ISI AI Seminar: Introducing paradigms as a viable structural guide for biomedical knowledge engineering

I gave a slightly more technical version of the talk presented at Google for my colleagues at ISI to describe the latest work going on in my group.

Video: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=528b06784cd24ce4843105a61bddf0c81d

Following Thomas Kuhn's seminal 1962 book in which he introduced the notion of scientific paradigms, we here describe a computational methodology that leverages that concept in a concrete formulation. I describe this approach partially as a methodology for framing and scoping the knowledge representation and analysis work necessary to build tools to serve a specific community. However this approach also has technical implications that are relevant to semantic web representations, the use of workflows and reasoning and the way that we derive content from existing scientific artefacts. We will explore this viewpoint in the context of a well defined domain problem (Biomarker studies of neurodegenerative diseases) with the strategic intent of developing a practical, scoped view of biomarker data that could serve as the basis of corollary work within AI computer science groups.

Google Tech Talk: Organizing the world’s scientific knowledge to make it universally accessible and powerful: building the breakthrough machine.

I gave a talk at Google Los Angeles on 04/30/2013 about my work. Here is a video link and a short abstract about the presentation.

YouTube Link: http://www.youtube.com/watch?v=DU5HRck4bn4

Abstract: Not all information is created equal. Accurate, innovative scientific knowledge generally has an enormous impact on humanity. It is the source of our ability to make predictions about our environment. It is the source of new technology (with all its attendent consequences, both positive and negative). It is also a continuous source of wonder and fascination. In general, the value and power of scientific knowledge is not reflected in the scale and structure of the information infrastructure used to house, store and share this knowledge. Many scientists use spreadsheets as the most sophisticated data management tool and only publish their data as PDF files in the literature. In this high-level talk, we describe a powerful, new knowledge engineering framework for describing scientific observations within a broader strategic model of the scientific process. We describe general open-source tools for scientists to model and manage their data in an attempt to accelerate discovery. Using examples focussed on the high-value challenge problem: finding a cure for Parkinson's Disease, we present a high-level strategic approach that is both in-keeping with Google's vision and values and could also provide a viable new research that would benefit from Google's massively scalable technology. Ultimately, we present an informatics research initiative for the 21st century: 'Building a Breakthrough Machine".

Building a Breakthrough Machine: a Historical Introduction

If we go back one thousand years, to 1013, and ask the question, “Why is the world different now from how it was then?” then we might cite military campaigns, political revolutions, evolving economic models or advances in technology. We might highlight the influence of key individuals: explorers, inventors, thinkers, industrialists and scientists. The common factor that underlies the world’s progression from medieval life in 1013 to life in the modern world is discovery.

Scientific breakthroughs are a disproportionately impactful subtype of discovery. Our understanding of phenomena like chemistry, molecules, DNA, vaccines, neurons, electricity, electromagnetism, the movement of planets, quantum mechanics, global warming or even cryptography were founded on ‘eureka’ moments. Scientists synthesize how they think phenomena work into concrete experimental or theoretical investigations that gave new predictive insight into what was actually going on. Developing breakthroughs of this kind require a combination of creativity and careful, rigorous scientific work that are the hallmark of exceptional talented practitioners. As yet, the only effective way to develop scientific discoveries is to find and train exceptional people, to provide them with laboratories and analysis tools, to foster their intercommunication and competition and try to pick out significant findings as they occur.

On Dec 23rd 1999, the Economist magazine published a review of the most important inventions of the last thousand years. Notably, they chose Gutenberg’s printing press as the most influential invention over that period. This machine allowed the generation, reproduction and dissemination of knowledge on an industrial scale. It toppled governments. It educated the masses. It revolutionized trade. Similarly, the invention and rapid development of electronic information technology over the last 70 years provides us with an astonishing array of computational tools that that have so far transformed the way we work, live, socialize, think and play. This technology allows us to use information easily and powerfully in ways hitherto unimagined a few short years ago.

Although informatics tools certainly facilitates science, the act of discovery itself still remains somewhat ephemeral and mysterious. The underlying synthesis of knowledge required to execute such discoveries remains hidden in the minds of a small number of experts. Perhaps we can develop knowledge engineering methodologies and techniques to understand, reproduce and automate the information-driven processes of scientific understanding and discovery. Perhaps, we can build machines that make advanced scientific reasoning as easy for people as reading and writing had become in the years after Gutenberg’s printing press.

In this blog, I will ask the question, “What will it take to develop a breakthrough machine?” and attempt to come up with some answers based on my group’s efforts as well as reviewing other work being done in the field. This blog is also intended to act as a challenge and an invitation to the community to discuss, argue and contribute to the discussion.