Data Categories & Collection Methods

What kinds of buildings make up Athens? What are their size and shape? How are they made and what of? Who built them and which are the most efficient? Where can you find different types? And which do you like, and think contribute to the success and well-being of the city?

We are collecting twelve types of data to answer these and many other questions about Athens. Click on any box to find out more about our different data categories.

Data Categories

Owing to the complexity of the stock as a system, we have tried to group our datasets in as simple a way as possible. The 12-category-grid above also doubles as our logo, and as Colouring Athens' control panel, allowing you to easily navigate across our maps.

The grid contains over 50 subcategories of data. These have been selected through consultation with representatives of various organisations combined with more than 500 responses to an open questionnaire, along with a detailed analysis of data needs of researchers working in sustainability science and urban science, based on the assessment of academic papers. The list is not exhaustive and new subcategories can be added at any point.

The grid is divided into two sections. The first includes data onLocation, Use, Type, Age, Size, Construction and Streetscape which contain information on the form, use and context of the building. These are relevant to multiple applications ranging from calculating and predicting volume of energy emissions, to assessing housing quality and supply, to predicting structural failure or informing the development of local plans. Using these data, open 3D rule-based city models can also begin to be built. The remaining five categories on the grid - Team, Planning, Sustainability, Dynamics and Community - all have multiple functions, and are designed not only to capture and contain data, but also to support analysis and help improve quality and sustainability in stocks through greater engagement and knowledge exchange from all those involved in.

Location data is the first type of data in the grid as all other data types rely on coordinates, addresses and building footprints for every building, to allow data be collected, mapped and spatially analysed. The greater the number of location categories filled on our map the darker the building colour is, allowing you to quickly see where more data are required.

Building footprints are a very important type of data essential for Colouring Cities platforms to work, as they act as mini filing cabinets, storing, locating and visualising contributed data. We are using a hybrid polygon/building footprint basemap that was generated through a combination of OpenStreetMap (OSM) polygons and Hellenic Statistical Authority polygons.

OSM footprints are the most comprehensive, precise, up-to-date footprints available to us. However, they only cover part of the city of Athens. Specifically, after visual inspection it was estimated that OSM currently covers only a part of the city, and specifically municipalities located at the center of the city and the eastern, northern and southern suburbs. At the same time, the Hellenic Statistical Authority Census 2001 footprints are the only other available source for building footprints. However, these footprints reflect the condition of buildings as it was 20 years ago. Since then, significant modifications have been made to the buildings (demolitions, constructions, additions). As a result, the map does not correspond accurately to the current situation.

The above possibilities and limitations led us to the generation of a hybrid model, based on both building footprints from the 2001 Census and OSM, according to the following methodology. After a visual inspection for each of the 43 Municipalities covered by the project, it was found that the OSM background reflects better the current condition of the buildings for the following 23 central and semi-central Municipalities, including the Municipality of Athens: Agia Paraskevi, Agios Dimitrios, Athens, Alimos, Maroussi, Vrilissia, Vyronas, Galatsi, Glyfada, Dafni – Ymittos, Elliniko – Argyroupoli, Zografou, Ilioupoli, Kaisariani, Kallithea, Moschato – Tavros, Nea Ionia, Nea Smyrni, Palaio Faliro,Papagou – Cholargos, Philadelphia – Chalcedon, Filothei – Psychiko and Chalandri. The Census 2001 background was used for the remaining following 20 Municipalities where the OSM cartographic background is still insufficient: Ilio, Agia Varvara, Agioi Anargyroi – Kamatero, Aigaleo, Vari - Voula – Vouliagmeni, Heraklion, Keratsini – Drapetsona, Kifissia, Korydallos, Lykovrysi – Pefki, Metamorphosi, Nikaia - Agios Ioannis Rentis, Piraeus, Penteli, Perama, Peristeri, Petroupoli, Chaidari, Acharnes and Fili.

The final building footprint basemap consists of 292,579 Hellenic Statistical Authority Census 2001 buildings and 234,853 OSM buildings. In total we have a background of 527,432 buildings. For those buildings derived from OSM users will be able to download data in the form of a shapefile, under the ODBl license, while for buildings derived from the Hellenic Statistical Authority users will be able to download only images. In case that a new building footprint basemap is generated during Census 2021, the information will be transferable to the new polygons.

Furthermore, rapid progress is improving global scale of footprint coverage is being made through Microsoft/Bing’s collaboration with OSM, and its application of artificial intelligence to satellite imagery, to generate open footprints. This has so far produced open footprint datasets for the US, Canada, Uganda and Australia, which are being integrated by OSM, alongside open street-network and international national mapping agency data (where available) as well as other types of open, crowdsourced, geoinformation.

