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Click here for video As citizens and professionals we accept that the planning process is there to uphold standards of safety, aesthetic, technical and social requirements. However, the planning process has suffered from many years of tinkering and making good. We now have a planning process that is dependent on outdated approaches and incompatible with the rest of the development industry. It is slow, which presents problems in the UK where we need to build, a lot, quickly. Planning risks preventing this building from happening at pace and of a higher quality. This situation presents, of course, a golden opportunity for a fully digitised end-to-end process which could: reduce the planning bottleneck automate those parts of the process that can be Increase transparency of the process open up new means of engaging stakeholders with the planning process, by for example visualising proposed developments and so increasing understanding allow us to see projects in context, with other proposed developments, rather than in isolation allow access to, and sharing of, crucial data (like structural and fire safety information) facilitate the use of modern methods of construction most importantly, give a more accurate understanding of build costs and timescales In order to bring this about, we have to standardise and digitise (as far as it is possible and desirable) the rules under which designs are created, assessed, and ultimately built. At the same time we have to find ways to generate and use interoperable data. This problem is what the group from Bryden Wood, 3D Repo, London Borough of Southwark and CDBB have been working on. We have developed a model which is open and based on the established BIM Collaboration Framework (BCF). It presents the data associated with planning so that it can be queried and interrogated. You can see a summary in the video above and read more about it here; Planning Golden Thread statement attached below 3DRepo technical write up Bryden Wood technical write up Bryden Wood Schema We know that many of the barriers associated with a change like this will be cultural rather than technical so we are seeking partners in the planning and development system who would like to test the model and collaborators who would like to fund the next stage of development. Please get in touch! You can also hear more about this on the Gemini Call on Tuesday, 18 May at 10:30 with Miranda Sharp and Jack Ricketts of Southwark Council. Link to DT Hub Calendar

I came across an EU funded project "xr4all" which provides a development environment(among other things) for XR projects. The details are here: https://dev.xr4all.eu Will it be possible for the NDT programme to provide similar platform for DT community in the UK? It will help in fostering rapid collaboration and development of the DT ecosystem. Thanks and kind regards, Ajeeth

I am considering starting a network for topics related to Lifecycle V&V (Validation and Verification) centred on Evaluation and Testing, and this message is to poll the level of potential interest. I imagine the network would offer the following: · A place for Test Engineers from different market sectors to share experiences and gain knowledge · Support for those areas where DT activity is low but growing, the Defence Sector is an example, to benefit from the experiences of other sectors Test Engineers have a mix of technical and customer skills that are central to successful project implementation. The DT concept provides a lifecycle project-thread that provides Test Engineers with an unprecedented opportunity to exercise their skills. Maybe finding a way to maximise this opportunity might also attract more people to the career, and be a way to improve recruitment into the world of Engineering? If we launch this Network, would you consider joining it? Dave Murray

