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Abstract

I have become "brutally honest" of late, at least according to one listener who heard my remarks during a recent whistle stop speaking tour of publishing conventions. This comment caught me a little off guard. Not that I haven't always been frank, but I do try never to be brutal. The truth, I guess, can be painful, even if the intention of the teller is simply objectivity. This paper is based on a "brutally honest" talk I have been giving to publishers, first, in February, to the Association of American Publishers' Professional and Scholarly Publishing Division, at which point I was calling the piece, "The Illusion of Free Information." It was this initial rendition that led to the invitation to publish something here. Since then I've been working on the talk. I gave a second version of it in March to the assembly of the American Society of Information Dissemination Centers, where I called it, "When Sectors Clash: Public Access vs. Private Interest." And, most recently, I gave yet a third version of it to the governing board of the American Institute of Physics. This time I called it: "The Future of Society Publishing." The notion of free information, our government's proper role in distributing free information, and the future of scholarly publishing in a world of free information . . . these are the issues that are floating around in my head. My goal here is to tell you where my thinking is only at this moment, for I reserve the right to continue thinking and developing new permutations on this mentally challenging theme.

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Abstract

Philosophy "done informationally" has been around a long time, but PI as a discipline is quite new. PI takes age-old philosophical debates and engages them with up-to-the minute conceptual issues generated by our ever-changing, information-laden world. This alters the philosophical debates, and makes them interesting to many more people - including many philosophically-minded people who aren't subscribing philosophers. We, the authors, are young researchers who think of our work as part of PI, taking this engaged approach. We're excited by it and want to teach it. Students are excited by it and want to study it. Writing a traditional textbook takes a while, and PI is moving quickly. A traditional textbook doesn't seem like the right approach for the philosophy of the information age. So we got together to take a new approach, team-writing this electronic text to make it available more rapidly and openly.

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Abstract

Consider a sentence such as "the current price of tea in China is 35 cents per pound." In a library with millions of books we might find many statements of the above form that we could capture today with relatively simple rules: rather than pursuing every variation of a statement, programs can wait, like predators at a water hole, for their informational prey to reappear in a standard linguistic pattern. We can make inferences from sentences such as "NAME1 born at NAME2 in DATE" that NAME more likely than not represents a person and NAME a place and then convert the statement into a proposition about a person born at a given place and time. The changing price of tea in China, pedestrian birth and death dates, or other basic statements may not be truth and beauty in the Phaedrus, but a digital library that could plot the prices of various commodities in different markets over time, plot the various lifetimes of individuals, or extract and classify many events would be very useful. Services such as the Syllabus Finder1 and H-Bot2 (which Dan Cohen describes elsewhere in this issue of D-Lib) represent examples of information extraction already in use. H-Bot, in particular, builds on our evolving ability to extract information from very large corpora such as the billions of web pages available through the Google API. Aside from identifying higher order statements, however, users also want to search and browse named entities: they want to read about "C. P. E. Bach" rather than his father "Johann Sebastian" or about "Cambridge, Maryland", without hearing about "Cambridge, Massachusetts", Cambridge in the UK or any of the other Cambridges scattered around the world. Named entity identification is a well-established area with an ongoing literature. The Natural Language Processing Research Group at the University of Sheffield has developed its open source Generalized Architecture for Text Engineering (GATE) for years, while IBM's Unstructured Information Analysis and Search (UIMA) is "available as open source software to provide a common foundation for industry and academia." Powerful tools are thus freely available and more demanding users can draw upon published literature to develop their own systems. Major search engines such as Google and Yahoo also integrate increasingly sophisticated tools to categorize and identify places. The software resources are rich and expanding. The reference works on which these systems depend, however, are ill-suited for historical analysis. First, simple gazetteers and similar authority lists quickly grow too big for useful information extraction. They provide us with potential entities against which to match textual references, but existing electronic reference works assume that human readers can use their knowledge of geography and of the immediate context to pick the right Boston from the Bostons in the Getty Thesaurus of Geographic Names (TGN), but, with the crucial exception of geographic location, the TGN records do not provide any machine readable clues: we cannot tell which Bostons are large or small. If we are analyzing a document published in 1818, we cannot filter out those places that did not yet exist or that had different names: "Jefferson Davis" is not the name of a parish in Louisiana (tgn,2000880) or a county in Mississippi (tgn,2001118) until after the Civil War.

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Date

23. 1.2022 10:22:18

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