We all know what “Knowledge” is, but to ensure we are on the same page, it is defined by the Oxford English Dictionary as
(i) expertise, and skills acquired by a person through experience or education; the theoretical or practical understanding of a subject;
(ii) what is known in a particular field or in total; facts and information; or
(iii) be absolutely certain or sure about something.
Of course, we can also sum it all up using Plato’s formulation of knowledge as “justified true belief.” So what is “Meta-Knowledge”? Well, think of it as knowledge about knowledge. To clarify, let me run an example by you, Mr Smith lives at No1 High Street – thats ‘data’. I can also step up a level and define the attributes of that data, as Name and Address – thats called “meta-data”, or to put it more simply, its data that describes the data. So Meta-Knowledge is simply knowledge that is knowledge about knowledge.
So why am I babbling on about all this? Well, because the University of Chicago has issued a press-release on the topic that starts out like this …
The Internet has become not only a tool for disseminating knowledge through scientific publications, but it also has the potential to shape scientific research through expanding the field of metaknowledge—the study of knowledge itself.
The new possibilities for metaknowledge include developing a better understanding of science’s social context and the biases that can affect research findings and choices of research topics
Huh! … but we have had the concept for some time, so what is actually new? Well, they go on to explain, and give some interesting examples …
An important new tool for metaknowledge researchers seeking previously hidden connections is natural language processing, one of the rapidly emerging fields of artificial intelligence. NLP permits machine reading, information extraction and automatic summarization.
Researchers at Google used computational content analysis to identify the emergence of influenza epidemics by identifying and tracking related Google searches. The process was faster than other techniques used by public health officials. These content analysis techniques complement the statistical techniques of meta-analysis, which typically incorporate data from many different studies in an effort to draw a larger conclusion about a research question, such as the influence of class size on student achievement.
For scientific research, meta-analysis can trace the connections between data and conclusions in ways that might not otherwise be noticed. For example, the availability of samples from the Southern Hemisphere related to continental drift has influenced the way in which geologists have made conclusions about plate tectonics.
Metaknowledge also has unveiled the possibility of “ghost theories”—implicit assumptions that may undergird scientific conclusions, even when researchers do not acknowledge them. For example, psychologists frequently use college students as research subjects and accordingly publish papers based on the behavior of a group that may or may not be typical of the entire population. Scholars using traditional metaknowledge techniques found that 67 percent of the papers published in the Journal of Personality and Social Behavior were based on studies of undergraduates. The use of computation could accelerate and widen the discovery of such ghost theories.
They also point out the potential here ….
Entrenched scientific ideas can develop when studies repeatedly find conclusions that support previous claims by well-known scholars and also when students of distinguished researchers go on to do their own work, which also reinforces previous claims. Both of those trends can be uncovered by scholars working in metaknowledge, Evans and Foster said.
Metaknowledge also helps scholars understand the role funding plays in research. “There is evidence from metaknowledge that embedding research in the private or public sector modulates its path,” they write. “Company projects tend to eschew dogma in an impatient hunt for commercial breakthroughs, leading to rapid but unsystematic accumulation of knowledge, whereas public research focuses on the careful accumulation of consistent results.”
The promise of metaknowedge is its capacity to steer researchers to new fields, they said.
“Metaknowledge could inform individual strategies about research investment, pointing out overgrazed fields where herding leads to diminishing returns as well as lush range where premature certainty has halted promising investigation,” Evans and Foster said.
You can read the full press-release here, but please never forget, that is just a press release that points you towards the actual science, The article in question is entitled, “Metaknowledge“, and was published in the Feb 11 Issue of Science.
I’ve blogged it here simply because it hit my “Ooooh that’s interesting” button, but that perhaps is only a reflection of my own personal interests, and nothing more. However you must admit that the computational production and consumption of metaknowledge does offer some interesting potential for the leveraging of scientific knowledge and the advancement of science.