Matthew West
Forum Replies Created
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On 29/03/2022 at 10:53, Lawrence Chapman said:
Is the work on the information management framework going to align with IFC ISO 16739?
The IFCs are one of many Industry Data Models that we need to take account of. An initial survey can be found here:
The challenge is that these industry data models are incompatible with each other making data difficult to share across industries and sectors.
It is the aim of the National Digital Twin programme to specifically enable sharing of data among digital twins across sectors to enable a system of systems approach to managing national infrastructure. Therefore the IMF sets out to develop a Foundation Data Model and Reference Data Library that is able to support data across multiple industry data models. We would expect to work closely with the developers and users of various Industry Data Models and Reference Data Libraries to ensure that the underlying data requirements they express are supported by the IMF. We hope this process will also help to highlight how individual Industry Data Models can be improved to make them directly more compatible with each other.
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Data Naturally flows through the lifecycle, through the supply chain, and upwards through levels of management and control.
On 23/11/2021 at 10:47, Paul said:
data gathering can be parasitic, symbiotic or slave
I don’t understand what you mean by this. Could you explain a bit please?
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On 15/07/2021 at 10:02, Anne GUINARD said:
Hello @Al_and @Matthew, further to the presentation at the Gemini call on the 06/07, a question was asked about how the proposed approach to identify information requirements fits with existing approaches / standards. It would be great to hear your thoughts on this.
Hi @Anne I am not aware of any existing standards to identify information requirements systematically (but there are lots of standards, so I might have missed one). Current practice is generally to ask users what their information requirements are. This can be hit and miss because users will tend to focus on what is an issue at the moment, and perhaps forget what works well and does not cause a problem. This is good for the consultant because if information requirements are missed, then it is the users fault for not telling the consultant what they were.
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On 15/07/2021 at 10:07, HenryFT said:
Information Requirements are clearly key to unlocking value (of all kinds)in the lifecycle of assets. @Al_ and @Matthew I think the spatiotemporal approach in the space time diagram is a great idea.Â
How do you think we can trace value but specifically for this question the return on investment from Information Requirements development? How important do you think it is to do that?
@HenryFTÂ Yes, having information you do not need is a cost without benefit, and not having information you do need means a higher risk of mistakes or exposure to legal consequences from not having the information.
When you look at the benefits  these start with the converse of the costs of poor quality information.
1.      You will be able to automate deterministic processes (the boring ones) because relevant information is held as data.
2.      You will just be able to use the information provided to you, rather than having to fix it up, condition, or wrangle the data before you can use it.
3.      The risk of making mistakes will be reduced because you had the information you needed to take the right decision when you needed it.
4.    In addition to the elimination of negatives, which all go straight to the bottom line by improving productivity, there are some purely positive benefits of good information management (see Figure 2).
5.      You will have greater agility because rather than responding to changes in circumstances, you will be able to anticipate them and pivot to take advantage of them rather than being overwhelmed by them.
6.      You will have better insights into your operations and assets and this will enable innovation that comes from being able to spot new opportunities.
7.      You have the confidence that comes from knowing you are in good shape, rather than hoping you are.
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On 15/07/2021 at 10:02, Catherine Condie said:
Would it be possible for you to explain how the proposed approach to capture information requirements fit with other components of the Information Management Framework (in particular, the Foundation Data Model and the Reference Data Library…)?
The requirements that you identify are input to the ontological analysis process (the thin slice process) that we will be using to extend the Foundation Data Model and Reference Data Library.
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On 23/12/2020 at 10:19, Ian Cornwell said:
I thought of the NDT and in particular the top-level ontology analysis when I received an invitation today to submit to:
Special Issue “Data and Metadata Management with Semantic Technologies” to be published in the journal Information (http://www.mdpi.com/journal/information/, ISSN 2078-2489).
Topics of interest include but are not limited to:
- Approaches to publish, harmonize, and consume (meta)data;
- Ontologies, metadata vocabularies, and standardization;Â
- In-use cases and lessons learned managing (meta)data in industrial and domain-specific applications (e.g., in relation to cultural heritage, e-government, education, environmental, health and medical data, among others).
The manuscript submission deadline is 15 September 2021. For more details please visit the Special Issue website:Â
https://www.mdpi.com/journal/information/special_issues/Data_Semant_Technol
Thanks for this Ian. We’ve taken a look at it, and this is clearly a SemWeb publication, and at the moment most of the work we are doing is in the Logic/Philosophical Ontology area, and other work in the Integration Architecture is not far enough advanced given the considerable effort involved in putting together a full academic paper. Perhaps next year.
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Noted. We’ve added this to our list to investigate in the New Year for extending the Top Level Ontologies, and/or Industry Data Models.
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Do you mean “Where are they?” in terms of progress, or how do they meet? I’ll answer both.
The Pathway document https://digitaltwinhub.co.uk/gemini-commons/informatioon-management-framework/Â sets out the work being done by the IMF team, including the TLO (Top Level Ontology)Â part of the FDM (Foundation Data Model).
The Pathway Document was published in May, and the Technical Team (also known as the Rat Pack) has been working on what it sets out since then. So far, they have published a Survey of Top Level Ontologies, and a Survey of Industry Data Models as source material for their work developing a Foundation Data Model and Reference Data Library.
https://digitaltwinhub.co.uk/gemini-commons/imf-technical-documents/
Work is also progressing in developing the Top Level Ontology for the Foundation Data Model. An early deliverable from this is due around Christmas for publication after Christmas.
For those interested in keeping up to date with and contributing to /reviewing the work being done, early visibility of work is made to a Google Group: UK NDT FDM. Ask me if you wish to join the group.
If that has not answered your question, please let me know.
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In the NDT programme we are taking a very broad view of what a Digital Twin might be. This is because we do not want to find ourselves in the position of being faced with a valuable opportunity and having to say “You can’t do that here because that does not meet our definition of a Digital Twin”. I think that would be absurd. So I work off a Digital Twin being a useful collection of data about something, which might be an asset or a process (or something else).
That is not to say that there are not some particular types of Digital Twin that are more tightly defined. For example, a Connected Digital Twin being one where there is measurement of the Physical Twin and active feedback from the Digital Twin to effect change in the Physical Twin. I think it makes a lot of sense to identify useful types of Digital Twin like that.
