already been installed and we can see from the online interface that useful data is already being created. Even at this stage we can see start to see how the building functions over the course of a number of days. We can deduce when the disparate heating systems kick in, which areas have a thermal lag, when cyclists use the storage and shower facilities and the areas that are more humid than others. As the sensor network becomes denser we will be able to see how different areas get used offering the ability to heat certain areas based upon demand.

This all looks very positive from a building management ‘mechanical’ perspective but we already can see that buildings don’t operate in isolation of the people who inhabit and work within them. At this early stage we can see how certain rooms and areas are used more regularly than others. We can start to infer patterns of activity and behaviours of the small number of people who operate the buildings on behalf of tenants. During the day the building is awash with activity that creates a certain anonymity, but out of hours, areas get cleaned, security personnel check spaces and these show up as isolated trigger events within the building. It does not take a big leap of the imagination to realise that a building optimisation platform could also be used as an instrument of surveillance.


There was broad agreement by the group that creating open data from sensor data was a good thing, especially if it could be used to benchmark buildings and enable a greater understanding of how buildings of different types behaved.

Ownership of data was seen as being important. Who is the owner of this data – the building owner or the people who inhabit or work in the space? It was highlighted that there is a relationship between ownership of the data and the power/agency people have within the space. So if you are a building owner you are more likely to feel that the data that you collect is yours as it is your building and a private space even though some of this data may be used to identify individuals. This is analogous to CCTV in that people in CCTV monitored buildings generally have very little say or knowledge of how the systems are operated other than ‘its for your security and safety’, how video is stored or who it is shared with.

Identification of need is really important with creating a sensor network or else initiatives are prone to poor application of technology with the creation of unusable data. There is also a tendency to over collect data or collect the wrong type of data. It was suggested that the forthcoming GDPR regulations might have a bearing on how data is collected within buildings and public spaces.

A criticism of the Knowable Building Framework pilot in Manchester is that the implementation has been undertaken with only the consent of the building managers who can see tangible benefit in seeing how the building operates with little consideration of its occupants.

The group identified that we need to explore how we build networks consensually as this would then be a precursor to building consent. Consensus assumes a number of things that potentially could be challenging for the implementation of sensor networks these might be:

  1. An understanding of the sensor environment’s purpose and how the data will be used
  2. The technology and what it measures
  3. What the safeguards are so that the technology is not abused
  4. Representing concerns if the technology is considered to be abused
  5. Understanding of data sharing and open data

The data that is collected from the sensors in its raw form is a rich sense of information but sharing the data as open data has risks. There are different levels of granularity that could help data owners share data but care would need to be taken in order to identify the appropriate level of aggregation and anonymisation. There is a trade-off between usefulness and privacy.

There was a some discussion on the value of the data created and if it could be used as a commodity to draw down preferential deals for building owners and building users alike. This could have some kind of leverage regarding power suppliers and building insurers.

There exist different classes of stakeholders within the building and it is important that any consent mechanism acknowledges them. These classes roughly break into; owners and management; occupants and users and; maintenance and operational.

Data needs to be available – or at least the intelligence that is derived from the data so that occupants and users of the building can understand for themselves how the building works. This would help in demystifying the technology and make it less threatening but also help people make changes to their own behaviours.

Visualisation could have a big part to play in this process as good visualisation and design enable understanding. By making the data available there is also the possibility to run events around the data to create new ways of creating information and understanding. Rennes has used the Data Remix (a form of hack event) format successfully for a number of challenges and it is suggested that one could be run that includes teams from Rennes in the future.

A further write up of the whole day (in French) can be found here

Faire un compte rendu à partir de l’atelier de travail

« Knowable Building Framework » est un modèle d’ouverture et de partage de données issues de capteurs qui collectent des données au sein des bâtiments. L’atelier de travail à Rennes a eu lieu le 18 janvier 2018 avec la participation de 35 personnes ayant une forte appétence pour les sujets énergétiques, l’internet des objets (IoT), l’environnement et l’appropriation de la technologie par les citoyens.

La rencontre s’est tenue à Telecom Bretagne (IMT Atlantique).

