How does the system work
being edited by PH sep 2024
The CCRP is a unique centralised network for Open Data Databases/Visualisation Platforms, on Building Stocks, moderated by academia. The CCRP's GitHub repository contains a set of tools specifically designed and managed to drive open data and free knowledge exchange on stocks to support global cooperation and collaborative research to advance UN SGS, and to support a permanent low system that maintains, and is built , in line with CCRP values and protocols. These are best summarised using Matrix.org's clear and succinct list of key values for decentralised, to which the CCRP also works. These are:
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Supporting the whole long-term ecosystem rather than individual stakeholder gain. -
Openness rather than proprietary lock-in. -
Interoperability rather than fragmentation. -
Cross-platform rather than platform-specific. -
Collaboration rather than competition. -
Accessibility rather than elitism. -
Transparency rather than stealth. -
Empathy rather than contrariness. -
Pragmatism rather than perfection. -
Proof rather than conjecture.
We are increasingly looking at supplementing CCRP protocols with Matrix protocols Matrix.org below. Matrix is with Professor John Crowcroft at University of Cambridge. The current plan is to use Matrix values as a third stage filter (in addition to academic affiliation and research expertise) for new academic researchers interested in becoming involved, and to assess the extent to which CCRP protocols could be improved.
The CCRP's international network comprises of academic institutions that oversee Colouring Cities open data visualisation platforms/open databases which provide open spatial data on national building stocks. The research programme is only open to academic researchers as this is a research led project where trust is paramount. The is particularly important as all code and data and methods are released under open licences and are accessible to all. There are are no formal agreements between CCRP Partners however all partner institutions must provide proof of academic status, and agree to CCRP protocols in addition to already meeting their own academic protocols to enable trusted network development. Academic emails are also required.
A critical feature of CCRP system design is not just research-led but that it is developed and led from the bottom up by academic researchers with common values and relevant expertise.
Creating a like minded community within academia, in addition to a decentralised, trusted academic network is seen as critical to the development of sustainable, resilient foundations that facilitate work for the collective good and not for purely personal gain. The aim is to address the culture of competitiveness and insecurity in academia through demonstrating the benefits of open knowledge and data exchange e.g voluntary collaborative working across countries reduces time spent applying for grants and expertise that be provided free by other countries and reduces multiple reinventions of the wheel. Co-development and sharing of large scale datasets and other resources within and across countries also allow researchers to solve problems faster rather than wasting time applying for money to buy data and expertise in.
The CCRP network is currently overseen by The Alan Turing Institute in London. However the aim is for oversight to move, over the next 18 months, to a steering group on which representatives from academic institutions interested in voluntarily leading CCRP Global Hubs are represented.
The key
CCRP databases are designed to capture, collate, structure, verify, visualise and release standardised open datasets on the physical characteristics, performance and dynamic behaviour of buildings and typologies, at building level. Standardisation is critical to enable national datasets to be compared and combined across countries, using AI, ML and other computational approaches to rapidly accelerate the move net zero and to help meet UN SDG goals.
CCRP open-source core code allows academic institutions to quickly integrate join easily collect over 100 classes of standardised data, identified by researches as being necessary to support specific SDGs. Data classes were initially selected at UCL/Turing based on consultation with UK researchers but as well as being able to produce open source code for new data classes relevant to each country, or region/locality, provided that code are made available for others to use, and data collected has been assessed against CCRP data collection protocols.
add programming languages- add links to any detailed documentation in codebase