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In conversations we’ve had in the Digital Twin (DT) Hub and the wider Centre for Digital Built Britain (CDBB) community, there have been significant concerns about the costs involved in investing in a digital twins. We believe, that to mitigate the risk and avoid the need to make changes down the line, standards are of vital importance. We need a shared foundation and framework to support the end goal of secure data exchange and interoperability.
We’ve made significant progress towards that goal and it’s exciting to be pioneers in establishing what will hopefully be a common language - guidelines that can be used, not just here in the UK, but globally.
To start with, we’ve needed to gain a thorough understanding of what the current standards landscape looks like and the CDBB commissioned the British Institute of Standards (BSI) to do the research. Their initial scoping exercise is complete and BSI and CDBB are now reviewing the results of this exercise to identify if and where standards are needed to overcome a specific challenge or fulfil a purpose. We’ve also looked to other sectors to see if existing standards can be applied or modified to work in the built environment.
We are now in the process of creating a clear roadmap that prioritises standards to be developed. The document will be accompanied by a report to include the narrative, justification and rationale behind the roadmap. It will be presented through a series of thematic areas: Digital Twins, Data, ICT, Application, and Outcomes as well as multiple sub-topic themes, to help enable users to locate key standards.
The end goal is a very practical guide. It will cover everything from a shared vocabulary, to ensure consistent definitions of assets, to recommended data formats, user case methodology, a code of practice on information exchange and so on.
A vital part of the process is involving stakeholders and we’re very grateful for all the feedback we’ve received so far. We have recently had the opportunity to share the latest review with DT Hub members as well as those within the wider digital twin community. Attendees of the recent workshop, hosted by BSI, had the opportunity to both critique and verify the findings as well as to share their views on some of the priorities for standards to support successful digital twins in the built environment. This has been a valued opportunity to really shape the direction of these important developments as we can’t do it alone.
A great example of the impact standards can make is one I came across from the early 1900s when the BSI developed a standard for tram gauges at a time when, in the UK alone, there were 75 different widths of gauge! They succeeded in reducing it down to five recommended widths. These became the standards going forward and greatly boosted the industry’s fortunes increasing compatibility between networks and rolling stock. As the British standard was adopted abroad, the UK tram market enjoyed more opportunities to trade and business flourished.
We hope to make a similar kind of impact – we want to see all developers of digital twins flourish and benefit from the advantages that sharing data and ideas can bring. But in order to do that successfully, the whole process needs to be underpinned by standards that have been formed out of thorough research and review and have the support and involvement of as many people as possible. We look forward to seeing you around the DT Hub!
Samuel Chorlton, Chair of the Digital Twin Hub
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?
the_pathway_towards_an_imf.pdf the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf HUB Version_DT Standards Roadmap_November 2020 (3).pdf DT Hub SII SUMMARY - Published.pdf
For a few years now, parts of our sector and indeed other sectors, have been researching, defining and promoting digital twins. If we observe anything, it’s that chatter (including within the DT Hub) has been rife with the ‘what is/isn’t a digital twin...’
I’m no expert, and don’t yet claim to offer a resolution to clarify the topic, but I do think a discussion hosted within the DT Hub would be of use. This discussion is something that will provide greater clarity and implementation for those less involved in this definition process and yet vitally important to the delivery of whatever a digital twin of the future is destined to be.
Let’s learn from BIM implementation
I wear many hats in my career and most of them are related to the implementation and ‘normalisation’ of BIM processes. As Vice Chair of the UK BIM Alliance and Chair of the UK & Ireland Chapter of buildingSMART International, I’m afforded a view of the sector from various different levels of stakeholders and the challenges they face in an ever-changing world as they prepare to digitalise. The silent majority are perhaps the key to unlocking the transformation to a digital sector and it’s vital that the BIM message reaches them and connects in a meaningful way to each and every one of them... BIM in the UK has been ongoing for over a decade and my feeling is that there is at least another to go before we reach ‘business as usual’. It’s exactly the same for Digital Twins.
All vocal parties involved here in the DT Hub seem keen to navigate more smoothly through the same sectoral challenges and one of those, in a similar vain to BIM, is “is this a Digital Twin or not”?
Acknowledging that BIM in the UK has formerly been going through the same sector engagement, we can also see similar issues appearing now with the concept behind Digital Twins being taken over by technology providers rather than sector stakeholders and subsequently being marketed in that way. It’s by no means a UK-only challenge, with many global discussions observed.
Hence, we’re rapidly on the way to Digital Twins being defined by technologies rather than their use and value to us as people. A human-centric approach to any digital transformation will almost always achieve greater adoption and ultimately ‘success’ than one led purely by technology. Hence the CDBB National Digital Twin Programme envisages the built environment as a system of systems, comprising economic infrastructure, social infrastructure and the natural environment. The CDBB Gemini Principles neatly position Digital Twins in a way that forces one to consider the overall business need (the ‘why’) and all the potential societal benefits.
Other DT Hub discussions have touched on the possibility of a Turing-type test. The original Turing test was created by Alan Turing to determine whether or nota machine was discernible from a human. Whilst the test is valuable for determining artificial intelligence, it’s also one that is evaluated by humans and hence quite challenging to ensure all evaluators are equal. Perhaps a technology-driven test that provides both a score and a ‘time taken’, introducing a level of competition between creators of Digital Twin systems might help adoption.
So here’s the proposition... we hold a workshop (or two) to discuss and investigate the need for a test, the type of test, ‘what’ is being tested, what the thresholds might be, and anything else that’s relevant to the topic of ascertaining whether or not someone’s proposed Digital Twin is actually a Digital Twin.
I have three questions to start the discussion here in this thread...
1. Do you feel the need for a ‘test’ to determine whether or not a Digital Twin is a Digital Twin? Can we continue without a formal ‘test’ or should we actively seek to develop something absolute to filter out what we’ve been able to do for many years and focus on true Digital Twin solutions and the search for the allusive Digital Twin unicorn?!
2. If we do need a test, will a simple yes/no suffice? Or does a ‘score have more longevity? If you ever saw the HBO series Silicon Valley, you may be familiar with the Weismann Score, a fictional test and score for online file compression. It enabled the fictional tech companies to demonstrate the success of their software and algorithms by testing their performance for file compression. Would a similar test be suitable for our purposes, with a threshold for determining if a proposed Digital Twin is a Digital Twin and would it then cater for future digital developments and emerging technologies?