La discussion s’est essentiellement focalisée sur deux volets :

D’abord technologique – il a été question de chercher des types de capteurs déployés dans le projet pilote et les données créées – et d’autre part Humain – comment les données pourraient être utilisées pour induire un changement comportemental et les implications d’avoir réseau de capteurs dense dans un bâtiment.


Le projet pilote « Knowable Buildings Framework » à Manchester est situé dans un espace de Co-working contenant plusieurs capteurs répartis sur un certain nombre d’étages. Les capteurs mesurent la température, l’humidité et les mouvements sur deux niveaux et sur un autre niveau, les capteurs incluent également la luminosité.

Les capteurs sont discrets et sont alimentés par des batteries LoRaWAN (Long Range Wide Area Network) pour envoyer des données à la plateforme intelligente qui affiche les mesures sur un tableau de bord.

Les informations peuvent ensuite être utilisées pour déterminer l’activité au sein du bâtiment et la manière dont les différentes zones sont utilisées.

La variation des températures au fil du temps permet d’être en mesure d’adapter le chauffage afin que ce dernier soit plus en adéquation avec l’occupation de l’espace. 

Les informations relatives à l’humidité dans les espaces peuvent être utilisées pour identifier des problèmes sous-jacents tels que des problèmes de ventilation ou d’humidité.

Les modules de capteurs de lumière peuvent être utilisées pour détecter une présence afin d’éclairer la pièce.

L’emplacement des capteurs

Le placement des capteurs dans le bâtiment est basé sur le besoin pour le système de collecter de manière optimale les données. Les espaces au niveau des étages, les zones d’entrée et les espaces de réunion sont couvertes pour les besoins de l’expérimentation.

Point important, les capteurs sont placés dans ce que l’on pourrait considérer comme des espaces communs, c’est à dire les espaces qui appartiennent et sont exploitées par l’opérateur pour le bénéfice de tous les locataires et utilisateurs du bâtiment. Les zones où les locataires avaient un accès exclusif ont été exclues.

Aperçu préliminaire issu du réseau

Un petit nombre de capteurs ont déjà été installés et nous pouvons voir à partir de l’interface en ligne que des données utiles ont déjà été créées. Même à ce stade, nous pouvons voir comment fonctionne le bâtiment en l’espace de quelques jours. Nous pouvons voir les variations de température du système de chauffage, les zones avec un décalage thermique et les zones qui sont plus humides que d’autres.

Au fur et à mesure que le réseau de capteurs se densifie, nous pouvons voir comment différentes zones sont utilisées, offrant la possibilité de chauffer certaines zones en fonction de la demande.

Tout cela semble très positif d’un point de vue « mécanique » de la gestion du bâtiment, mais nous pouvons déjà constater que les bâtiments ne fonctionnent pas isolément des personnes qui y habitent et qui y travaillent.

A ce stade précoce, nous pouvons voir comment certaines pièces et zones sont utilisées plus souvent que d’autres. Nous pouvons commencer à déduire des modèles d’activité et de comportement d’un petit groupe de personnes qui exploitent le bâtiment.

Pendant la journée, le bâtiment est inondé d’activités qui créent un certain anonymat, mais en dehors des heures d’ouverture, les zones sont nettoyées, le personnel de sécurité vérifie les espaces et ceux-ci apparaissent comme des événements déclencheurs isolés dans le bâtiment.

Il ne faut pas faire un gros effort d’imagination pour se rendre compte qu’une plateforme d’optimisation des bâtiments pourrait également être utilisée comme un instrument de surveillance.


Le groupe a été largement d’accord pour dire que la création de données ouvertes à partir des capteurs a été une bonne chose, surtout si elle pouvait être utilisée pour comparer les bâtiments et permettre une meilleure compréhension du comportement des bâtiments de différents types.

La propriété des données était considérée comme importante. Qui est le propriétaire de ces données – le propriétaire du bâtiment ou les personnes qui habitent ou travaillent dans le bâtiment – Il a été souligné qu’il existe une relation entre la propriété des données et le pouvoir que les personnes ont dans l’espace.

Ainsi, si vous êtes propriétaire d’un bâtiment, vous avez plus de chances de penser que les données que vous collectez vous appartiennent, car il s’agit de votre bâtiment et d’un espace privé, même si certaines de ces données peuvent être utilisées pour identifier des individus.

