Nov 112011

This blog post provides details about the web tool developed by the STEEV project.

Problem Space:

  • There is a requirement by the UK government to reduce the country’s carbon emission by 80% by 2050.
  • Buildings account for 45% of energy use in the UK, the equivalent of all transport and manufacturing combined (ESRC, 2009).
  • Most building stock which will exist in 2050 has already been built.
  • To achieve this target massive alterations of the current buildings are required. Part of the solution would be a tool that could enable planners, local authorities and government to best estimate the impact of policy changes and to target the interventions appropriately.

Cue  – the STEEV demonstrator, a stakeholder engagement tool developed to visualise spatio-temporal patterns of modeled energy use and efficiency outcomes for the period of 1990-2050 –

For a portable overview of the project download the STEEV postcard

Primary Users:

Students, researchers, lecturers from a wide variety of disciplines/sub-disciplines, including geography, architecture, ecology, environmental science, economics, energy engineering and management.

The tool is also aimed at a range of stakeholders such as policy makers, urban developers, climate change specialists, carbon energy analysts, town planners.

Key Product Information – motivations and mechanisms

The STEEV demonstrator was developed to complement a larger project, Retrofit 2050 – Re-Engineering the City 2020-2050: Urban Foresight and Transition Management (EPSRC EP/I002162/1) which aims, through a range of stakeholders, to get a clearer understanding as to how urban transitions can be undertaken to achieve UK and international targets to reduce carbon emissions. The Retrofit 2050 project focuses on two large urban case study areas (Manchester and Neath/Port Talbot, South Wales – the latter being the focus of the STEEV demonstrator due to data availability within the project time-frame), through modelling scenarios of carbon emissions and energy use, both now and in the future.

The demonstrator itself is a client web application that enables researchers and stakeholders to look at how the spatial and temporal distribution of energy efficiency measures may impact upon likely regional outcomes for a given future state. This takes the form of a spatio-temporal exploration and visualisation tool for building-level energy efficiency modelling outputs such as the energy rating of the building, the likely energy demand of the building and the related CO2 emissions. A finite series of modelled scenario permutations have been ‘pre-built’ thus providing a limited number of parameters to be interactively altered in order to explore the spatio-temporal consequences of various policy measures.

View the STEEV Demonstrator Website: :

Note: A further workpackage to establish a small area data viewer as part of the presentation layer will also be implemented shortly. This replaces the Memento geo-Timegate component of Workpackage 3.

The user interface has two main areas of activity, namely:

  • three ‘pre-built’ policy scenarios which depict government investment in energy efficiency measures (from best to worst case scenario) and a user generated scenario created by selecting a combination of the energy efficiency variables which go to make up the ‘pre-built’ scenarios.
  • a map viewer that enables model output values (SAP ratings, Energy use, CO2 emission) for each scenario to be viewed for each decade (1990 to 2050) at Output Area level of spatial granularity.

Further information about the policy-scenarios and variable descriptions are available from the help page

Fig1. – The STEEV Demonstrator

STEEV tool interface

Fig. 2. – Policy Scenario 2 – Low Carbon Reference

CO2 emissions, 2010 - Low carbon reference

Fig. 2 – Policy scenario 2 – Low Carbon Reference (i.e. the government invests in partial decarbonisation of the grid through reduced dependence on fossil fuels. Large investment in energy efficiency and small scale renewable, some change in occupant behaviour) has been selected for 2010. CO2 emissions have been chosen as model output value.

Fig. 3 – User-generated Scenario

Energy use for Custom Scenario 2020

Fig. 3 – A zoomed in view of a user-generated scenario for Energy Use for 2020. Note: User generated scenarios are forecast only.

Fig. 4 – Policy scenario 3 – Google Earth Time Slider

Energy efficiency data can be downloaded as Keyhole Markup Language (KML) files for use with the Google Earth Time Slider (for ‘pre-built’ scenarios only – see below) or as raw ASCII files complete with spatial reference for analysis in a Geographic Information System.

Energy Use policy scenario

Fig. 4 – KML files viewed on Google Earth for Energy Use output model values for policy scenario 3 – (i.e. the government invests in decarbonisation of the grid through renewable, nuclear, and huge investment in energy efficiency and small scale renewables. Large scale change in occupants behaviour)

Fig. 5 – Model output for individual buildings

Model output for individual buildings

Fig. 5 – Forecasted model output values (SAP rating, Energy use, CO2 emissions, CO2 emissions based on 1990 levels) for an individual building in 2030.

Note: Click on Blue dot and select Buildings map layer.

