We are pleased that Cognizone was a sponsor of the SEMANTiCS 2022 conference, which again this year has shown us that it is a true knowledge and sharing hub where ideas around Semantic technologies and AI are emulated.
That was a very special moment for us because we had the chance to announce the launch of our product Hanami.
If you stopped by our booth, you were able to participate in our live poll and give your opinion on “What would you like to see improved in the current Linked Data editors?”
The results are striking:
These results clearly mirror the enhancements the practitioners would like to see from vendors and suppliers and also reflect the main concerns that we have at Hanami.
How can we provide a tool to our users that can facilitate knowledge graph editing at multiple levels?
The generation and maintenance of knowledge graphs is a very time- and resource-consuming task; thus, we strongly believe that we need to automate most part of it.
There are many good starting points for automating the building of knowledge graphs, but maintenance remains an untapped area. Setting up tools to ensure data quality and at the same time making data editing easier are probably more complicated issues to tackle and are the strengths of Hanami: we support the automation of editing and maintenance tasks to build an enterprise knowledge graph more stable, reliable and flexible.
After all, this is a good analogy of the data management needs of today’s enterprises: making sure you don’t need to delete everything and start again, but working to move data sets to something more qualitative and reliable that everyone in a company can use with confidence. The main idea is to combine existing metadata with automation, intelligence and processing power and do everything we can to help organisations better manage and use data, even in overly complex data environments.
In the two most cited answers in our survey, we clearly consider collaboration to be the backbone of our application and the driver of the future of enterprise knowledge graph management. The collaboration will be an active process where everyone is equipped with the skills to improve the quality of published data, understand the data, communicate insights from that data and make more informed decisions with data.
To discover more about our approach, we invite you to download our eBook full of insights: Read the eBook
For those who wish to check our presentation, the slides are here: Read the slides