Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 3 |
Descriptor
Computer Interfaces | 3 |
Data Collection | 3 |
Artificial Intelligence | 2 |
Computer Networks | 2 |
Computer System Design | 2 |
Data Analysis | 2 |
Academic Libraries | 1 |
Accuracy | 1 |
Automation | 1 |
Barriers | 1 |
Classification | 1 |
More ▼ |
Author
Brandon Sepulvado | 1 |
Chris Haffenden | 1 |
Emma Rende | 1 |
Faton Rekathati | 1 |
Fredrik Klingwall | 1 |
Hillevi Hägglöf | 1 |
Jennifer Hamilton | 1 |
Justyna Sikora | 1 |
Love Börjeson | 1 |
Martin Malmsten | 1 |
Robin Kurtz | 1 |
More ▼ |
Publication Type
Reports - Research | 2 |
Journal Articles | 1 |
Reports - Evaluative | 1 |
Tests/Questionnaires | 1 |
Education Level
Higher Education | 1 |
Postsecondary Education | 1 |
Audience
Location
Sweden | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Love Börjeson; Chris Haffenden; Martin Malmsten; Fredrik Klingwall; Emma Rende; Robin Kurtz; Faton Rekathati; Hillevi Hägglöf; Justyna Sikora – College & Research Libraries, 2024
This article provides an account of the making of KBLab, the data lab at the National Library of Sweden (KB). The first part discusses the work involved in establishing a lab as both a physical and a digital site for researchers to use digital collections at previously unimaginable scales. The second part explains how the lab has deployed the…
Descriptors: Foreign Countries, Government Libraries, Artificial Intelligence, Computer Networks
Ruediger, Dylan – ITHAKA S+R, 2021
Ithaka S+R's Research Support Services program's most recent project, "Supporting Big Data Research," focused specifically on the rapidly emerging use of big data in research across disciplines and fields. As part of this study, they partnered with librarians from more than 20 colleges and universities, who then conducted over 200…
Descriptors: Colleges, Universities, Data Analysis, Data Collection
Brandon Sepulvado; Jennifer Hamilton – Society for Research on Educational Effectiveness, 2021
Background: Traditional survey efforts to gather outcome data at scale have significant limitations, including cost, time, and respondent burden. This pilot study explored new and innovative large-scale methods of collecting and validating data from publicly available sources. Taking advantage of emerging data science techniques, we leverage…
Descriptors: Automation, Data Collection, Data Analysis, Validity