The OSM/Microsoft partnership is extremely important in that it means that footprints are likely to become increasingly available at global scale (with the quality of these able to be improved through parallel release by national mapping agencies), opening up offering opportunities for scientific analysis of diverse types of building attribute data at global scale.

In the meantime we will try to collect and release as much information on Location as we can. This includes building number and address, lat/long coordinates and OSM ID (geometry/polygon) number.

The most significant current source of open location data is OpenStreetMap (OSM), which has been at the forefront of driving release of open data on cities since 2004. Its collaborative maintenance model, along with Wikipedia's has also strongly influenced Colouring Cities' approach. Originally set up to crowdsource data on streets, OSM also now focuses on providing open data on buildings. All data generated by Colouring Cities platforms are therefore designed to link seamlessly to OSM, with OSM IDs, and attribute data integrated wherever possible.

In order to analyse cities in a more scientific way, their basic composition first needs to be understood. One of the most commonly used types of data in planning, urban analysis and energy assessment is land use data. This provides information of the kind of buildings that exist and how many examples of each different kind are there and how much floor space is available for different types of activity. It also helps answer questions such as where do specific types of land use cluster, is this same in all cities, and how does this affect the way the city operates?

Despite widespread demand for land use data, at property and building level, for cities as a whole, comprehensive open land use data are still not available in Greece. Fortunately information on building use is quite easy to collect, and can usually be worked out simply by viewing the front of the building from the street or using a streetview image. The vast majority of properties are residential. Recognising houses is quite straightforward. Blocks of flats can be differentiated from offices by the presence of curtains. Identifying activities within non-residential buildings is slightly harder but activities can often be determined by the shape and size of buildings, their window layout as well as signage to the front, or at entrances.

If you would like to add data just select a building and decide which land use 'Group' the activity belongs to. These are: Mixed use, Residential, Retail, Industry & Workshops, Wholesale & Warehouses, Offices & Services, Recreation & Leisure, Education, Health, Transport, Utilities & Infrastructure, Under construction, Unused - Vacant, Other.

The kind of activities and number of people a building was originally designed to hold, as well as the period in which it was built, will affect a building's form, including its size, shape, decorative features and layout. Such characteristics are also used to group buildings into specific types or typologies, where copies or versions also exist.

Understanding the location of different building typologies is important in areas such as the retrofit of buildings to improve energy efficiency, allowing retrofit methods and budgets to be more accurately targeted and understanding how buildings and packed together. Understanding survival rates for different typologies, and identifying and retaining adaptable ones, is also necessary to reduce unnecessary waste and energy in construction, and to learn from the past to build more long-lasting buildings for the future.

When combined with footprint, size, height and age data, typology information also helps build a picture of a building's 3D geometric form. This is increasingly important in energy and urban heat analysis, and in the development of 3D rule-based digital city models able to simulate future planning and energy scenarios.

Building age is also commonly used, and recorded, by architectural historians, building conservationists, heritage specialists and urban morphologists.

Information on building age, generated from date of construction, is extremely important for geolocating building types. More recently building age data have also become increasingly used in energy and urban sustainability research, particularly in emissions analysis and urban heat assessments. Here construction date is often combined with other attribute data to help describe the building's form, particularly its geometry and volume. Age data, combined with historical construction and demolition data (captured in our 'Dynamics ' category) are also needed to produce actual building lifespan data. This is required to forecast when and where specific areas of the stock may have to be replaced, and to plan lifespan extension. (Age data will also in future be used, within our 'Sustainability' category, to provide an indication of potential building lifespans as well.)

Building age data, are held by the Hellenic Statistical Authority for all buildings but are not openly released, even for academic research. Colouring Cities develops interdisciplinary approaches to assist the capture of the most accurate building age data possible. Our 'Age' and 'Dynamics' categories have been designed, in consultation with historians and heritage experts, to encourage input from architectural historians, civic societies, building conservationists and others with expert knowledge of building history. We are also experimenting with automated approaches to age data generation which allow faster coverage of the city. Here the age of buildings is inferred by the age of the road. Local historians are invited to verify the data or alter it where applicable.

Data on the size and geometry of a city's buildings have many applications ranging from use in 3D digital city models, to understanding implications to changes to the height of a city's buildings, to analysing and predicting energy use, and greenhouse gas emissions, and the build-up of urban heat.