Members of the STEEV project presented at the following events:

  • STEEV / GECO Green Energy Tech Workshop at the Edinburgh Centre on Climate Change (13 October 2011) – for further details see blog post
  • Post-event comments include:

    STEEV provides a new simple tool to quickly visualise a series of scenarios concerning energy consumption and carbon emissions within the complexities of the urban fabric. By facilitating the visual and historical understanding of these issues in a wider area, and for its forecasting capability considering a series of energy efficiency variables, it has a great potential to assist the planning and design processes.“ – Cristina Gonzalez-Longo (School of Architecture, University of Edinburgh)

    The STEEV system’s geospatial information on energy consumption and CO2 emissions can help planners and project developers target projects and initiatives related to energy efficiency and reduction of carbon emissions. Furthermore, the forecasting tools built into STEEV enables energy and carbon emissions to be estimated through to 2050 on the basis of alternative scenarios for energy efficiency initiatives, renewable energy, etc. This facility should help to determine where the opportunities for future emissions reductions will be, and the contributions made by existing policies and plans to future (e.g. 2020 and 2050) emissions reduction targets.” – Jim Hart (Business Manager, Edinburgh Centre for Carbon Innovation)

  • The Low Carbon Research Institute 3rd Annual Conference held at the National Museum of Wales on 15-16 November 2011
  • Post-Industrial Transformations – sharing knowledge and identifying opportunities, a two-day architectural symposium held at the Welsh School of Architecture on 22-23 November 2011

The STEEV demonstrator is a JavaScript client application which uses Open Layers as the mechanism for displaying the map data over the web. It also deploys a Web Map Service with temporal querying capabilities (WMS-T) to deliver Ordnance Survey open mapping products via the Digimap OpenStream API. The modelled energy efficiency variables are held in PostGIS (an open source spatial database extension to PostgreSQL)

Data – Open Database License (ODC-ODbL) — “Attribution Share-Alike for data/databases”
Code – GNU General Public License version 3.0
Blog & other website content – Creative Commons Attribution 3.0 Unported License

Table of Contents of Blog Posts:

Project Logos:

combined logos of EDINA, JISC, WSA

Project Team:

STEEV Project Team

EDINA team members (L to R: Lasma Sietinsone, George Hamilton, Stuart Macdonald, Nicola Osborne. Fiona Hemsley-Flint is currently on maternity leave.)

Simon Lannon: Project partner from Welsh School of Architecture, Cardiff University:

Sep 292011

The first port of call for explanation or definition of STEEV tool functionality or terminology is this Help page.

We thought it useful to make available contextual information describing both policy scenario, variable.

Thus: here are the Policy Scenarios Descriptions, and here are the Variable Descriptions.

Note: As part of the usability and user testing we shall endeavour to make the variable and policy scenarios description information more explcit for the purposes of informing end use of the tool.

Other Help and Guidance notes:

STEEV Camtasia broadcast – explains and walks users through the functionality and features of the energy efficiency visualisation tool.

Contextual Overview of the STEEV tool

Overview of the Energy and Environment Prediction (EEP) model developed by the Welsh School of Architecture

The STEEV tool uses ‘hover over‘ boxes to provide an explanation about functionality. Use the mouse to hover over the buttons, slider gauge, markings and labels to get further information. Green information buttons provide further details about each scenario.

The Share Link feature on the interface uses a STEEV RESTful API to define a URI representing the value of the model, each variable, the year, the map extents and the map zoom level. This facilitates the sharing of a URL by returning the client to the state when saved.

Printing – Version 1.0 of the STEEV demonstrator does not include a print nor a save map image facility. To print (and edit) a map image created by the demonstrator use the Print Screen button on your keyboard and paste the image in to an image editing package such as PaintShop Pro. Save the map image in the image file format required (JPEG, GIF, WMF, TIF, PNG).

Model Output Value Feature Return functionality: further information about displaying model output values at the individual building level.

Data Download – further information about the raw ASCII Comma Separated Value (CSV) and Keyhole Markup Language (KML) format data file download.

Guidance notes on viewing the Policy Scenario KML files in Google Earth.

Alternatively view the ‘Using the Time Slider bar in Google Earth’ You Tube clip:

YouTube Preview Image
 September 29, 2011  Posted by at 4:09 pm General Tagged with: , , , ,  No Responses »
Sep 292011

As we move into the final phases of STEEV thoughts now turn to user testing and usability. OK, so we’ve built a visualisation tool to view time-series energy efficiency variables for a specific geographic area. But just how intuitive is the interface? How easy it is to use, for the practitioner, or for the novice user? What functionality is missing, and what is superfluous?

