This dataset contains the descriptive metadata harvested from the Texas Digital Newspaper Program collection on The Portal to Texas History and is accompanied by a dataset derived from the harvested metadata. This dataset was used for an IFLA Newspaper Section and Rootstech presentation.

Circulation report from November 2008 that details the numbers from various Texas Daily Newspaper Association members.

Advertising linage report that details ad revenue for Texas Daily Newspaper Association members, for December 2008.

Advertising linage report that details ad revenue from the Denton Record Chronicle, Texas Daily Newspaper Association member, for the year of 2008.

Advertising linage report that details ad revenue from the Dallas Morning News, a Texas Daily Newspaper Association member, for November 2008.

Advertising linage report that details ad revenue from the Plainview Daily Herald, a Texas Daily Newspaper Association member, for November 2008.

Circulation report from December 2008 that details revenue from Texas Daily Newspaper Association members.

Linage report from December 2008 that details ad revenue from Texas Daily Newspaper Association members.

Advertising linage report that details ad revenue from the Temple Daily Telegram, a Texas Daily Newspaper Association member, for December 2008.

ETS Corpus of Non-Native Written English was developed by Educational Testing Service and is comprised of 12,100 English essays written by speakers of 11 non-English native languages as part of an international test of academic English proficiency, TOEFL (Test of English as a Foreign Language). The test includes reading, writing, listening, and speaking sections and is delivered by computer in a secure test center. This release contains 1,100 essays for each of the 11 native languages sampled from eight topics with information about the score level (low/medium/high) for each essay. The corpus was developed with the specific task of native language identification in mind, but is likely to support tasks and studies in the educational domain, including grammatical error detection and correction and automatic essay scoring, in addition to a broad range of research studies in the fields of natural language processing and corpus linguistics. For the task of native language identification, the following division is recommended: 82% as training data, 9% as development data and 9% as test data, split according to the file IDs accompanying the data set.