Data on the dimensions of buildings are also relevant to many other areas of urban research, from analysing housing capacity and identifying areas suitable for densification, to observing (within urban science and urban morphology) long-term patterns of change within urban form.

In the 'Size' category, data on building height and number of storeys are collected.

What are Athens' buildings made of and how are they built? What type of construction systems and methods are used? What is the main material used for the building's core? Does it have solid brick walls, or perhaps a wooden, steel or concrete frame? How much is glazed? Has it recently been refurbished and retrofitted to help reduce carbon emissions and reduce energy costs?

This type of information is useful to built environment professionals involved in the repair, management, conservation, retrofit, design and construction of Athens’ buildings. However, it is not currently available for the city. The idea is to use this category to help create a live, open repository for data about construction in Athens.

Understanding what kind of material is stocked where in the city, and the location of different types of structural systems, is also relevant to many other types of research, from calculating potential energy and construction waste flows, to targeting funds for retrofitting programmes, to geolocating vulnerable construction systems. Spatial construction data can also help us explore questions such as: Are there health issues associated with specific types of building materials or building systems? Which types of systems can be most easily repaired? Which have the shortest lifespan and where are these located? Which are the most energy efficient? How can we use our collective knowledge of the operation of systems and materials to inform sustainable design and construction in Athens for the future?

In our streetscape category, we are collecting information on all greenery, street width, accessibility of pavements, bicycle lanes and levels of noise. Greenery specifically has a number of roles in Athens: It adds beauty, but it also acts as a climate moderator, improving thermal comfort within the city by providing shade, and reducing the build-up of heat and urban heat islands. It can also improve health, by reducing pollution and improving air quality through the production of oxygen, absorption of carbon dioxide and heavy metals, and by trapping dust particles.

Team captures data on designers and builders. For most buildings this requires expert input from professional and amateur historians. Awards and quality marks are also included here, to celebrate construction firms' commitment to sustainability, and industry skills and expertise. The section is also designed to drive up new build quality by enabling the longevity, energy Performance and workability/attractiveness of buildings (as viewed by users/citizens) to be more easily tracked over time, and used to improve building design in future.

Planning captures data on allowed FAR, plot coverage and maximum allowed building height, and, most importantly, on the preservation status of buildings. This helps communities understand in advance if the buildings they consider to be of local importance are being threatened, and allows them to use the 'Community category' to highlight buildings they have found to contribute to the area/city.

Sustainability is a broad category designed not only to capture data on the maintenance level of the building, identify buildings in risk of collapse and collect data on energy Performance, but also to stimulate discussion on inclusion of new types of data designed to maximise building longevity and minimise emissions. Data categories of future interest include for example the repairability, adaptability and potential lifespan of buildings/or building components.

Dynamics captures data on the evolution of the city, on incremental development within plots over long periods of time, and on building lifespans. These are needed to track rates of change, assess typology survival rate, predict lifespans and anticipate vulnerability to demolition and system failure. They are also required in urban metabolism studies to assess and predict the volume of energy and waste flows occurring in the city, generated from changes to the stock, and differences in the amount of energy used in new material extraction/new construction/old building disposal compared with building updating/extension/reuse.

Our 'Like me?' category simply asks whether you like the building. You might think it works well on the inside, or on the outside, contributes to the local community or adds to the quality, diversity and success of the city as a whole. You can 'Like' as many buildings as you wish but you only have one vote per building. The more 'Likes' there are, the deeper the colour will get.

Colouring Athens is designed, in the first instance, as a constructive, welcoming environment for knowledge exchange about the building stock. It is included to encourage engagement. For these reasons we do not collect 'dislikes'.

It is however designed to stimulate discussion. To create a more sustainable, efficient, successful and healthy city we need to build better buildings, demolish less and reuse and upgrade more. Conversation between those using and those creating and managing buildings is vital. Buildings that work well for many members of the local community do so for a reason.

Categories are not set in stone. Where there is general consensus that a category or subcategory should be adjusted or added, relevant changes can be made. You can add your suggestions to our discussion threads here.

Subcategories

We are gradually releasing subcategories for testing. If you are able to help us by adding or checking the accuracy of data, just go to Edit Maps, click on a building, choose any category of interest and fill in any information you can. Every entry and/or verification helps. Some categories are easier to fill than others. Our 'Community' category is perhaps the best place to start. Here you can simply colour any building you think contributes to the city.

Examples of subcategories within our 12 main categories are shown below. We're trying to keep collection as efficient and simple as possible.