The idea of a Digital Twin [DT] needs to advance in a standardized and formal manner. As @DRossiter87 pointed out, this is necessary to "support the consistent adoption of, and interoperability between, digital twins for the built environment within the UK" To aid in this endeavour, it is useful to delineate the difference between the following terms: “DT General Use Case” [GUC]: a very short sentence, possibly consisting of two or three words – ideally a verb followed by a noun – ultimately concerned with the brief and blunt statement of the central business aim that is motivating the use and implementation of a DT, e.g., ‘optimize traffic’. “DT Use Case Scenario” [UCS]: a documentation of the sequence of actions, or in other words, DT-user interactions executed through a particular DT case study or an actual DT real-world project. “DT Use”: a typical technical function or action executed by any DT throughout the course of any UCS. Accordingly, the DT uses are seen as the standard building blocks by which a standard common language can be founded. Such a standard language, which can possibly be machine-readable as well, can be used in documenting and detailing the DT-user interactions in a standard format to facilitate their publishing and sharing of knowledge. Below is a figure of a “DT uses taxonomy”. It is made up of three distinct hierarchical levels, these are respectively: ‘Included Uses’ containing four high-level cornerstone uses that are, besides rare exceptional cases, included in and executed by almost every DT throughout any UCS (i.e. Mirror, Analyse, Communicate and Control); ‘Specialized Uses’ including special forms of the Included Uses, where each specialized use enjoys unique strengths suitable for specific purposes; and “Specialized Sub-Uses” at the lowest hierarchical level of the taxonomy, which further differentiates between variant types within a Specialized Use at the higher level by virtue of very fine inherent variations that distinguish one type from another and thus, enhances the DT’s practical adequacy in dealing with alternative contexts and user specifically defined purposes. The table below include a formal definition of each DT Use. DT Use Definition Synonyms 01 Mirror To duplicate a physical system in the real world in the form of a virtual system in the cyber world. Replicate, twin, model, shadow, mimic 1.1 Capture Express in a digital format within the virtual world the status of a physical system at a point of time. (Usually, offline DT) collect, scan, survey, digitalize 1.2 Monitor Collecting information related to the performance of a physical system. (Online or Offline DT) Sense, observe, measure 1.3 Quantify Measure quantity of a physical system’s particulars, instances or incidents. (Online or Offline DT) Quantify, takeoff, count 1.4 Qualify Track the ongoing status of a physical system (Online or Offline DT) Qualify, follow, track DT Use Definition Synonyms 02 Analyse To create new knowledge and provide insights for users and stakeholders about a physical system. Examine, manage 2.1 Compute To perform conventional arithmetical calculations, traditional mathematical operations and functions and simple statistical techniques like correlations Calculate, add, subtract, multiply, divide 2.2 Mine To uncover, identify and recognize the web of interdependencies, interconnected mechanisms, complex processes, interwoven feedback loops, masked classes, clusters or typologies, hidden trends and patterns within the physical system. Learn, recognize, identify, detect, AI, ML, BDA 2.3 Simulate To explore and discover the implications and possible emerging behaviours of a complex web of interacting set of variables. 2.3.1 Scenario To find out the implications, impacts or consequences of implementing pre-defined scenarios (akin to non-destructive tests) What-if, evaluate, assess 2.3.2 Stress-Test To identify the scenarios that may lead to failure or breakdown of physical system (akin to destructive tests) Test, inspect, investigate 2.4 Predict Concerned with futures studies 2.4.1 Forecast to predict the most likely state of a real system in the future, by projecting the known current trends forward over a specified time horizon. foresee 2.4.2 Back-cast To question or prove in a prospective manner, how the physical system is operating towards achieving the pre-set aims and goals. manage, confirm 2.5 Qualitize Enhance and improve the quality of the outcomes or deliverables produced by an intervention in real world. 2.5.1 Verify Verify conformance and compliance of physical system with standards, specifications and best practice. Validate, check, comply, conform 2.5.2 Improve Inform the future updating, modifying or enhancing the current standards to be in better coherence and harmony with the actual operational and usage behaviours and patterns. Update, upgrade, revise DT Use Definition Synonyms 03 Communicate To exchange collected and analysed information amongst stakeholders. interact 3.1 Visualize To form and vision a realistic representation or model of current or predicted physical system. review, visioning 3.2 Immerse To involve interested stakeholders in real-like experiences using immersive technologies such as VR, AR and MR. involve 3.3 Document Document and represent gathered and/or analysed data in a professional manner and technical language, forms or symbols. Present 3.4 Transform To modify, process or standardize information to be published and received by other DT(s) or other DT users (e.g. a National DT) or overcome interoperability issues Translate, map 3.5 Engage To involve citizens and large groups of people including marginalized groups in policy and decision-making processes. Empower, include DT Use Definition Synonyms 04 Control To leverage the collected and analysed information to intervene back into the real world to achieve a desirable state. Implement, execute 4.1 Inform To support human decision making throughout the implementation of interventions in the real world. Support, aid 4.2 Actuate Using CPS and actuators to implement changes to physical system. Regulate, manipulate, direct, automate, self-govern Standardised set of ‘DT Uses’ can help avoid miscommunication and confusion while sharing or publishing DT Use Case Scenarios and their content explicitly explaining the 'know-how'. It can also support the procurement of DT services by ensuring the use of a one common language across the supply chain and stakeholders. Al-Sehrawy R., Kumar B. @Bimal Kumarand Watson R. (2021). Digital Twin Uses Classification System for Urban Planning & Infrastructure Program Management. In: Dawood N., Rahimian F., Seyedzadeh S., Sheikhkhoshkar M. (eds) Enabling The Development and Implementation of Digital Twins. Proceedings of the 20th International Conference on Construction Applications of Virtual Reality. Teesside University Press, UK.

