Knowledge Graphs have a real potential to become highly valuable, topical and relevant. If only we can get them prised out of the engineer, data scientists, or software experts hands.
We simply should so we can get this concept fully out into the real world, that of applying as solutions to real client problems, it would really help. I get tired of hearing about “use cases”, where concepts like KG often get caught up in, that never-ending validation.
Is this validation simply because it does not work, it is too much hard work delivering the promise within the concept? Or the approach has too much complexity around it and needs massive resources to undertake?
KG needs a real resource momentum and a determination to break through uncertainty. Its huge value should drive it, and caution should be modified and lets go out and validate it, in the real world.
If any of these “constraints” are the case, then we do need to “hack this” differently, as Knowledge Graphs has what I see an incredible potential, as an application solution that should be deemed as far too important to keep under wraps. We need to instill a sense of urgency into this. Why, well read on.
Here I want to give a deeper explanation of knowledge graphs- a ‘potted’ history and future view. So, my attempt here is to give Knowledge Graphs a more ”layman” context so we can begin to see how this “Knowledge Graph” concept can become really important to recognize, support and apply in our lives.
It will equally become a significant industrial application as well, as increasingly be part of our everyday working life in related searches as it is today by our personal use of Google or other search engines that have Knowledge Graphs increasingly sitting behind them. It might become the next big “buzz”, I recently heard being as topical as “Artifical Intelligence” as a prediction for use in an industrial application. As big a buzz- wow.
It is once we make all the connects in the knowledge that is out there, waiting to form new relationships, we unleash our connected understanding in completely new ways.
Knowledge Graphs help us to form essential context and that has been often missing or simply the poor cousin to content. Context is king, not content! Continue reading