First step was to meet with the EDINA training officer (who has experience in conducting usability and user testing for EDINA projects and services). It was immediately apparent that work was required in terms of workflow and instruction. A detailed list of requirements has been assembled for implementation.

For the next step in this process we have approached a ‘Usability Expert’ with a view to having an overall look at the tool in terms of features and functionality in order to articulate and finesse possible ambiguities. We hope to have at the end of this process a usability guide detailing both process and outcome and make this available through the STEEV blog.

Our aim is to have conducted this exercise in time for the STEEV/GECO Green Energy Tech Workshop on on 13 October. This will allow practitioners the opportunity to use the tool in earnest whilst providing further feedback from an experts perspective.

Expect a future blog post detailing the results of the extended usability exercise.

Regarding part 2 of the title. OK, so there’s wasn’t a fit between STEEV and Memento. What does fit however, is the deployment of the Google Earth Time Slider to view the policy-based scenarios (as provided by our project partner) for each of the four modelled output over time (namely: SAP Rating, Energy, COs emissions, CO2 emissions based on 1990 levels). Our GI Analyst (Lasma Sietinsone – replacement for Fiona who’s currently on maternity leave) has created a dozen KML files which can be viewed in Google Earth using the Time Slider utility. The KML files can be downloaded from

Note: Guidance notes on viewing the KML files in Google Earth are available.

Alternatively view the ‘Using the Time Slider bar in Google Earth’ You Tube clip:

YouTube Preview Image
 September 29, 2011  Posted by at 3:27 pm General Tagged with: , , , , , , ,  No Responses »
Sep 282011

The programme for the GECO / STEEV Green Energy Tech Workshop to be held at the Edinburgh Centre for Climate Change on 13 October is now available (see URL:

Our aim was to have a full yet varied set of presentations from the academic, public and private sector around the central theme of ‘energy efficiency and the building’. Feel free to forward the Eventbrite link to colleagues. Places are limited to please be sure to sign up soon!

Please get in contact for further information:

 September 28, 2011  Posted by at 1:58 pm General Tagged with: , , , ,  No Responses »
Aug 312011

After much discussion agreement has broken out between project partners regarding the STEEV project sub-contract (or Collaboration Agreement) between the University of Edinburgh and Cardiff University. Legalese such as ‘foreground’, ‘ownership and exploitation’, ‘liabilities’ have been unpicked, deliberated over and agreed upon. After initial confusion costs (directly incurred staff costs in addition to directly allocated and indirect costs) payable to the Welsh School of Architecture have also been settled and signatures have been signed!

Plans are afoot to organise a joint GECO ( / STEEV workshop for autumn 2011. The ‘Green Energy Tech’ event, to be held at the University of Edinburgh, aims to invite public sector, industry and academic practitioners in the area of green energy, carbon budgeting, energy efficiency and reduction, urban energy systems, renewable energy, decarbonisation, energy consumption, fuel poverty etc to discuss, share ideas and showcase tools that can appeal to a range of stakeholders. More information to follow.

The STEEV project will also be presenting at the Rantrad Future Cities 2011- International Symposium in London on 15 & 16 December 2011.

 August 31, 2011  Posted by at 6:11 pm General Tagged with: , , , , , ,  No Responses »
Aug 242011

Simon Lannon (Welsh School of Architecture) has provided the following by way of a contextual overview of the visualisation tool in development:

The simulation of the urban environment is a complex process; the EEP methodology simplifies this by using simple standard energy prediction tools, and ways of grouping houses together. The grouping of houses usually follows the type of house e.g. terraced, semi detached or detached, this is reasonable for simple problems, but when trying to predict the energy use of a detached house it could be two ends of a very large scale, from a labourers cottage to a mansion. The best way to group houses in this project is by their size and when they were built. To do this a number of common house types are surveyed, the results of these surveys are clustered together to give groups of houses with similar energy predictions.

The groups of houses are then modelled using the SAP technique to give a baseline or start point. From this baseline these groups of houses are modified to improve the energy efficiency, bolt on solar panels and take into account potential changes in the occupant’s behaviour. In this example it has been assumed the occupants might accept low inside temperatures by wearing more clothes.

The prediction of energy use for each of these modifications is undertaken then applied to each of the houses in the sample area, in this case most of the houses in Neath Port Talbot, South Wales (around 55,000).

Occupant behaviour also has an impact on whether a particular type of modification will take place. This is represented in this project by trigger points for ten year steps from 2020 to 2050, the trigger points represent this occupant behaviour year by year, and are associated with the likelihood of an occupant undertaking energy efficiency measures. The impact of energy efficiency measures is modelled by a series of trigger points that end with all the houses in the area having at least simple energy efficiency and 50% having a more expensive energy efficiency measures such as external insulation cladding.