It is proposed that the Information Management Framework (IMF) for the creating of a National Digital Twin will consist of three technical elements: the Foundation Data Model (FDM), Reference Data Library (RDL) and Integration Architecture (IA). The IMF will underpin the creation of an environment which supports the use, management and integration of digital information across the life-cycle of assets. The IMF will also enable secure, resilient information sharing between organisations and will facilitate better decision making across sectors. The National Digital Twin Programme has initiated work investigating this approach with a thin slice of the IMF for the Construction Innovation Hub, to support the development of CIH’s Platform Ecosystem. This thin slice of the IMF is called the FDM Seed. The FDM describes basic concepts such as space-time which are attributable across all areas of our industry. By developing this, the FDM provides a way to explore relationships between these different areas. The FDM Seed is an inception of the above concept and is proposed by starting smaller and watching the development grow - similar to a seed. The first steps of the FDM Seed project is to survey the landscape, to investigate what ontologies and Data models are already in use out there, what they can do, and their limitations, and assess what tools may be useful as a starting point for the FDM and the RDL. The starting point for the FDM is a top-level ontology, this contains the fundamental and generic types of things that exist and the fundamental relationships between them. The survey of Top-Level Ontologies (TLOs) uncovered a surprisingly high number of candidate TLOs with 40 being identified and reviewed, many more that we could have imagined. Fig 1.General classification of the TLO – taken from A Survey of Top-level Ontologies The final survey of top-level ontologies is, we think, the first of its kind. We were looking for an ontology that was rigorous, simple and with sufficient explanatory detail to cover our scope of interest, which is very broad. There are roughly two groups of TLOS, Foundational and Generic: The foundation are rigorous, principled foundations and provide a basis for consistent development and would be suitable for the FDM. The Generic tended to generalisations of lower level, rather than principled and lack a principled basis for extension, and therefore not suitable for the structure of the FDM, though likely to be use for the FDM generic lower levels. An RDL provides the classes and properties to describe the detail of an asset. The survey hoped to identify the most prominent of Industry Data Models and show the best starting point for the IMF RDL. There are many different RDLs in use across sectors. For the purpose of the FDM seed a limited analysis was carried out, but the list is open, and more candidates will be added for future consideration. Surveying and analysing the most commonly used RDLs will mean we are able to give guidance to organization when mapping their existing RDLs to the NDT. Next steps The Survey papers have now been published. We encourage you to engage with the National Digital Twin Programme to find out more about the approach, the results of the survey and the Assessments of the TLOs and Industry Data Models & RDLs. You can find these resources under the 'Files' tab. The Programme is now in the process of gathering their recommendations for the TLOs to use to start the work on the FDM Seed thin slice. We anticipate basing the FDM development on one of the TLOs, bringing in elements from others, based on the survey & analysis.

Strategic planning for life after Covid-19 brings an unprecedented opportunity to change the way we view and manage our infrastructure. Mark Enzer, from CDBB makes the case for putting people first. The current pandemic has been a powerful but unforgiving teacher. It has demonstrated the importance of data and the power of digital models to derive insights from those data, to help us model outcomes, to guide the pulling of the levers to control “R” and to help us make better more-informed decisions. Covid’s disruptive impact across all sectors and societies has also revealed the interconnections and interdependencies between our economic and social infrastructure, highlighting the importance of creating resilient, sustainable and secure infrastructure systems upon which essential services depend. So why change our view of infrastructure? We have created an amazing, complex machine on which we wholly depend. Without it, our lives would be immeasurably worse. Society would not survive. That machine is infrastructure – our built environment. However, we don’t appreciate the relationship between infrastructure and our wellbeing. Therefore, we don’t set objectives in terms of outcomes for people and society. And although we understand each part of the built environment, we do not manage it as a whole. Therefore, we don’t know how to address its systemic vulnerabilities or make it work better. If we envision, plan and manage infrastructure differently, we can make it what it should truly be: A platform for human flourishing. Putting people first The Centre for Digital Built Britain (CDBB) and the Centre for Smart Infrastructure and Construction (CSIC) have recently published ‘Flourishing systems’, which makes the case for a people-focused systems-based vision for infrastructure. As we consider priorities following the Covid-19 outbreak, we have an opportunity to plot a new course that recognises the fundamental role of infrastructure in the social, economic and environmental outcomes that determine the quality of people’s lives. To do this, we must see infrastructure as a complex, interconnected system of systems that must deliver continuous service to society. Infrastructure is so much more than just a series of construction projects. Adopting a system-of-systems approach makes it possible to address the great systemic challenges such as achieving net-zero carbon emissions, improving resilience and preparing for a circular economy. It also unlocks the potential of digital transformation across the built environment. How digitalisation delivers value With the ongoing digital transformation of the infrastructure industry, we have the opportunity to deliver huge benefit for people – for whom infrastructure ultimately exists. Digital transformation encompasses how we function as organisations, how we deliver new assets and how we operate, maintain and use existing assets. Bringing digital and physical assets together creates cyber-physical systems – smart infrastructure. Effectively, this is applying the fourth industrial revolution to infrastructure. Making better use of asset and systems data is central to this vision because better analysis of better data enables better decisions, producing better outcomes, which is the essential promise of the information age. As part of this, we must recognise digital assets, such as data, information, algorithms and digital twins, as genuine ‘assets’, which have value and must be managed effectively and securely. In time, as data and digital assets become valued, data itself will be seen as infrastructure. We are now at a point where the vision for effective digitalisation of the whole of the built environment is within reach. Enabling secure, resilient data sharing Managing complex interconnected systems requires the appropriate tools. CDBB’s National Digital Twin programme sets out a structured approach for effective information management across the system as a whole. This approach is informed by ‘The Gemini Principles’ and is driven by the NIC’s ‘data for the public good’ report. The recent paper ‘Pathway Towards an Information Management Framework’ suggests an approach for the development of an Information Management Framework to enable secure, resilient data sharing across the built environment. It is this that will enable data connections between digital twins, which is at the heart of the concept of the ‘National Digital Twin’ – an ecosystem of connected digital twins. All systems go Taking a systems-based approach to our infrastructure will improve our ability to deliver desirable outcomes for people and society – around accessibility, inclusion, empowerment, resilience and wellbeing – not just for now but for generations to come. It will also better equip us to address the urgent global systemic challenge of climate change. It’s time to see infrastructure differently – as a system of systems that provides a platform for human flourishing. flourishing-systems_final_digital.pdf

