Semantic knowledge graphs to help changemakers make an impact
Philippe Höij in Semantic Knowledge Graphs
How do you drive intentional change, affecting the way people think and do, on a global scale? This is a question we have been exploring together with our global enterprise clients for a long time.
Based on our experiences, and with the knowledge and insights learned as part of that work, we build a knowledge platform to help changemakers harness the power of knowledge collaboration, semantic knowledge graphs and data mesh to drive real, global, and sustainable change, in society and in enterprises.
Together is our best shot
Real change is most often complex, disorderly, and messy. It does not happen in a predictable way, as we cannot know exactly how things will unfold. Planning meticulously, collaborating on sought outcomes and ensure lots of practice and experiments; does however dramatically increase the odds of positive intentional change to happen. Connecting and driving actions towards a “burning why” means we not only can do, but we also get the willingness to do.
Courage, community, and collective are our best shots through these greatest challenges. Individualism is inadequate for planetary forces like climate change, biodiversity challenges, and global pandemics. No less societal forces like healthcare, economic equity, and racism. If you want to go fast, go alone—if you want to go far, go together.
Only together, as a collective, can we confront the global challenges ahead and steer them in a better direction. With shared thought, and collective intention and action.
Intentional change and outcomes-based thinking
In 2021 we founded a grants-funded project, AIDITTO. We did so together with a team of visionaries, coders and societal needs owners. Our initiative was a response to the pandemic where we tried out a few of the ideas we now continue to develop here.
Additionally, as a part of our initiative, we conducted research on how to build boundary objects. Systems that would allow people to collaborate on knowledge, that draws upon previous work on knowledge base platform worked on for several clients. We realized that what we were looking for was a broader thing than we had initially imagined.
DFRNT Zebra will be one of many tools
With a data mesh, data integrations do not have to work through a specific vendor, as in traditional scenarios. Other applications and services can work directly with TerminusCMS and continue where we left off.
We believe that what is essential for good knowledge work is to be able to express knowledge freely. Thinking about complexity requires a free form approach to the data we meet. Knowledge will need to be expressed and connected in unforeseen and unexpected ways at a moment’s notice. Such as when we realize that our models are inaccurate and need to change. It should be possible to mix, remix and connect new knowledge with any existing knowledge. Innovative ideas should be possible to be branched out and tried.
The ability to get started expressing knowledge graphs earlier in the process, is why we believe a data-orientated whiteboard approach for structured data is essential. To make connected knowledge accessible and possible to interact with for those that are part of an initiative, and beyond, in visual graph collaboration, is how we believe a tool like ours we build will bring value. We do though have some work ahead of us to make the full datalog foundation of TerminusDB and TerminusCMS SaaS shine as brightly as it deserves.
Where to put strategic and tactical knowledge
This reasoning takes us to a key question: is there is a better way to handle emerging structured data and knowledge when collaborating in initiatives? A better way than to do so in tabular spreadsheets, bespoke and siloed application suites, hard-to-evolve relational database schemas and other takes on tabular data?
We believe so, and we believe that strategic and tactical knowledge needs to be treated better than it is: even slideware have some real limitations in how well they work for actual and good knowledge collaboration.
The name of our platform, Zebra, is a word play on the Swedish words Se and Bra: Se translates to “see”, and Bra to “good”. To see things clearly and visualize how the dots are connected. To clarify the direction of the outcomes we seek, and importantly connect them to a burning why; through sought effects/results of the initiatives, described in your knowledge graph. A simple example visualization of connected data in Zebra for the SDGs that we will come back to in a future post:
Conclusion
We enable knowledge sharing in environments characterized by volatility, uncertainty, complexity, and ambiguity (VUCA), where we know semantic knowledge graphs can be used effectively for sensemaking. The ability to hold multiple perspectives/branches, time travel, perform thought experiments and simulate scenarios are all prerequisites for an ability to express and explore knowledge accurately.
The DFRNT Zebra platform (beta waiting list sign-up) is about having an easy-to-use place to capture and inter-connect emerging knowledge about the direction and content of an initiative. It comes out of solving our own needs for driving change, collaborating on knowledge, modelling information and describing cause-and-effect relationships in complex client initiatives.
Our belief is that semantic knowledge graphs should be used more widely than today in this space.