The process of all modelling has been more complex than initially thought, perhaps with hindsight the sample should have been smaller, but the task has been completed. The task was to model 55,000 houses over 50 years in ten year steps, for 625 different scenarios, as sum total of around 172 million calculations and 9 GB of data.

 August 24, 2011  Posted by at 5:36 pm General Tagged with: , , , ,  2 Responses »
Aug 092011

Annual leave and conflicting activities have meant that the STEEV blog has been on a forced diet. I do have a couple of morcels of news which may assuage the hunger of this social media channel however…

In the middle of July we had a Skype call with Herbert Van de Sompel (Los Alamos National Laboratory) about how the Memento framework could be implemented in order to facilitate the spatio-temporal visualisation of energy variables.

As mentioned in the blog post ‘evolution of an interface’ a decision was made to use Output Areas as the spatial unit of analysis. It was our collective opinion that visualising the energy efficiency variables at house-level was too fine grained to offer any meaningful representation (even although the data supplied by the Welsh School of Architecture was provided at this level). This has implications in terms of the use of MasterMap as the large scale context mapping product* which was initially earmarked as the potential web-content upon which Memento could act. As it stands Herbert didn’t see any purposeful use case involving STEEV and Memento which would add to the functionality of the visualisation tool. Memento can be implemented (by linking to unique or presistent URIs generated by the tool) and we intend to portray this in the interface. This will not however showcase Memento’s temporal sweep through web-content (as highlighted on BBC/CNN content) as intended by its originators.

I parapharase Herbert (from correspondence) when he says:

Memento deals with web-time i.e. the state of a web resource at a given point in time. It allows one to use the HTTP URI of a web resource (say an HTML page, an image, even a database) and request a representation of the state that resource was in at the point in time that is of interest. This means, Memento looks at the Web as a “system” and can refer to and and look into the state of that system (and its constituent resources) at some point in the past.

This is a very different notion to looking at the state of some other “system”, e.g. a simulation of the real world, and checking in what state the real world was or will be at some point in “real world time” according to that simulation. In the case of STEEV, we are referring to a temporal state within the simulation. Not a temporal state of the Web.
Thus the temporal semantics involved in Memento and in STEEV are fundamentally different and that, as a result, applying Memento concepts to the latter is inappropriate.

A useful output from our conversation with Herbert however was the proposed creation of a STEEV RESTful API which would define a URI and its arguments for the determining and retrieval of a particular state. The URI arguments would represent the value of the model, each variable, the year, the map extends and the map zoom level. A mechanism would be added to the interface for saving its current state as a URI – perhaps to the clipboard, a popup or envoking an email client. Fetching the URL would return the client to the state when saved.

example URI:,203198.976,270931.968,225776.64&zoom=2

A meeting has been set up with Herbert here at EDINA for 19 September where we will discuss our implementation of the framework and other possible enhancements that have synergies with Memento or perhaps even Annotate (another utility developed at the Los Alamos National Laboratory).

* The upside of using Open Layers and Open Stream as context and navigational mapping utilities is that there should be no licencing restrictions on the use of the STEEV tool.

 August 9, 2011  Posted by at 2:15 pm General Tagged with: , , , ,  No Responses »
Apr 072011

JISC Infrastructure Call 15/10: Geospatial Strand
Project Name: Spatio-Temporal Energy Efficiency Visualisations (STEEV)

Directly Incurred Staff Costs

Project Manager, 25% FTE – £8,410
Software engineer, 50% FTE – £16,331
GI Analyst, 25 % FTE – £6,838
Social Media Officer, 10% FTE – £2,683
Web designer, UofE, 5% FTE – £1,602
PI/Manager, Cardiff University, 8% FTE – £4,332

Total Directly Incurred Staff (A) = £40,196

Directly Incurred Non-Staff

Travel and expenses* – £12,000
Hardware & software – £500

Total Directly Incurred Non-Staff (B) = £12,500

Total Directly Incurred Costs (C) = £52,696

Amount Requested from JISC – £74,572

Institutional Contributions – £21,665

Total Project Cost = £96,236

No. of FTEs: 1.23 over 6 individuals

* Includes allocation to Van de Sompel and colleague for project engagement, meetings and conference attendance. Note that their time and input to project is otherwise at zero-cost to JISC.

 April 7, 2011  Posted by at 5:29 pm Project Plan Tagged with: , , , ,  No Responses »