3. Finally, are you keen and able to join a virtual workshop?
the_pathway_towards_an_imf.pdf the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf HUB Version_DT Standards Roadmap_November 2020 (3).pdf
Open Sharing of Data Asset Registration Scenario Simulation Occupant/User Management Environmental Management Traffic Management Process Optimization Asset Management Carbon Management Resource Management Resilience Planning Risk Management Using these use cases, we can begin to explore how the National Digital Twin (NDT) programme can support members of the DT Hub in realizing their value. One way of doing so is by identifying what parts of these use cases need to be developed via the Commons Stream as part of the Information Management Framework (IMF).
The reasoning being these 12 use cases are:
Horizontal. Meaning that they can be applied within several sectors and their respective industries; and High-value. Meaning that they can achieve a return on investment. Positively, these use cases have a strong synergy with a similar schedule presented by Bart Brink of Royal HaskoningDHV on a recent buildingSMART webinar on digital twins.
By identifying DT Hub member horizontal, high-value, use cases we hope that their associated tasks, key performance indicators and federation requirements can be recommended for prioritization as part of the development of the Information Management Framework (IMF).
At the beginning of June, CDBB released The Pathway Towards an Information Management Framework: A Commons for a Digital Built Britain, a report setting out the technical approach that will lead to the development of the National Digital Twin. Within the report it focuses on three key facets that will enable secure, resilient data sharing across the built environment:
Reference Data Library. A taxonomy describing a common set of classes to describe the built environment; Foundation Data Model. An ontology outlining the relation between these classes or properties of these classes; and Integration Architecture. Exchange protocols to facilitate sharing of information, using these defined classes and relations between digital twins.
As opposed to being released as a complete resource, we will likely see these facets developed organically as the NDT programme continues to follow its mantra of:
As such, the key question isn’t “what should these facets include?” but “what should be included first?”. We hope to answer this question using these horizontal, high-value, use cases.
EXAMPLE:
“Environmental management”. At the beginning of 2020, news reports focused on air pollution and its link with infrastructure. In addition, many building assets may wish to monitor air quality due to its known impact on occupant performance. As a use case that is associated to regulatory compliance, productivity, and applicable to a breadth of assets Environmental Management may be a horizontal, high-value, use case.
To support such a use case, the:
Reference Data Library. May need to include classes such as: Temperature, Wind speed, Humidity, CO2, and PM2.5 as well as their associated units to enable the consistent recording of this information. Foundation Data Model. May need an ontology describing acceptable ranges and the relationship of air quality concepts to other classes such as Health and Productivity depending on the function being monitored; and Integration Architecture. May need to facilitate the sharing of information from sources such as other digital twins, as well as datasets from the Met Office and local governments. Simply put, by identifying these horizontal, high-priority, use cases, we may be able to begin accelerating the realization of their value by having the taxonomies, ontologies and protocols needed to facilitate them available at an earlier stage of the overall IMF development.
And there we have it. As DT Hub members begin to consider how the information management framework may support their digital twin development as well as the national digital twin, which use cases do you think are the most horizontal and high-value? How do you think these facets might support your ability to undertake these use cases?
Please feel free to add your thoughts below, or, alternatively, comment directly on the draft community-driven document which is, and will continue to be, progressively developed as member views are shared.
the_pathway_towards_an_imf.pdf the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf HUB Version_DT Standards Roadmap_November 2020 (3).pdf
To ensure that these resources are fit-for-purpose, they need to align to the needs of the DT Hub members; supporting use cases. As such, this article uses the output of the Theme 3 webinar to explore and begin to identify horizontal, high-value, use cases for prioritization.
The outcome of this work will be a community-driven document (draft under development here) to inform the Commons on which use cases should be considered a priority when developing resources.
During the Theme 3 webinar, a total of 28 use cases were identified by members.
Open Sharing of Data
Data-sharing Hub
Health and Safety
Social Distancing
Customer Satisfaction
Behavioural Change
National Security
Traffic Management
Incident Management
Efficiency Monitoring
Condition Monitoring
Scenario Simulations
Rapid Prototyping
Asset Optimization
Investment Optimization
Preventative Maintenance
Carbon Management
Service Recovery
Decision Support
National Efficiency
‘Live’ in-use Information
Logistic / Transit Tracing
Natural Environment Registration
Pollution Monitoring
Air Quality Monitoring
Resilience Planning
Resource Optimization
Service Electrification
This initial schedule demonstrates the breadth of value that a digital twin can facilitate. However this list can be refined as some of these use cases:
Overlap and can be consolidated through the use of more careful terminology. For example both Pollution Monitoring and Air Quality Monitoring were identified. However it is likely that the system, sequence of actions, as well as any associated key performance indicators will be shared between these use cases. Therefore they could be consolidated under a single use case Environmental Monitoring.
May be specific to some members or some sectors. For example, Customer Satisfaction Monitoring is a vital use case for DT Hub members who directly engage with a user-base within a supplier market (for example, utility companies and universities). However, many organizations manage assets and systems whose actors do not include a customer (for example, floor defence systems, and natural assets). Likewise, Service Electrification is a use case that is only applicable for assets and systems which rely on fossil fuels (for roads and railways). As such, while Customer Satisfaction Monitoring and Service Electrification are vital use cases which must remain within scope of the overall programme, they may not be appropriate for prioritization.
Are aspects as opposed to a stand-alone use case. For example, ‘Live’ In-use Information may be a requirement of several use cases such as Traffic Management and National Security but does not in itself constitute a sequence of actions within a system. By identifying the use cases that are most common to DT Hub members as well as eliminating duplicates, it is hoped that a refined schedule can be produced; limited to high-value, horizontal use cases. Such a schedule will be valuable to:
The NDT programme to understand what use cases the IMF Pathway will need to support; Asset owner/operators to identify and articulate the value-case for implementing digital twins; and Suppliers to demonstrate the validity of their software in realizing these values. Furthermore, once a streamlined schedule has been developed, further research can be undertaken to identify the typical key performance indicators used to measure and monitor systems that support these use cases.
And there we have it, useful use cases. Of the 28 use cases identified which do you think are the most horizontal? Which do you think are high-value (priority) use cases? Which do you think could be aggregated together?
