Modelling across the built and natural environment interface
Modelling across the built and natural environment interface: Conclusions from a CDBB interdisciplinary workshop
Author: Matthew White
The Centre for Digital Built Britain (CDBB) National Digital Twin Programme has recently published a research report titled “Modelling across the built and natural environment interface: Conclusions from an interdisciplinary workshop”. This research was enabled by the Construction Innovation Hub and brought together 12 experts from the built and natural environment modelling communities, to discuss what opportunities could arise from better integration of digital models across this sectoral divide.
The consensus was that sharing models across interdisciplinary silos provides a valuable opportunity to address some of the world’s most pressing problems and priorities. To enable this, the research concluded that the UK’s research, industry and policy bodies must focus on the following priorities, simultaneously and systematically:
- Make interconnected models accessible to stakeholders to drive better decisions, by making built and natural environment models visible early in the decision process.
- Bring communities together around a shared vision in order to frame better questions, as the basis for model integration.
- Develop a common approach / platform to enable better data and model sharing across disciplines, joined by shared architectures, and common standards for security and quality.
- Establish and share best practice at all scales, to support better local, regional and national decision-making.
We are embracing the findings from the research report, helping organisations across government, utilities, and transport sectors to make better decisions, based on better models. We do this by enabling good data quality, security-mindedness, and an information architecture.
As stated in the report, the built environment both impacts and relies on the natural environment in complex ways. Understanding this relationship better can lead us to make better decisions about how we manage both systems in balance with one another. Both systems must continue to provide services and opportunities for people and nature to flourish for generations to come, and integrated digital modelling has a huge role to play in the ability to make that happen.
How the 1Spatial Platform can help
The report refers to the need for better decisions, based on better models, which require better data. This includes good quality, security-mindedness and an information architecture that supports data from different disciplines being used together – known as interoperability.
Our 1Spatial Platform is a complete set of collaborative and integrated Location Master Data Management (LMDM) software components, which combines servers, portals, dashboards, SDKs, APIs, data connectors, business-focused applications and our patented 1Integrate rules engine.
The need for Data Quality
Data quality was mentioned by several participants as the key enabler to model integration, and the lack of a widespread culture and standards for data quality was seen as a barrier. 1Integrate (part of the 1Spatial Platform) can ensure data quality by validating and/or fixing data. We focus on the 6 data quality dimensions recommended by the Data Management Association UK (DAMA) to assess and measure data quality. These include:
- Accuracy: Does data reflect reality and how reality changes over time
- Completeness: Is all the data required for a particular use present? It may be that data fields are not 100% complete but is the critical data complete.
- Uniqueness: Is data unique or are their duplicate sets that could be combined?
- Consistency: Does data conflict with other values within a record or across different data sets. Consistent data allows data to be linked from multiple sources
- Timeliness: Is data available when it is expected and needed. How does data diminish over time
- Validity: Does data conform to an expected format, type or range
You can find out more about how to meet the DAMA data quality dimensions here and learn how 1Spatial ensure data quality in our recent blog.
The need for Security
Secure, ethical and resilient architectures for integration were listed among the technical considerations. If a platform is developed, it needs to be designed and managed with security-mindedness from the start. The 1Spatial Platform has been designed with security and specifically data security at the core.
1Integrate and 1Data Gateway undergo regular penetration testing, and our product teams work carefully to comply with ISO 9001 and Cyber Essentials Plus.
1Data Gateway and 1Integrate (part of the 1Spatial Platform) provides secure, self-service data validation, processing, and analytics, whilst our LMDM design principles encourage the simplification and minimisation of data handling, and the separation of concerns.
The need for Information Architecture
Participants agreed that robust information architectures, including metadata and ontologies, need to be developed and standardised to enable cross-sectoral integration of models. 1Spatial works with government, utilities and transport organisations to design and implement robust information architectures, including Spatial Data Infrastructures (SDIs). SDIS are fundamental to modelling across the built and natural environment interface.
1Spatial’s collaborative platform provides integrated software components, for managing, and accessing high quality data. Better decisions are based on better models, which require better data. 1Spatial look forward to being part of CDBB’s information management journey and helping organisations to focus on the priorities identified in this research report.
For further information about 1Spatial’s platform please get in touch.