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When considering whether to reuse other researchers’ data, determine whether the data is suitable for your purposes and, if so, determine the terms for reuse of the data. Properly cite the dataset in order to:
- Provide credit to data creators
- Assist in measuring impact of data
- Enable others to access the data
- Help researchers know how their data is being used
A data citation should include:
- Title of dataset
- Version information
- Publication date
- Identifier/Locator (DOI/URL)
For more information on citing datasets, visit the Digital Curation Centre website.
Most personal names are not unique, can potentially change, and may be ordered differently depending on culture. This makes identifying and linking scientific and academic authors to their contributions (both publications and research data) difficult. There are several resources available to allow researchers to uniquely identify themselves electronically:
- ORCID (Open Research & Contributor ID) "...aims to solve the author/contributor name ambiguity problem in scholarly communications by creating a central registry of unique identifiers for individual researchers and an open and transparent linking mechanism between ORCID and other current author ID schemes. These identifiers, & the relationships among them, can be linked to the researcher's output to enhance the scientific discovery process and to improve the efficiency of research funding & collaboration within the research community."
"ResearcherID is a global, multi-disciplinary scholarly research community. With a unique identifier assigned to each author in ResearcherID, you can eliminate author misidentification and view an author’s citation metrics instantly. Search the registry to find collaborators, review publication lists and explore how research is used around the world."
- Google Scholar Citations
- "Track citations to your publications
- Check who is citing your publications. Graph your citations over time. Compute citation metrics.
- View publications by colleagues
- Keep up with their work. See their citation metrics.
- Appear in Google Scholar search results
- Create a public profile that can appear in Google Scholar when someone searches for your name. "
- Public investment
- Required by publishers/funders
- Inform new research
- Maximize transparency
- Increase impact
- Reduce duplication effort
- Provide credit to researcher
- Researcher and team
- Scientific communities
- Funding agencies
Ways to share
When to share
- During a project
- Immediately after a project
- Given time after a project
What to share
- Raw data
- Processed data
- Software/scripts used
Researchers should consider the legal and ethical issues involved in sharing (e.g. do they have consent to share participant data?). They should also consider the potential for reusability of their data, as well as whether outsiders will be able to understand the data. There are some potential drawbacks to sharing. Ensuring data is fit to share may be time-intensive. Others could misuse or misrepresent a dataset. Data released in the middle of a project may not have undergone sufficient quality assurance. There may be an overlap of publications if data are released during or immediately following a research project.