Please feel free to add your thoughts below, or, alternatively, comment directly on the draft community-driven document which will be progressively developed as member views are shared. Feel free to comment on the content included and suggest how to refine the schedule.
the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf HUB Version_DT Standards Roadmap_November 2020 (3).pdf
As organizations develop a wide array of datasets and supporting tools, a key concern has been the capability of the people using these resources to make decisions and take action. To do so, these people need to be sufficiently skilled.
Industry reports, such as the Farmer Review, have consistently identified skills shortage as a key issue within the built environment. This figure below, produced by the Construction Products Association (CPA), shows the proportion of firms who have had difficulties in recruiting traditional trades. For example, in the first quarter of 2017, over 60% of firms had difficulty recruiting bricklayers.
A cause of this shortage is the lack of training being provided by organizations within the built environment. As shown in the figure below from the Farmer Review, workforces within the built environment are some of the least trained. While an obvious solution may be simply to provide more training, the issue is confounded by the fact that we need to inject a new set of skills in to the sector; increasing the amount of training required.
In 2018, The World Economic Forum produced their Future of Jobs Report. It considered what are the current emerging and declining skills as a result of digital transformation, automation and the fourth industrial revolution.
These, are highlighted in the table below.
Considering the results provided, the need for manual skills as well as installation and maintenance skills are declining rapidly. As such there is a risk that any immediate training to fill our skills gap may not be suitable for future employment needs. As initiatives such as the Construction Innovation Hub and Active Building Centre consider Design for Manufacture and Assembly (DfMA) and other more modern methods, perhaps the focus should be on which skills are needed for the future.
Digital twins, as representations of physical assets, processes or systems, will need to be interfaced with built environment professionals of the future. The question however, is in what capacity? Let’s consider a scenario:
Cardiff University has a digital twin of their campus. Within this twin, they have included sensors to record the usage and occupancy of lecture halls to access space optimization.
For an estate manager to be able to use this twin, they may benefit from:
Software skills, to interface with the incoming data. This software may not be part of their core asset management system; needing additional knowledge and skills to use. Analytical thinking, to allow them to test scenarios. For example, to test what would happen to usage if a single building was changed to private rent from external customers; improving the universities income generation. Creative thinking, to allow them to consider new ideas. For example, to use the timetable to place lectures that straddle lunch across-campus; increasing foot-traffic past the university lunch hall. Intuitive thinking, to allow them to question outputs. For example, to be able to identify when a faulty sensor may have led to data discrepancies or when an analysis programme has identified importance solutions due to its correlative nature such as starting lectures at 6am to free up more rooms for private rent. Ultimately, the reason for adopting digital twins will be to provide value for an organization and its wider ecosystem. As such, problem-solving skills, critical thinking, systems analysis and analytical thinking will likely become core competencies. For organizations with critical long-term planning requirements, future employees need to be taught these skills now so that they are appropriately competent for the future.
And there we have it, breaking the barriers related to skills. How relevant do you think the WEF top 10 growing skills will be for future consumers of digital twin content? What skills do you consider to be core to future digital twin users?
the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf HUB Version_DT Standards Roadmap_November 2020 (3).pdf
This blog is the second in series that looks at what we can learn from the development of digital twins in other sectors. It draws on key findings from a report by the High Value Manufacturing Catapult. This includes industry perspectives on:
The definition of digital twins Key components of digital twins Types of twin and related high-level applications and value The report “Feasibility of an immersive digital twin: The definition of a digital twin and discussions around the benefit of immersion” looks partly at the potential for the use of immersive environments. But, in the main, it asks a range of questions about digital twins that should be of interest to this community. The findings in the report were based on an industry workshop and an online survey with around 150 respondents.
We’ve already seen that there are many views on what does or does not constitute a digital twin. Several options were given in the survey, and the most popular definition, resonating with 90% of respondents was:
A virtual replica of the physical asset which can be used to monitor and evaluate its performance
When it comes to key components of digital twins, the report suggests that these should include:
A model of the physical object or system, which provides context Connectivity between digital and physical assets, which transmits data in at least one direction The ability to monitor the physical system in real time. By contrast, in the built environment, digital twins may not always need to be “real-time”. However, looking at the overall document, the position appears to be more nuanced and dependent on the type of application. In which case, “real-time” could be interpreted as “right-time” or “timely”.
In addition, analytics, control and simulation are seen as optional or value-added components. Interestingly, 3D representations are seen by many as “nice to have” – though this will vary according to the type of application.
In a similar fashion to some of our discussions with DT Hub members, the report looks at several types of digital twin (it is difficult to think of all twins as being the same!). The types relate to the level of interactivity, control and prediction:
Supervisory or observational twins that have a monitoring role, receiving and analysing data but that may not have direct feedback to the physical asset or system Interactive digital twins that provide a degree of control over the physical things themselves Predictive digital twins that use simulations along with data from the physical objects or systems, as well as wider contextual data, to predict performance and optimise operations (e.g. to increase output from a wind farm by optimising the pitch of the blades). These types of twin are presented as representing increasing levels of richness or complexity: interactive twins include all the elements of supervisory twins; and predictive twins incorporate the capabilities of all three types.
Not surprisingly, the range of feasible applications relates to the type of twin. Supervisory twins can be used to monitor processes and inform non-automated decisions. Interactive twins enable control, which can be remote from the shop-floor or facility. Whereas, predictive twins support predictive maintenance approaches, and can help reduce down-time and improve productivity. More sophisticated twins – and potentially combining data across twins – can provide insight into rapid introduction (and I could imagine customisation) of products or supply chains.
Another way of looking at this is to think about which existing processes or business systems could be replaced or complemented by digital twins. This has also come up in some of our discussions with DT Hub members and other built environment stakeholders – in the sense that investments in digital twins should either improve a specific business process/system or mean that that it is no longer needed (otherwise DT investments could just mean extra costs). From the survey:
Over 80% of respondents felt that digital twins could complement or replace systems for monitoring or prediction (either simple models or discrete event simulation) Around two-thirds felt the same for aspects related to analysis and control (trend analysis, remote interaction and prescriptive maintenance) with over half seeing a similar opportunity for next generation product design While remote monitoring and quality were seen as the areas with greatest potential value. Cost reduction in operations and New Product Development (NPD) also feature as areas of value generation, as well as costs related to warranty and servicing. The latter reflects increasing servitisation in manufacturing. This could also become more important in the built environment, with growing interest in gain-share type arrangements through asset lifecycles as well as increasing use of components that have been manufactured off-site.
