Benefits of sharing data:
- Analyses can be reproduced and/or validated by others
- Data can be checked for cleanliness and accuracy
- Data can be used for educational purposes
- Help the development and evaluation of novel statistical methods
- Allows testing of secondary or new hypotheses
- Helps in designing new experiments
- Simplifies data acquisition for meta-analysis
- Helps to prevent research misconduct and selective reporting of results
Modified from (Vickers, A (2006) Whose data is it anyway? Sharing raw data from randomized trials. Trials 7: 15).
View this Data Sharing and Management Snafu video for a great example of the challenges of utilizing someone else’s data:
Standards for sharing data:
Without standards, your data may be unusable or unidentifiable. Metadata is descriptive or contextual information that refers to your data. The level of information you keep about your data will depend on the type of data you collect and expected re-purposing.
Use standardized taxonomies and controlled vocabularies to better capture, manage, and archive your data. The most basic type of metadata to capture includes:
- Descriptive (title, time, author, keywords, relations to other data, what the data is about)
- Technical (process used to produce the data, or process required to use the data)
- Administrative (ownership, use permissions)
- Provenance (data origination, history of changes, versions)
- Discipline specific (format, subject, taxonomies, etc.)
For more information on subject-specific metadata (taxonomies, thesauri, ontologies, etc.), see the University of Pittsburgh Metadata & Discovery Guide or the Digital Curation Center Guide on Metadata Standards.
Copyright & Ethical Use of Data
Copyright and Data as Intellectual Property
For more information on copyright and data management, or to request a workshop, please see the UF Libraries Copyright on Campus guide.
Citing Data: If you are using another researcher’s data, you must properly cite the data. For more information on citing datasets.