The Texas Data Repository uses the CC0 option. This option lets others distribute, remix, tweak, and build upon your work, even commercially. The summary of the legal code behind this designation states, "The person who associated a work with this deed has dedicated the work to the public domain by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law." (Further information: https://creativecommons.org/about/cc0/)
TDL asks that all users who download datasets from the Texas Data Repository adhere to the following Community Norms. Any materials (books, articles, conference papers, theses, dissertations, reports, and other such publications) created that employ, reference, or otherwise utilize the data (in whole or in part) gathered from deposited datasets should credit the source with the applicable data citation generated by the Texas Data Repository (found on the dataset page). These citations include the data authors, data identifier, and other information in accordance with the Joint Declaration of Data Citation Principles (https://doi.org/10.25490/a97f-egyk) for all research data.
Sound, reproducible scholarship rests upon a foundation of robust, accessible data. For this to be so in practice as well as theory, data must be accorded due importance in the practice of scholarship and scholarly record. Data citation, like the citation of other evidence and sources, is good research practice and is part of the scholarly ecosystem supporting data reuse.
The following Data Citation Principles cover purpose, function and attributes of citations:
- Importance: Data should be considered legitimate, citable products of research.
- Credit and Attribution: Data citations should facilitate giving scholarly credit and legal attribution to all contributors to the data.
- Evidence: In scholarly literature, the corresponding data should be cited.
- Unique Identification: A data citation should include a persistent method for identification that is globally unique.
- Access: Data citations should facilitate access to the data, associated metadata and other materials to make use of the referenced data.
- Persistence: Unique identifiers, and metadata should persist — even beyond the lifespan of the data they describe.
- Specificity and Verifiability: Data citations should facilitate identification of the specific data that support a claim.
- Interoperability and Flexibility: Data citation should be flexible but should not compromise interoperability.
C. Maintaining Anonymity of Human Subjects
Users of the Texas Data Repository should not abuse the available data that relate to human subjects and use the materials to:
- obtain information that could directly or indirectly identify any research subjects, or obtain information to attempt to identify any research subjects;
- produce and/or publish connections among datasets that could identify individuals or organizations; or
- obtain (additional) information about or (additional) means of contact for already-identified subjects.
If you are interested in building an API application designed (exclusively or not) to allow and provide access to Texas Data Repository and its materials and services, please keep in mind that such applications:
- acknowledge and agree that Texas Data Repository is not otherwise affiliated with any third-party Dataverse software API applications that provide access to Texas Data Repository, and therefore will not be held liable (in whole or in part) for any suits or damages incurred by the third-party Dataverse softwareAPI application owners, administrators, and affiliates; and
- Adapted from https://creativecommons.org/publicdomain/zero/1.0/
- Adapted from Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. Martone M. (ed.) San Diego CA: FORCE11; 2014 https://doi.org/10.25490/a97f-egyk