It would be great if you would like to share your views on any of the points raised above. For example, do you think built environment twins need the same or different components to those described above? And can digital twins for applications like remote monitoring and quality management also deliver significant value in the built environment?
the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf HUB Version_DT Standards Roadmap_November 2020 (3).pdf
The idea of digital twins in space may seem like science fiction – or at least a long way removed from the day-to-day challenges of the built environment. But, in fact, the aerospace industry has been at the forefront of many of the technology innovations that have transformed other areas. Before Michael Grieves coined the term digital twin in 2002, NASA was using pairing technology to operate and repair remote systems in space.
Digital twins, in the aerospace sector, have since gone way beyond simulations. This is driven by a need to accurately reflect the actual condition of space craft and equipment and predict potential future issues. While the crew of Apollo 13 may have relied on a physical double as well as digital data, future space stations and trips beyond our atmosphere will be using digital twins to deliver the right kinds of insights, decision support and automation needed to achieve their missions.
Despite the great distances and the technological advancement of space technologies there are valuable parallels with industries back on earth. For example, digital twins of remote and autonomous vehicles (like the Mars Exploration Rover) could provide useful lessons for similar vehicles on earth, from robots in nuclear facilities and sub-sea environments, through to delivery vehicles in a logistics centre or drones on a building site.
More specifically, a 2012 paper co-authored by NASA provided several insights into the approach to digital twins in aerospace, including the following definition:
A Digital Twin is an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding flying twin
Digital twins could represent a significant shift away from a heuristic (i.e. past-experience based) approach to one using sophisticated modelling combined with real-life data. This shift impacts design and build, certification and ongoing operation. The drivers behind this change include a need to withstand more extreme conditions, increased loads and extended service life. (Imagine a manned trip to Mars, or one of the new commercial space ventures that call for vehicles to be used again and again).
The paper also looked at some of the needs and priority areas for digital twins, including:
more accurate prediction of potential materials failures; as well as the condition of other systems in space vehicles by connecting multiple models with data from the physical twin. If digital twins can add value in the harshest environment imaginable, what applications could this have for the built environment? One example is the interesting parallels between assessment of the risks of cracks and failures in long-life space vehicles and long-term structural monitoring of bridges and other infrastructure. The required level of fidelity (i.e. the level of detail and accuracy) as well as the extent to which real-time data is needed, may vary considerably – but many of the same principles could apply.
More widely, the authors of the paper felt that the parallels and benefits from developing digital twins for aerospace could extend across manufacturing, infrastructure and nanotechnology.
The ideas explored in the paper also go well beyond monitoring and towards automation. For complex space missions, vehicles may not be able to get external help and will need to be self-aware, with “real-time management of complex materials, structures and systems”. As the authors put it:
“If various best-physics (i.e., the most accurate, physically realistic and robust) models can be integrated with one another and with on-board sensor suites, they will form a basis for certification of vehicles by simulation and for real-time, continuous, health management of those vehicles during their missions. They will form the foundation of a Digital Twin.”
Such a digital twin could continuously forecast the health of vehicles and systems, predict system responses and mitigate damage by activating self-healing mechanisms or recommend in-flight changes to the mission profile.
While the context may be very different, our discussions with DT Hub members and others in the market suggest that built environment infrastructure owners and operators are aiming to achieve many of the same aspirations as NASA – from better prediction of potential issues through to actuation and self-healing.
Which space twin applications and ideas do you think we could apply to the built environment?
We would welcome your comments on this piece as well as your thoughts on other topics where you would like to hear more from us.
the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf HUB Version_DT Standards Roadmap_November 2020 (3).pdf
As we develop the thinking, tools, and resources relating to digital twins, a lot of discussion is taking place regarding their scope, scale and accuracy. Within the Gemini Principles it stated that a digital twin is:
I want to reflect on this statement. In particular, the use of “realistic”.
For something to be realistic, according to the Oxford English Dictionary, it must represent something in a way that is accurate and true to life. For example, for something to be “photo-realistic” it must appear as if it was a photograph.
However, the Gemini Principles state that a digital twin must represent physical reality at the level of accuracy suited to its purpose. Interestingly, while undertaking discovery interviews with DT Hub members we saw this issue realized.
Interview Insight
"Several members commented on how people in their organizations would try to extend the use of their digital twins beyond their intended purposes."
This was seen as both a positive and a negative outcome. The positive being that members of these organizations saw the value in these digital twins and wanted to harness their insight. The negative being that these digital twins did not have the information or, when available, did not have level of accuracy required to be used for these extended purposes. For these extended needs, these digital twins were not realistic.
Amongst DT Hub members there appears to be a shared view that digital twins are, fundamentally, purpose-driven. Therefore, digital twins might not be “real” representations, but instead the “right” representation to support a purpose.
Consider an example. An air traffic control system utilizes a “digital twin” of runways, aircraft and their flight paths along with sensor information (e.g. weather and radar) to assist with preventing collisions, organize and control the landing and departing of aircraft. In this example while real-time information and analytics are used, none of the physical elements (planes, control towers) have realistic representations, they instead use basic representations to support the air traffic controller. Instinctually an air traffic control system does everything we want a digital twin to do, it is a digital representation of physical assets which also includes sensor information where the physical assets provide a link back to the digital twin. Given this, it should be fairly clear that an air traffic control system would be considered a digital twin. However, this does not appear to be the case.
A poll was placed on twitter asking “would you consider an air traffic control system a digital twin”. After 62 votes were cast, the result was exactly 50:50. What does this tell us? Perhaps public messages on what a digital twin is aren’t sufficiently defined? Perhaps the question was poorly worded? Or perhaps, for some, the lack of a realistic representation is the reason they said no? Unfortunately, context for each vote isn’t available. At the very least we can be sure that our shared view may not be shared by everyone.
In an age where many consider data to be the new oil perhaps we should consider using our data sparingly. So long as the data provided is sufficient for its intended purpose, a realistic representation may not always be required.