De manière analogue aux caméras de surveillance dans la mesure où les personnes se soucient peu de la manière dont la vidéo est stockée ou avec qui elle est partagée, dans les bâtiments, les personnes ont généralement peu de choses à dire ou à savoir sur le fonctionnement des systèmes.

L’identification des besoins est vraiment importante avec la création d’un réseau de capteurs pour éviter que les initiatives soient sujettes à une mauvaise application avec pour conséquence, la création de données inutilisables.

Il y a aussi une tendance à trop recueillir de données ou à collecter le mauvais type de données. Il a été suggéré que les règlements RGPD à venir pourraient avoir une incidence sur la façon dont les données sont collectées dans les bâtiments et les espaces publics.

Une critique du projet pilote « Knowable Building Framework » à Manchester est que la mise en œuvre a été entreprise avec juste le consentement des gestionnaires de l’immeuble qui peuvent voir un avantage tangible sur le fonctionnement du bâtiment. Ces derniers n’ont cependant pas pris la peine de recueillir l’avis des occupants du bâtiment.  

Le groupe a identifié que nous avons besoin d’examiner la manière dont nous construisons les réseaux de manière consensuelle, car cela serait précurseur de la construction du consentement.

Un consensus suppose un certain nombre de choses qui pourraient potentiellement être difficile à mettre en place pour la mise en œuvre des réseaux de capteurs. Ils pourraient s’agir de :

  1. La compréhension de l’objectif de l’environnement du capteur et de la façon dont les données seront utilisées.
  2. La technologie et ce qu’elle mesure.
  3. Des garanties pour que la technologie ne soit pas utilisée à mauvais escient.
  4. La représentation des préoccupations si la technologie est dévoyée.
  5. La compréhension du partage de données et des données ouvertes.

Les données collectées à partir des capteurs dans leur forme brute sont riches en informations, mais le partage des données en tant que données ouvertes présente des risques. Il existe différents niveaux de granularité qui pourraient aider les propriétaires de données à partager des données, mais il faudrait prendre soin d’identifier le niveau approprié d’agrégation et d’anonymisation. Il y a un compromis entre l’utilité et la vie privée.

Il y a eu une discussion sur la valeur des données créées et si elles pouvaient être utilisées comme une marchandise pour tirer des accords préférentiels pour les propriétaires de bâtiments. Cela pourrait avoir une sorte de levier en ce qui concerne les fournisseurs d’énergie et les assureurs du bâtiment.

Il existe différentes catégories de parties prenantes dans le bâtiment et il est important que tout mécanisme de consentement les reconnaisse. Ces parties prenantes sont pleinement impliquées dans le bâtiment. Nous avons les propriétaires et les gestionnaires ; les occupants et utilisateurs et la maintenance et les opérationnels.

Les données doivent être disponibles – ou au moins les renseignements dérivés des données afin que les occupants et les utilisateurs du bâtiment puissent comprendre par eux-mêmes comment fonctionne le bâtiment. Cela aiderait à démystifier la technologie et la rendrait moins menaçante, mais aiderait aussi les gens à modifier leurs propres comportements.

La visualisation pourrait jouer un grand rôle dans ce processus, car une bonne visualisation et un bon design permettent la compréhension. En rendant les données disponibles, il est également possible d’exécuter des événements autour des données afin de créer de nouvelles façons de créer l’information et de la comprendre.

Rennes a utilisé avec succès le format Data Remix (sous le format d’un hack event) pour relever un certain nombre de challenge et il est suggéré d’en faire un dans le futur en incluant les équipes de Rennes.

Vous trouverez c-dessous des informations complémentaires en français de notre atelier de travail, sur le lien suivant.

Buildings, internet of things and open data – Can we create consent?

Thursday 25th January 15.00 – 17.00
Federation Street
Manchester M4 4BF

Register here

Sensors and the Internet of Things have the ability to transform the way we manage infrastructure. Open Data Manchester in partnership with Sensorstream Ltd and Things Manchester in collaboration with Rennes Metropole is exploring how data from sensors can be collected, analysed and released as open data.