Hi all, Today CDBB released their BIM interoperability report. While BIM is distinct from Digital Twins there will be a need to interoperate between them. As such, I think this report will be of use to members. The report is currently out for public consultation. Available at the link provided and attached below ☺️ https://www.cdbb.cam.ac.uk/news/bim-interoperability-expert-group-report cih_bim_interoperability_expert_group_report_april_2020_final.pdf

Development of common Ontologies and Taxonomies will be key to interoperability and data exchange between Digital Twins. So who's actively developing them? At Highways England we are actively developing a Domain Ontology to serve as the basis for our data modelling and information sharing within and outside our organisation. I'm keen to solicit as much input to this as possible, as well as learn from the efforts of other organizations. Protégé users (it's free) can review the Ontology as it develops by requesting access to: https://webprotege.stanford.edu/#projects/0b3be685-73bd-4d5a-b866-e70d0ac7169b/edit/Classes Let me know your username (you can reach me at ian.gordon@highwaysengland.co.uk) and I'll give you access. Feedback is much appreciated.

During discovery interviews with DT Hub members, several barriers relating to the use of digital twins were identified. This blog post is one of a series which reflects on each barrier and considers related issues so that we can discuss how they may be addressed. As our members, and indeed other organisations active in the built environment, develop data and information about their assets, the ability to ensure that this data can be used within other tools is a priority. To do so, the data needs to be interoperable. One definition of interoperability is: In brief, if data can be shared between systems it is considered interoperable. Typically, this can be achieved in one of two ways: Both systems use the same formal description (schema) to structure the data; or One system transforms its data using an intermediate formal description (schema) to structure the data The simplest solution appears to be (1), to have all systems create, use and maintain information using the same schema. This would mean that information could be used in its default (native) format and there would be no risk of data being lost or corrupted during its transformation. However, this isn’t practicable as, from a technical perspective, it is unlikely that the broad range of information needed to support every possible purpose could be captured against the same schema. In addition, public procurement directives require performance-based technical specifications as opposed to naming specific software. This means that an organization may be challenged if they specify their supply chain use a particular piece of software as it would circumvent directives around competition and value for money. As it is not possible to guarantee that the same schema will be used throughout, it is far more practicable to identify which established industry schema is most suitable to accept data within (2) depending on the purpose of using this information. In doing so, there is an added benefit that the information you receive may be open data. Typically misused as a synonym for interoperability, open data is important for sharing but for a specific reason. Open data, in brief, is un-restricted data. By using proprietary software and systems the schema used to structure that data is hidden. As a user of that software you are effectively given permission by the vendor to use that structure to view your information. For built environment assets this can be a problem as the physical asset can outlast the software used to design and manage it. Meaning that in 50 years a tool that allows access to this information may not exist - or sooner given the cannibalistic nature of the software industry. Consider SketchUp for example. Since its release in 2000, it has been owned by three different organizations: @Last Software, Google, and Trimble. The permission to use the SKP schema has changed hands several times. Who will produce software to view these files in 30 years’ time? To ensure enduring access to asset information, either bespoke schemas need to be developed and maintained internally, or an established open schema needs to be used. However, while several open schemas are readily available (such as IFC, PDF, PNG, MQTT) they can raise concerns related to access, control and abuse of the data within. These concerns, thankfully, can be offset through control. Using open data structures, it is possible to ensure that only the information you wish to exchange is delivered. By using proprietary structures hidden information can also be exchanged which cannot be controlled; potentially causing a larger risk than their open counterparts. Conversely, to produce a “need-to-know” dataset an open data approach is, ironically, easier to control. When considering which methodologies to use, open data benefits typically outweigh its risks. The use of these open data structures will not only unlock interoperability between digital twins within an organization but will be the mechanism that enables a secure national digital twin. Access to appropriate data about our national infrastructure is currently held behind proprietary schema. Let’s make Britain’s data open again! We hope you enjoyed this short piece on breaking the barriers related to interoperability. What specific challenges have you faced relating to the implementation of interoperability? Do you consider open data in this content is an opportunity or a threat? Would you prefer the National Digital Twin to be based on an open or a propriety schema?