And there we have it, realism and its place within Digital Twins. Do you believe that a digital twin has to be realistic? Can something be a digital twin without being a realistic representation? Had you voted on this poll, would you have considered an air traffic control system a digital twin?
Twin
What is
What if
Files
Queries
Physical
Real
Asset
Function
Time stamp
Time graph
Transaction
Enterprise
Outputs
Outcomes
As Designed?
As Intended? (for discussion)
I wanted to share some early thinking with you, and please consider this a consultation not a formal announcement of direction.
Following the latency post from @DRossiter87 and some conversations with people in different markets. I have found a useful framework to separate BIM from Digital Twins.
There is a caveat with the following, this is not a statement of which is better. Both BIM and Digital Twinning have key benefits. Much like a chef has a collection of knives for different use cases. The same is true for BIM and twins. BIM as defined in the standards available sets out how data can be procured in a transactional model. This is where a client can set the information requirements for a supply chain to author and deliver information for a particular purpose.
The table above sets out a series of differences and I will work through them one by one to explain what they mean and how they differ.
1. What is vs What if
A BIM will tell you what something is, it cannot answer the question what if. The IMF sets out a pathway for askign questions of datasets. For example “What if I turned this value off?”.
2. Files vs Queries
Very similar to the above, but with a view on functionality. The BIM sets out the container of the data and the files within. These files include CSV files or a SQL databases for example. The query in the twin space is an operation on the dataset or file.
3. Physical vs Real
The BIM space treats physical elements as assets. Those assets would be on some form of register which lists 'tangible things'. Those assets generally develop over time in line with the level of information need. In the twin space this representation of the physical is abstracted up into its function. The real aspect is how the object interacts with reality. This interaction is physically within the system (a pump pumping water) and is broader service / organisational purpose (the pump provides a minimum pressure to supply water to customers and is linked to the revenue stream that, for example, is charged by the cubic meter of water.)
4. Asset vs Function
Related to the above, the asset focus is purely on the performance specification and range of the asset's performance in isolation. The twin considers the function the asset plays. @Simon Scott explained a great example of this. The function of a level crossing is to ensure two types ofmobile infrastrcture do not collide (please correct me if im wrong here simon), there is a difference between asking for a level crossing (an asset) and asking for two infrastructures not to collide (a function) are fundementally two differnt questions.
5. Time stamp vs time graph
Time in BIM is a time stamp against a transaction or digital snapshot of an asset. The twin aspect is the time graph, the status of a person over time changes. The queries from the twin understand the historical elements of an asset. For example, when searching for an actor on google it can piece together data of that person from a series of datasets that allows a comprehensive history of that a actor to be rendered.
6. Transaction vs Enterprise
The BIM standards describe a process for multiple parties to transact data. They set out how data can be procured, authored and delivered as a series of transactions. The twin represents an enterprise view where data flows with purpose aligned with agreed outcomes.
7. Outputs vs outcomes
BIM through its focus on transactions and assets can only provide insight on outputs, where twins focus on functions and enterprise it can provide insights on outcomes.
8. 3D Rendition vs Abstracted
BIM requires a 3D rendition of an asset as set out in the level of information need / requirements. For the digital twin, and to use @DRossiter87example of a BMS, there is no need for a full representation of the asset. All that is required is the data needed in order to execute a decision, either for a machine or human.
Of course, if the what if statement includes a spatial requirement a boundary condition for the geometry is required. A non-geographic example, is that the BMS wants to know which rooms to heat for the day for a school, a key input could be the lesson plans from the teaching staff to understand occupancy of a space.
On the other hand, a geographic example is if the AHU requires a filter replacement and the plantroom is tight for space. There would be a need for a physical representation of the space.
I welcome the discussion and feedack!
the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf
Open Sharing of Data Asset Registration Scenario Simulation Occupant/User Management Environmental Management Traffic Management Process Optimization Asset Management Carbon Management Resource Management Resilience Planning Risk Management Using these use cases, we can begin to explore how the National Digital Twin (NDT) programme can support members of the DT Hub in realizing their value. One way of doing so is by identifying what parts of these use cases need to be developed via the Commons Stream as part of the Information Management Framework (IMF).
The reasoning being these 12 use cases are:
Horizontal. Meaning that they can be applied within several sectors and their respective industries; and High-value. Meaning that they can achieve a return on investment. Positively, these use cases have a strong synergy with a similar schedule presented by Bart Brink of Royal HaskoningDHV on a recent buildingSMART webinar on digital twins.
By identifying DT Hub member horizontal, high-value, use cases we hope that their associated tasks, key performance indicators and federation requirements can be recommended for prioritization as part of the development of the Information Management Framework (IMF).
At the beginning of June, CDBB released The Pathway Towards an Information Management Framework: A Commons for a Digital Built Britain, a report setting out the technical approach that will lead to the development of the National Digital Twin. Within the report it focuses on three key facets that will enable secure, resilient data sharing across the built environment:
Reference Data Library. A taxonomy describing a common set of classes to describe the built environment; Foundation Data Model. An ontology outlining the relation between these classes or properties of these classes; and Integration Architecture. Exchange protocols to facilitate sharing of information, using these defined classes and relations between digital twins.
As opposed to being released as a complete resource, we will likely see these facets developed organically as the NDT programme continues to follow its mantra of:
As such, the key question isn’t “what should these facets include?” but “what should be included first?”. We hope to answer this question using these horizontal, high-value, use cases.
EXAMPLE:
“Environmental management”. At the beginning of 2020, news reports focused on air pollution and its link with infrastructure. In addition, many building assets may wish to monitor air quality due to its known impact on occupant performance. As a use case that is associated to regulatory compliance, productivity, and applicable to a breadth of assets Environmental Management may be a horizontal, high-value, use case.
To support such a use case, the:
Reference Data Library. May need to include classes such as: Temperature, Wind speed, Humidity, CO2, and PM2.5 as well as their associated units to enable the consistent recording of this information. Foundation Data Model. May need an ontology describing acceptable ranges and the relationship of air quality concepts to other classes such as Health and Productivity depending on the function being monitored; and Integration Architecture. May need to facilitate the sharing of information from sources such as other digital twins, as well as datasets from the Met Office and local governments. Simply put, by identifying these horizontal, high-priority, use cases, we may be able to begin accelerating the realization of their value by having the taxonomies, ontologies and protocols needed to facilitate them available at an earlier stage of the overall IMF development.