This workshop should interest building owners and managers, city officials, IoT technologists, open data activists, data governance and privacy specialists and anyone interested in how data derived from sensors can be shared.

Areas of discussion:

  • Overview of technologies being used for monitoring buildings – using as an example a pilot LoRaWAN sensor network being implemented in Manchester and programmes taking place in Rennes.
  • Can the sharing of sensor data help save money and make our cities more efficient and environmentally sustainable?
  • What are the risks of sharing and how can they be mitigated against?
  • How can data be licensed as open data?
  • Can we create a consent framework to allow data to be released?

The project

The Knowable Building Framework is developing an open source internet of things consent framework for monitoring the performance of older commercial buildings in a non-invasive way using discrete low power sensors, and if appropriate publishing the data from these sensors as open data. Unlike modern stock, older buildings often fall behind as far as the utilisation of new technology is concerned. Many landlords undertake a certain amount of retrofitting such as zonal heating or movement detection systems but these tend to be ad hoc and unconnected, with no ability to monitor how effectively these systems are working either singly or together. The internet of things and the analysis of data derived from sensors can give landlords, building management and tenants insight into the performance of buildings, enabling adaptations that can be economically and environmentally beneficial, whilst also creating opportunities for behaviour change within those buildings. The sharing of performance data as open data can also have benefits for mapping energy usage and demand within cities as well as creating a debate about responsible energy consumption.


Work with us

Call for freelance staff (paid)
Open Data Manchester has an ambitious programme for 2018 that includes events, workshops, training and data projects. To help us deliver these projects successfully we would like to call on the Open Data Manchester community to help.

At present we are creating a register of people we can call on to help deliver forthcoming projects and the skills we will be looking for will be as diverse as the programme that we seek to deliver.

So if you are if data is your thing, you can wrangle code or manage events and help keep Open Data Manchester going please send your CV and availability to hello[@]opendatamanchester[.]org[.]uk. We can’t promise anything but we may contact you soon. See below for the rates we pay.

The rates are averaged from a number of sources and worked out as:
Half day rate is day rate / 8 * 4.5 and rounded to the nearest £10
Weekly (contiguous days) daily rate * 4.5 rounded to the nearest £10
Fortnightly (contiguous days) daily rate * 9 rounded to the nearest £10

For longer periods of work we will be offering fixed-term and fixed fee contracts.

Fancy volunteering
Over the next couple of months we will start to develop a volunteer programme to do more more outreach work. If you are interested in joining us drop an email to hello[a]opendatamanchester[.]org[.]uk outlining your interests and availability. Open Data Manchester has a policy of reimbursing reasonable expenses for travel and food when volunteering.

Open Data Manchester is committed to making opportunities available to all regardless of sex, race, marital status, disability, age, part-time or fixed term contract status, sexual orientation or religion. Our Equal Opportunities Policy is a living document and can be found here.

Fare’s Fair – Why we need open fares data for public transport

Being able to understand how much your journey is going to cost is essential for encouraging mobility by public transport in our modern age. Not knowing how much a journey is going to cost before you make it, hinders forward planning and creates a barrier to use. How many people have stepped on to a bus only to find that the journey was more expensive than they first thought? Or that the fare charged yesterday was different than the fare you got charged today?

To this end transport campaigners have been vocal in their efforts to get public transport agencies and operators of public bus services to release fares data, so that people can make intelligent choices about the way that they get around. Transport Hack organised by the fantastic people at ODILeeds is one such example of this happening. Open Data Manchester was itself involved with opening up the bus fares data for all of Greater Manchester in 2010, only for TfGM to discontinue.

Yesterday we learn’t that TfGM had knocked back an FOI request for Manchester Metrolink fares data, citing issues of Commercial Interest.

We think this is wrong on a number of points.

