Quoting Eric Lease Morgan <emorgan_at_ND.EDU>:
>
> In the context of my previous message, there are two types of data:
> 1) quantitative, and 2) qualitative. The former is applicable to
> mathematical processes. The later is not.
But you can quantify what you call qualitative data, that is, data
that is not numeric. You can count anything, as the applications that
are making use of full text are doing. You can make "more related to"
calculations even using words ("this word is more related to another
word than that word" or "A has a greater relationship to B than C has
a relation to B"). I'm not sure why you would limit yourself to
numerical data, rather than countable data. Once you count, you turn
your data into quantity. Based on the nature of our data, I think
that's where we'll get bang for our computational buck.
kc
>
> For example, dates can greater or less than other dates. Dates can
> be averaged. Dates can be graphed. The closest thing we have to
> quantitative information in our bibliographic records are dates and
> number of pages. The later -- qualitative data -- is not applicable
> to mathematics. Authors. Titles. Subjects. Notes. Yes, a person can
> add and subtract the sum of all author names but such information
> describes the collection, not the works themselves. The balance of
> data in our bibliographic data is administrative in nature. ISSN.
> ISBN. Control numbers. Call numbers. Etc. This data does little to
> assist the reader.
>
> The situation does not have to be so unbalanced. If we insisted on
> full text, then we could include additional quantitative information
> in our bibliographic records. The best example is number of words.
> If a library knew how long each book was in terms of number of
> words, then a library could tell a patron, "This book is longer than
> most," or "This book is very short." Given full text, libraries
> could benchmark things like grade levels and readability scores.
> Libraries could then offer interfaces such as, "Here are a number of
> short books for high school students on the topic of astronomy
> written (not published) in the the 1800s, and these have been read a
> significant number of times."
>
> Quantitative information lends itself to a greater degree of
> objective interpretation and comparison. It lends itself to
> graphing, charting, and visualization. Illustrations based on
> numbers are more efficient than pure qualitative information -- "A
> picture is worth a thousand words."
>
> Getting to this point is an incremental process:
>
> 1) dump all our bibliographic records to file
> 2) read a record
> 3) find a digital version on the 'Net
> 4) mirror the digital version locally
> 5) analyze the digital version to extract quantitative information
> 6) update the record
> 7) go to Step #2 for all records
> 7) re-index
> 8) provide additional services and interfaces to the index as well
> as the item
>
> We can begin with our books. The next step can take in open access
> journals. The step after that can include blogs and other open
> content apropos to our collections.
>
> Our profession needs to get with the program. We are not meeting
> patron expectations. The services of librarians are truly noble and
> laudable, but since there are so many institutions who are willing
> to provide similar services, these services are no longer seen as
> public good necessarily supported by a government or over-arching
> institution. Much of the profession will fade unless we re-tool
> ourselves. Making our data easier to use -- putting it in a form
> usable by people outside our club -- is one way to accomplish this
> goal. Describing things quantitatively is a particular example.
>
> --
> Eric Lease Morgan
> University of Notre Dame
>
> "Take the Great Books Survey -- http://bit.ly/auPD9Q"
>
--
Karen Coyle
kcoyle@kcoyle.net http://kcoyle.net
ph: 1-510-540-7596
m: 1-510-435-8234
skype: kcoylenet
Received on Tue Dec 21 2010 - 13:57:28 EST