For those who were unable to attend the workshops we are able to share the structure and a summary content of the presnetations. We followed a two-part structure for the workshops. Firstly, a review / validation of stakeholder requirements and secondly the testing of prototype energy planning tools. These were presented as initial ‘beta’ versions of developing SEMANCO tool(s) and used as the basis for structured discussion around the parameters, assumptions and requirements for the tools. The recorded outcome formed the basis for a comparative analysis undertaken between the design parameters and the stakeholder requirements. The text below sets out the alternative but complementary prototype tools and methods illustrated in the workshops, together with the parameters (format, accuracy, cost, platform and transferability) that provided the basis for discussion and analysis.
The first hypothetical Use Case explored was a registered social housing provider (RP) as a actors with ‘pepper potted’ ownership …
Format: Set of individual property typologies Trimble Sketchup. Supported by web access SAP tools.
Accuracy (level of detail / data input / metadata): Input data based on Google Maps and site survey. Aggregated approach to area based on frequency of typologies. Input error.
Cost (IT systems & data acquisition, database management / monitoring): Use of freeware (professional versions available offering additional functionality). Free publicly accessible data sets. Cost of staff time for modelling, data collection and SAP. Potential training for use of software.
Speed: Subject to variety in housing / building stock.
Platform (system requirements): PC / MAC. Web.
Transferability (comparison / use of complementary data sets): Requires aggregation of property typologies at an area scale. Bespoke spreadsheet for area-based aggregation. Visualisation on Sketchup allowing for detailed property modelling with add-ons / CAD / Revit or similar.
Limitations: Local knowledge to inform working assumptions Input error.
The second hypothetical Use Case explored was a Local authority with extensive building stock and an interest / responsibility for private housing interventions …
Format: Excel. Bespoke and self-contained. Link to GIS (ESRI ArcGIS) if software licence allows. Cost benefit model for energy efficiency interventions.
Accuracy (level of detail / data input / metadata): OS base data for gross ground floor area (m2) for all domestic buildings. Landmap for accurate building age (sap input) buildings heights.
Cost (IT systems & data acquisition, database management / monitoring): Requirement for technical support for data input and / or analysis. Sourcing the base maps / topography (Landmap / OS may have restrictions on wider distribution).
Speed: Quick (approximately 400 properties / LSOA per day). Potential to be fully automated. Staff support / time if validation and checks are required.
Platform (system requirements): PC / MAC. ERSI ArcGIS (possible use of shareware GIS).
Transferability (comparison / use of complementary data sets): Geo-referencing allows for database mapping and manipulation. Output in dBase / Excel spreadsheet format to support output tables / graphs. Exported .shp file into Cad directly / Sketchup indirectly.
Limitations: Limitations over non-domestic properties, heat network mapping and identifying high levels of heat / energy demands.
The third hypothetical Use Case explored was a National charity campaigning on ‘fuel poverty’, targeting ‘municipality’ partnership and initiating projects using the prototype SEMANCO tool…
Format: 3D Map, Java (but limited to recent PCs and Google Crome)
Accuracy (level of detail / data input / metadata): Landmap or similar OS base data. Building height data / roof area from supplemental Lidar data (to calculated volume and exposed surfaces). Estimated window areas (site survey / ‘street view’. Orientation of facades and roof (metadata notes required to highlight the source material)
Cost (IT systems & data acquisition, database management / monitoring): Generally ‘open source’ data with query tool. Potential to supplemented with commissioned data. Significant additional costs for 3D Lidar data sets.
Speed: Quick. Automated, desk-top study.
Platform (system requirements): Agency9 Web Platform.
Transferability (comparison / use of complementary data sets): Potential reuse of building models for options and detailed design?
Limitations: Currently restricted to residential uses. Complications in estimating multiple occupancy properties.
Prior to the presentations commencing, the audience were given with some context around the development of the SEMANTIC framework. The undertone set against the tool was that this was something in development and very much a ‘prototype’ at this stage. This immediately let the audience know what they were about to see was ‘in development’ and there would be a process of re engagement in future. The intelligent nature of the questions returned with regards to the operational functionality of the tool highlighted a good level of understanding particularly with regards to the theory of SEMANTIC modelling and the ‘potential’ outputs of the tool. The SEMANCO tool was presented as a prototype tool with some functionality, a working demonstration of the current utility and the assessment of what additional functionality is being developed and expected. The background to the SEMANCO project was introduced with a basic non-technical outline of the theory behind it, and the idea of semantic data modelling. The mixed stakeholder audience(s) were prompted to thing about their own organisation and potential applications that included the use of their own linked data being added to the development of the model.