Dataset from the DataRes Project. This dataset is the primary survey on data management needs of researchers.

This dataset contains Twitter JSON data for several Twitter search queries collected the week following the filibuster by Wendy Davis in the Texas Senate related to Senate Bill 5, using the twarc (https://github.com/edsu/twarc) package that makes use of Twitter's search API. A total of 560,954 Tweets make up the combined dataset.

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.

This dataset contains Twitter JSON data for several Twitter search queries that were collected around the #YesAllWomen Twitter "conversation" between May 25, 2014 and June 8, 2014 using the twarc (https://github.com/edsu/twarc) package that makes use of Twitter's search API. A total of 2,805,763 Tweets and 34,532 images make up the combined dataset.

The dataset was developed to support research intended to develop a spatially-explicit model that prioritizes riparian areas in terms of potential for ecosystem restoration specifically to improve water quality downstream of the riparian area, and ultimately improve drinking water quality. The model was developed and then tested on the Lewisville Lake watershed (north central Texas, just north of Dallas, Texas, USA). The dataset contains environmental data for 90 sub-watersheds that form the overall Lewisville Lake watershed with a corresponding identification map.