The web has seen a huge growth in the amount of information available on all manner of topics. As the data has exploded however, it’s been increasingly challenging to make sense of it all as knowledge has become fragmented across an increasing number of sources.
There are thousands of articles published each day, and keeping on top of it can be challenging for even the most diligent of people. This results in potentially important insights passing us by.
Helping find the needle in the haystack
There have been various attempts to make this discovery process more scalable, with the likes of the Semantic Scholar and Konfer designed to make it easier to find the latest research.
These tools can go some way to help us connect the dots between various strands and identify previously unrecognized relationships.
Researchers at Oak Ridge National Laboratory have been working on the challenge for several years, with their latest effort being the Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI), which aims to provide researchers with a tool to discover the latest literature in their field.
“Humans’ limited bandwidth constrains the ability to reason with the vast amounts of available medical information,” the team say. “By design, ORiGAMI can reason with the knowledge of every published medical paper every time a clinical researcher uses the tool. This helps researchers find unexplored connections in the medical literature. By allowing computers to do what they do best, doctors can do better at answering health-related questions.”
The tool utilizes big data, graph computing and the Semantic Web to provide users with intelligent responses.
Automated curation
This is a particular challenge in areas such as medicine, where traditional search engines such as MEDLINE return thousands of results. It’s a level of information that even the most diligent will struggle to manage.
Whilst IBM’s Watson has famously taken on this challenge, there have also been projects such as Semantic MEDLINE that attempt to provide a visual display of the most relevant results in graph form.
“Semantic MEDLINE is kind of like having a research assistant who looks at a ton of articles and organizes them for you,” the team say.
To achieve this however requires a huge amount of computational grunt, and it has required the Apollo graph computer housed at ORNL to allow the system to achieve its potential.
From here, ORiGAMI was a natural next step, with the result being a free application that’s capable of returning detailed health insights in less than a second.
The future of research
The team believe that ORiGAMI has the potential to hugely increase the efficiency of medical research. The tool does however merely direct people to the right stuff. Whilst this is undoubtedly valuable, it does little to help make sense of the findings.
A project that might help with this is the Annotating All Knowledge project, which aims to add a conversation layer over the world’s knowledge platforms.
This will hopefully make it easier to add contextual awareness to a paper, and how it fits into the wider ecosystem. It will allow things like post-publish discussion and peer review to be placed in a single, logical location.
Check out the video below for more information about the project.