And there we have it. As DT Hub members begin to consider how the information management framework may support their digital twin development as well as the national digital twin, which use cases do you think are the most horizontal and high-value? How do you think these facets might support your ability to undertake these use cases?
Please feel free to add your thoughts below, or, alternatively, comment directly on the draft community-driven document which is, and will continue to be, progressively developed as member views are shared.
the_pathway_towards_an_imf.pdf DTHUb_NewbieGuide_May2020_(1).pdf
Value; Manufacturing; Assurance; and Digital While the DT Hub forms part of the digital work stream, other elements of the CIH programme, such as the development of a value framework, are relevant to our discussions around enabling digital twins to realise value.
Of course, considering the breadth of organisations who are members of the DT Hub their approach to value will differ, as each organisation will have different social, environmental, and economic priorities. Having a value framework allows this variety to be articulated in a structured way so that all approaches can be expressed consistently. Shown below are the categories being considered as part of the CIH Value Framework, which was presented at a Generation4Change (G4C) event in May:
Based on The Five Capitals approach, each category within this framework is intended to be weighted to articulate an organisations’ definition of value. For example, an organisation such as the Environment Agency may wish to place a stronger weighting on natural values than an organisation that primarily operates within a large urban centre. Once the value categories and their respective weightings have been identified, the indicators associated with those categories need to be identified and measured. This is what we have tried to begin exploring within the DT Hub during June via our Pathway to Value conversation starters #1 and #2. These use cases were then developed into 12 horizontal use cases which can be broadly mapped onto the Five Capitals as shown:
Data
Sharing
Asset
Registration
Scenario Simulation
User/Occupant
Management
Process
Optimization
Asset
Management
Carbon Management
Resource Management
Environmental
Management
Resilience
Planning
Traffic Management
Risk
Management
NOTE: Data Sharing and Scenario Simulation are considered applicable to all value categories.
In turn, we did further research to demonstrate that these use cases can be attributed to performance indicators. For example, organisations who prioritise financial categories may wish to manage their assets. To manage these assets, they need to measure indicators such as:
Asset Utilisation; Capacity Utilisation; Mean time to failure; and Mean time to repair. To measure these indicators, several tasks will need to be undertaken; constituting a use case. Therefore it is reasonable to assume that, to realise value, each category that an organisation prioritises will need underlying use cases. It is these use cases that enable the respective indicators to be measured to determine whether value has been realised.
Value > Indicator > Tasks > Use Case
In addition, digital twins can themselves provide deeper insight into the value of multiple use cases. This is because of the way they connect to physical assets and systems, providing an ability to analyse and model what might happen next.
For example: Replacing a piece of plant within a system may impact on all of the five capitals as it may use less fuel (+ natural), perform to a higher efficiency (+ manufactured), reducing the operational cost of the asset (+ financial) with improved access and installation procedures (+ safety), but manufactured by an organisation with questionable ethics (- social).
It is only through the use of a digital twin that all of the indicators, for all of an organisations’ use cases, can be considered holistically. As the datasets develop they could even establish correlations that allow potential decisions to be measured against several value categories simultaneously to determine the outcome that provides the greatest overall value. These decision therefore will be data-driven; validating the value they intend to provide.
And there we have it. By determining which categories an organisation prioritises within a value framework, the associated indicators can be identified and measured to realise value. This helps an organisation to determine which of these indicators are most critical, which of their assets can be considered exemplar, as well a method of measuring the impact of future interventions and investments which in turn can support business cases. How suitable do you feel the CIH value categories are for your organisation? How does your organisation currently measure value? Are you aware of any alternative value frameworks that should also be considered?
DTHUb_NewbieGuide_May2020_(1).pdf
ISO 14033 (Quantitative Environmental Information) ISO 15704 (Requirements for enterprise-referencing architectures) ISO 18101-1 (Oil and Gas interoperability) ISO 30146 (Smart City ICT Indicators)
And, more interestingly, one of these saw the first definition for a digital twin included within an ISO document:
Within ISO, there are several requirements which need to be conformed to when producing a definition. These requirements are outlined within two standards:
ISO 10241-1 (general requirements and examples of presentation) ISO 704 (principles and methods) ISO 10241-1, which covers the structure of a term including how to structure a definition and referencing; and ISO 704, which covers the principles of doing terminology work. These standards state that when developing a definition, it should:
Be a single phrase specifying the concept and, if possible, representing that concept within a larger system; The digital twin definition from ISO/TS 18001 does so by referencing other key terms such as digital assets and services. This provides a relationship to other related terms. In doing so, this definition makes digital twin a type of digital asset being used to create value.
Be general enough to cover the use of the term elsewhere; This definition is specific enough to capture what a digital twin is in a generalist sense, while also being sufficiently generic that the same definition can be used in other standards. This is vital to achieve a harmonization of concepts across a disparate suite of documentation.
Not include any requirements; and In addition, this definition doesn’t say what needs to be done for something to be considered a digital twin. This is important as definitions are meant to inform, not instruct.
Be able to substitute the term within a sentence. Finally, and possibly the most challenging requirement, a definition needs to be able to substitute for the term within a sentence. For example:
This exemplar organization utilizes a digital twin to improve the effectiveness of their predicative maintenance systems This exemplar organization utilizes a digital asset on which services can be performed that provide value to an organization to improve the effectiveness of their predicative maintenance systems Within the Gemini Principles, there is also another definition to consider:
However, while this definition isn’t suitable for ISO as it wasn’t designed to meet these requirements, the inclusion of “realistic digital representation” might help enhance the ISO definition.
And there we have it. The ISO definition for digital twin is, technically speaking, a good example of an ISO definition. However, does the definition sufficiently capture the correct concepts and relationships outlined within the Gemini Principles? Following the criteria above, how would you define a digital twin?
DTHUb_NewbieGuide_May2020_(1).pdf
Being a relatively new concept in the infrastructure sectors, the most common question I get asked is ‘what is a digital twin?’
Indeed, the more people I speak to, the greater my belief that there is a better question: ‘What could a Digital Twin be?’
The real beauty of Digital Twin is that the market is emerging, the ‘what’ is still being explored by those who will own and utilise them, predominately owner/operators of UK infrastructure assets.
