Archive for the ‘Demographics’ Category

New: Library of Congress Demographic Group Terms (LCDGT)

Wednesday, May 13th, 2015

From an email:

As part of its ongoing effort to provide effective access to library materials, the Library of Congress is developing a new vocabulary, entitled Library of Congress Demographic Group Terms (LCDGT). This vocabulary will be used to describe the creators of, and contributors to, resources, and also the intended audience of resources. It will be created and maintained by the Policy and Standards Division, and be distinct from the other vocabularies that are maintained by that division: Library of Congress Subject Headings (LCSH), Library of Congress Genre/Form Terms for Library and Archival Materials (LCGFT), and the Library of Congress Medium of Performance Thesaurus for Music (LCMPT).

A general rationale for the development of LCDGT, information about the pilot vocabulary, and a link to the Tentative List of terms in the pilot may be found on LC’s Acquisitions and Bibliographic Access website at

The Policy and Standards Division is accepting comments on the pilot vocabulary and the principles guiding its development through June 5, 2015. Comments may be sent to Janis L. Young at

A follow-up question to this post asked:

Is there a list of the codes used in field 072 in these lists? Some I can figure out, but it would be nice to see a list of the categories you’re using.

The list in question is: DEMOGRAPHIC GROUP TERMS.

To which Adam Schiff replied:

The list of codes is in and online at (although the latter is still lacking a few of the codes found in the former).


Researchers Turn Data into Dynamic Demographics

Tuesday, May 1st, 2012

Researchers Turn Data into Dynamic Demographics

From the post:

Aside from showing off how their travel, culinary and nightlife habits, users of the geolocated “check-in” service Foursquare could shed light on the character of a particular city and its neighborhoods.

Researchers at Carnegie Mellon University’s School of Computer Science say that instead of relying on stagnant, unyielding census and neighborhood zoning data to take the temperature of a given community, Foursquare checkin data can provide the much –needed layer of dynamic city life.

The researchers have developed developed an algorithm that takes the check-ins generated when foursquare members visit participating businesses or venues, and clusters them based on a combination of the location of the venues and the groups of people who most often visit them. This information is then mapped to reveal a city’s Livehoods, a term coined by the SCS researchers.

All of the Livehoods analysis is based on foursquare check-ins that users have shared publicly via social networks such as Twitter. This dataset of 18 million check-ins includes user ID, time, latitude and longitude, and the name and category of the venue for each check-in.

“Our goal is to understand how cities work through the lens of social media,” said Justin Cranshaw, a Ph.D. student in SCS’s Institute for Software Research.

The researchers analyzed data from foursquare, but the same computational techniques could be applied to several other databases of location information. The researchers are exploring applications to city planning, transportation and real estate development. Livehoods also could be useful for businesses developing marketing campaigns or for public health officials tracking the spread of disease.

A good example of remapping data. The data was collected and “mapped” for one purpose but subsequently was re-mapped and re-purposed.

Mapping the semantics of data empowers its re-use/re-purposing, which creates further opportunities for re-use and re-purposing.

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