Aristotle (384-322 BCE) was remarkable for the depth and scope of his knowledge, which included mastery of a wide range of topics from medicine and philosophy to physics and biology. Aristotle not only had command over a significant portion of the world's knowledge, but he was also able to explain this knowledge to others, most famously, though briefly, to Alexander the Great.
Today, the knowledge available to humankind is so extensive that it is not possible for a single person to assimilate it all. This is forcing us to become much more specialized, further narrowing our worldview and making interdisciplinary collaboration increasingly difficult. Thus, researchers in one narrow field may be completely unaware of relevant progress being made in other neighboring disciplines. Even within a single discipline, researchers often find themselves drowning in new results. MEDLINE, (1) for example, is an archive of 4,600 medical publications in 30 languages, containing over 12 million publications, with 2,000 added daily.
Making the full range of scientific knowledge accessible and intelligible might involve anything from simply retrieving facts to answering a complex set of interdependent questions and providing appropriate justifications for those answers. Retrieval of simple facts might be achieved by information-extraction systems searching and extracting information from a large corpus of text, such as Voorheese (2003). But aside from the simplicity of the types of questions such advanced retrieval systems are designed to answer, they are only capable of retrieving "answers"--and justifications for those answers--that already exist in the corpus. Knowledge-based question-answering systems, by contrast, though generally more computationally intense, are capable of generating answers and appropriate justifications and explanations that are not found in texts. This capability may be the only way to bridge some interdisciplinary gaps where little or no documentation currently exists.
Project Halo is a multistaged effort aimed at creating Digital Aristotle (DA), an application encompassing much of the world's scientific knowledge and capable of answering novel questions through advanced problem solving. DA will act both as a tutor capable of instructing students in the sciences and as a research assistant with broad interdisciplinary skills, able to help scientists in their work. The final DA will differ from classical expert systems in four important ways.
First, in speed and ease of knowledge formulation. Classical expert systems required years to perfect and highly skilled knowledge engineers to craft them; Digital Aristotle will provide tools to facilitate rapid knowledge formulation by domain experts with little or no help from knowledge engineers.
Second, in coverage. Classical expert systems were narrowly focused on the single topic for which they were specifically designed; DA will over time encompass much of the world's scientific knowledge.
Third, in reasoning techniques. Classical expert systems mostly employed a single inference technology; DA will employ multiple technologies and problem solving methods.
Fourth, in explanations. Classical expert systems produced explanations derived directly from inference proof trees; DA will produce concise explanations, appropriate to the domain and the user's level of expertise.
Adoption by communities of subject matter experts of the Project Halo tools and methodologies is critical to the success of DA. These tools will empower scientists and educators to build the peer-reviewed, machine-processable knowledge that will form the foundation for Digital Aristotle.
The Halo Pilot
The pilot phase of Project Halo was a six-month effort to set the stage for a long-term research and development effort aimed at creating Digital Aristotle. The primary objective was to evaluate the state of the art in applied KR&R systems. …