You can, of course, speak to many organisations who can articulate a vision for Digital Twins that are tailored to their goods and services, and in my experience, these are generally valid examples.
Here are a few examples:
[Engineering Provider] Enabling clients to adjust parameters and assess the impact of real world behaviours to understand how an asset will perform over its whole life. [Technology Provider] Allowing clients to integrate or simulate real world feedback to see how changing components within a system might affect overall risk profiles. [Contractor] Allowing digital production management to evolve design data through the build process, ensuring an asset is ready for use in its operational phases. [IT provider] Portraying a vision of enterprise systems being linked to real time information from sensors, leveraging internet of things capability. All of the above are great examples of Digital Twin capabilities when considering the Gemini Principles definition ‘a realistic digital representation of assets, processes or systems in the built or natural environment’. What excites me most, is what would happen if we considered integrating all these capabilities to create a fully integrated enterprise, to include supply chains and perhaps even citizens?
Think of what could be achieved, a design change could be tested against real time data in a simulation to assess how it would perform in operational life. Not only that, the link to enterprise systems would mean the impact on cost, risk, supply chain and other business metrics could also be tested. The possibilities are endless. Importantly many businesses already have the component pieces, they are however isolated rather than being integrated.
Taking this very broad, all-encompassing view, is tough for businesses to digest as they identify likely investment needs, work through value creation and understand risks. This is difficult when thinking about things on such a grand scale. This is why a good first step might be to develop a roadmap showing what a Digital Twin could be for your organisation. This could be done by underpinning a high-level vision and working backwards to prioritise what to do now, in the mid and long term to help you get there. A roadmap should not be considered a fixed plan and must evolve with your business as it changes, however it provides direction and initial guidance on where to focus investments and create early value.
By taking this approach, digital twins can become part of an organization’s integrated enterprise. By developing an integrated enterprise utilising the framework as set out in the ICE Project 13 (http://www.p13.org.uk/) , organisations will not constrain themselves by worrying too much about ‘what is a Digital Twin’, and can instead focus on what Digital Twin could be. This approach is being promoted by the water sector regulator OFWAT, termed ‘systems thinking’. Systems thinking encourages a big picture mindset, identifying the pieces of the puzzle to create that big enterprise picture and approaching each piece of the puzzle in a structured way, towards a common goal.
The next big step for an integrated enterprise is to think about federating information across multiple organisations to create a National Digital Twin. It is this global opportunity that we should all be excited about, through collaboration between government, academia and industry the UK can be a world leader in the evolution of the digital economy.
To achieve this, we need to think big, be prepared to fail, not hold back and work together to evolve UK infrastructure to be a world leading centre of excellence.
Kevin Reeves is the Director of Internet of Things and Digital Twin at Costain.
DTHUb_NewbieGuide_May2020_(1).pdf
A test will serve as an invaluable tool for educating and up-skilling, avoidingconfusion and set a direction for implementation. This is something particularly close to my heart as we’re currently (still) experiencing this in global BIM discussions. Whilst on the topic of BIM, the test could be a great way of identifying what a typical BIM process deliverable is and how a digital twin might differ. This is particularly pertinent as we’re currently observing digital twin negativity and the misconception that digital twins are ‘just BIM’.
Take a look at the attached image, a snapshot of a Twitter Poll... this may be just a small sample, but of 113 people on twitter who responded to this tweet by a Canadian colleague, just over HALF of them think digital twins are software vendors marketing vaporware - a product that doesn’t come to fruition. The other half are of the impression that digital twins are a ‘technology’. Clearly there’s work to be done...
Personally, I think we need a mutually agreed distinction to engage and involve a wider group of professionals from within our sector and outside of it to really progress and deliver the benefits outlined in The Gemini Principles.
Comments you’ve provided so far suggest that a test could be helpful, although some of you share the concern that the time taken to form a test may be better spent developing a digital twin. Other comments have highlighted the need to avoid being short-sighted in the ‘boundaries’ of a test. If we are to develop a test, it will need to be flexible enough to cater for edge cases and to evolve over time as technologies and possibilities become more easily achievable - i.e. when the goal posts move!
Do we need to define a baseline case, so that all proposed digital twins are measured against it? If so, what are the fundamentals?
For example, which of the following might be considered a digital twin:
• www.lightningmaps.com (near real-time data visualization of weather systems); • https://www.tidetimes.org.uk/ (log of expected highs and lows of a tidal system); and • www.googlemap.com (periodically updated traffic system with patterns and disruptions) Each of these are similar but constitute different fundamentals. LightningMapsuses weather station data, while TideTimes uses a database of pre-established tide peaks and throughs. Is the collection of (near) real-time data fundamental, or something that is only applicable to specific use case?
Once we have the fundamentals, which digital twins need to be tested? If we are ultimately aiming for a national digital twin, surely we need to test all of them to ensure compatibility and value if it is to be included/connected to it? If this is the case, then I’m talking myself into the notion that a simple yes/no or pass/fail will never be enough... We need to find a way to identify and celebrate the (positive) extremes, to encourage the development of borderline cases to become true digital twins and to seek new directions and measures of ‘what looks good’ as the sector integrates digital twins into its decision-making.
It looks like we have a LOT to discuss in the proposed workshop on the 17thNovember to explore why, what and how we should be measuring.
Outline agenda below, to be informed by the ongoing forum discussions.
The Why - Discussing the pros and cons of a digital twin test. Objectives & Activities for looking at intuitive tests for digital twins Summary of initial industry feedback. A Yes/No, Pass/Fail or a Sliding Scale? Existing 'test' examples that could be leveraged from other industries. Discussing what elements make up a digital twin. I hope you will continue the discussion on this thread, which will give us time to prepare the workshop materials and key discussion points and to do that, I have some questions to continue the discussion...
1. In YOUR role in either procuring, creating, maintaining or analysing/interacting with a digital twin, what should we be testing or measuring? Please let us know what your involvement (current or proposed) is and what we should be measuring/testing to help in that role. 2. What, in your opinion, makes a digital twin - real? Let’s keep this short, give me your top 5! 3. How do we best differentiate what we should typically deliver in a BIM process and a digital twin? Digital twins are a huge opportunity for bettering the entire built environment design, procurement, operation and provide tangible benefits to society. What therefore can we do to promote the relationship (and a distinct difference) between BIM and digital twins?