  • Manchester Metrolink is the only tram operator in Greater Manchester – not counting the fantastic tramway at Heaton Park, which we don’t think is a competitor
  • The data is already in the public domain – therefore it wouldn’t take that much effort to aggregate it or get a picture of the fares structure
  • It is in the public interest to get as many people to understand the cost of mobility in Greater Manchester
  • Closed systems hinder the development of seamless ticketing and multi-modal travel by putting opaque commercial interests in front of public service delivery

To this end Open Data Manchester set about compiling the fares data for the Metrolink network. It did’t take that long – about a day – and we used programmatic as well as manual methods. The data is in tabular Excel form as well as a parsed text document. It is provided as is and we can’t be liable for any mistakes or inconsistencies – although we have checked it as much as we can.  Please let us know if you find any errors or create something interesting.

The data can be found here

Minor edits – addition of a link and additional bullet point were made at 14.00, 20.10.17

An edit was made regarding licensing 18.11.17

Open Data Manchester – Next Steps

Thursday 21st September 18.30-20.30
1st Floor
Federation House
Federation Street
M4 2AH

Register here

After seven years Open Data Manchester has become a registered company and soon it will become a CIC. This will allow us to deliver better programmes and also work with others more effectively.

If you would like to hear more and suggest ideas for future activity. Join us

Internet of Things and Open Data Publishing

Tuesday October 3rd 10.30 – 13.30

88 Wood Street
L1 4DQ

Register for free here

If you have an interest in internet of things and how the data produced can contribute to the broader data economy, this is your chance to have a say.

The internet of things offers unparalleled means to create data from sensors, devices and the platforms behind them. This explosion of connectedness is creating huge opportunity for building new products and services, and enhancing existing ones. With these opportunities come some gnarly challenges. These exist around standards in data and protocols, security, discoverability, openness, ethics and governance. None of these are trivial but all of them need to be understood.

This workshop is for people involved in open data, Smart Cities and the internet of things who are starting to come up against and answer some of these challenges.

It is being run by Open Data Manchester and ODI Leeds for the Open Data Institute to look at the future of open data publishing and IoT

The Open Data Institute (ODI) is always working towards improvements in open data – from making it easier to find and use right through to refining and implementing standards. They are very keen to work with people who use open data to see what they can be doing to help and improve open data for everyone.

The workshops are open to everyone who wants to join in, contribute, or work with us. The output from the workshops will be put forward to the ODI and the UK government with recommendations on how open data should be published.

Refreshments and lunch will be provided.

If you can’t make it but would still like to contribute, we have an ‘open document’ available here. We encourage people to add their questions, comments, suggestions, etc.

After the workshop there is the launch of LCR Activate a £5m project led by Liverpool John Moores University with the Foundation for Art and Creative Technology (FACT) and the LCR Local Enterprise Partnership. A three-year European Regional Development Fund (ERDF) initiative using AI, Big Data/High Performance Computing, Merging Data and Cloud technologies for the benefit of SMEs in the Liverpool City Region. Register here.

2017 programme update

It has taken longer than expected but our 2017 programme is finally getting off the ground. The programme, highlighted in the last post, was a provisional one and we hope to track it as well as we can over the coming months.

February kicks off our programme with two events both related to last November’s Echo Chambers and ‘Post-fact’ Politics event. On Saturday 18th February, in partnership with The Democratic Society we will be running a workshop that develops the ideas from November’s event and turns them into action. The event is free and if you couldn’t make it to the first event and would like to attend, we will quickly get you up to speed. The evening of Tuesday 28th February will be a regular Open Data Manchester meeting where initiatives developed from the workshop will be showcased. As always if you want to add to the event in any way, contact us or just turn up.

The evening meeting will be a chance to look at national and international open data events taking place in the coming months.

Provisional programme for 2017

IMG_0066From last night’s planning meeting we now have a provisional programme for 2017 and it is quite an ambitious one. What is great from our perspective is that there is a continuation of a number of themes that we have been looking at over the last year and a resurfacing of perennial ones. Highlights include the ‘making and doing’ workshops that have been developed as part of the Echo Chambers and ‘Post-Fact’ Politics programme and the Visualising Data workshops. There are a number of sector and technically specific events but one to watch out for is alternative ways of looking at the world which will be a day of walks, talks and explorations. As always there is a large dose of how data and technology impact on society and much more.

This is a provisional programme and we are looking for as much input as possible (Dates and sessions are subject to change). Please click on the Google Doc and add comments. We are looking for people who can contribute, sponsors, venues and partners.

Link to Google Doc

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