The workshop will take place on the 17th November from 14:00 – 16:00. Register on Eventbrite to receive joining instructions. See you there!
C
DTHUb_NewbieGuide_May2020_(1).pdf
Following the initial forum discussion querying the need for a digital twin ‘test’ and the subsequent post asking ‘what’ we should measure if a test is needed, we hosted a workshop to deep dive into the topic. With great interactivity and engagement with over 40 active contributors from across various roles in the sector, a few common themes surfaced which inspiringly, were echoed by a Digital Twin Fan Club event the following week.
After a brief introduction from the CDBB team, Dan Rossiter of BSI covered the meaning of the word ‘definition’ and ‘test’ before we dived into the workshop session where we asked several questions of the attendees. The themes covered the following topics:
Do we need a test for digital twins? If there is a test, how should it be ‘scored’? What makes a digital twin a ‘real’ digital twin? If there is a test, what would it measure? And then a quickfire yes/no round to determine if certain ‘things’ are digital twins. Mapping of those results on a banded scale.
Spoiler alert! The first topic garnered a resounding ‘yes’. Observations within the group raised concern over digital twins and their use being driven by technology companies rather than the approach we’d rather take which is by purpose-driven solutions (culture, process and technology) to solve current client challenges. With ‘twinwash’ marketing often reaching clients and the supply chain masses before it reaches those with the real experience and capabilities, we really are perilously close to repeating what BIM has been through already – and we’re still battling against that!
Scoring was a longer discussion that saw real industry value of a simple yes/no result, but through the workshop, it became evident that being able to see how one particular digital twin compared to another was perhaps a useful checklist for the ‘lesser’ version.
We were steering clear of defining ‘what’ a digital twin is, that work is being undertaken in other CDBB workstreams. What we wanted to unearth was, for each attendee, for their particular use case, what made a digital twin ‘real’… needless to say that this began the real-time versus right time discussion (also previously discussed here and here on the DTHub)! There were wide and varied responses about interfaces, connectedness, insights and prediction and these are summarized in the upcoming report.
The quickfire round was useful, for a few reasons. Firstly, attendees were required to answer using their gut instinct. Secondly because it demonstrated that there is a clear consensus on a few digital twin examples. Finally, it was useful to expand a little on each of the examples to explore where the differences of opinion lie. I should point out that the examples used in the quickfire round are all taken from marketing / forums / discussions that are happening out there in the built environment right now… these aren’t examples that we, the workshop facilitators, defined as ‘being’ digital twins.
The results are as per the attached image and you can clearly see where the common trends sit. The interesting examples for the overall discussion are the items with a split in opinion… clearly an indicator for the need for a test?
The last exercise for the attendees was to place these above examples and their own contributions onto a graded scale, from red (not a digital twin) through amber and to green (real digital twins and ‘unicorn’ digital twins!). An interesting and revealing exercise, especially when given the opportunity to move the indicators that others had placed.
If we’re looking to draw conclusions from the workshop, I’d suggest that the many great conversations over 1.5hrs could have easily lasted several weeks, mainly due to the ‘is it’ or isn’t it’ nature of the discussions. This leads me to observe that:
As an initial exploratory task to determine the industry’s appetite for a test, linked to an accurate definition, this has been a revealing and thought-provoking exercise and one that I’m keen to continue.
To that end: Do you agree with the quick-fire round? Are you adamant about a particular characteristic that a digital twin must have? Let’s ensure that the workshop is the beginning, not the end, to this discussion!
The DT Hub was launched at the end of March 2020 and now in August has grown to over 500 members. That’s over 500 people and organisations interested in developing digital twins across infrastructure asset owners, local authorities, architects, engineering consultants, construction companies, software developers, AI companies, big tech and more. We’re discussing how digital twins do mean different things to different people but what we all have in common is the need to share data. Connecting digital twins to reduce the level of carbon use in a city will only be possible if we can share data across digital twins.
That’s why behind all the really exciting digital twin developments lies a framework. An information management framework for organising, labelling and sorting data. An information management framework for setting standards for how we share data. Because if we don’t have that framework our digital twins will all speak different languages.
The approach to developing this framework is set out in the Pathway to the Information Management Framework (the technical document) and the summary. This approach is open for consultation and feedback until 31 August and we really encourage you to respond, even if it’s with a “we like it” or more importantly, if you want to provide some feedback that might impact the approach. Our ontologists are busy building the foundation data model because we need to get on with building the framework but that doesn’t mean it can’t be adapted or improved and we need your input to ensure we get the best version possible.
With the possibility of different types of information management frameworks emerging across the economy, our focus if very much on consensus and consultation to ensure we are able to share data in a secure, interoperable way. A good example to drive home the important of interoperability is the evolution of mobile phone technology, two different standards emerged, GSM and CDMA. GSM was driven largely by the political will of European states to have a standard mobile technology across Europe. CDMA was privately driven and proprietary, out of the States. Whilst each had their technical merits at different points in the evolution of mobile phone technology, eventually GSM became the most widely adopted technology. Interoperability in mobile phone technology is really important because people want to be able to use their phones wherever there is network coverage. Scale in networks is important where we all benefit from being able to interconnect. Imagine a different version of the internet where we couldn’t access public websites from certain computers?
Scale and quality of networks are really important where public benefit is involved. We all benefit from one high quality network rather than many small, inferior networks. In this way, getting the best input into developing the Information Management Framework is crucial. The Information Management Framework will lay the foundations for sharing data about infrastructure and the built environment globally as we ensure it emerges as the best set of standards. The foundation data model is currently being developed by a set of experts and whilst good theories are developed in the lab they need to be tested out in the open. The DT Hub provides a forum for testing. The motto of the DT Hub is “learn by doing, progress by sharing”. There is no definitive guide to Digital Twins as yet, I believe you are all co-developing it. We are all learning what is possible with digital twins and what we need to do to make them work. The National Digital Twin programme at the Centre for Digital Built Britain which is supported by the Department for Business, Energy and Industrial Strategy is open to your suggestions and input on developing the Information Management Framework. In order to develop the best set of standards for sharing data, we need the best input, so please respond!
Sarah Hayes is the Change Stream Lead of the National Digital Twin programme.