Sharing your research data
This module will help you with the Data collection-creation section of your data management plan. Data management planning templates are available for download here or directly from our library data management page here.
More information on this topic can be found here
Section 1: Publishing and sharing data
Section 2: Preserving and archiving data sets
Section 3: Copyright elements
Section 4: Re-using data
Publishing and Sharing Data
To benefit from making your datasets open, make sure that they:
- are easy to find
- include information on how the data was collected, saved and accessed
- give clear information about how the datasets can be used.
Easy to find
To make it easy for researchers to find, choose a digital repository that is either commonly used in your field of study or is covered by databases such as Google’s Dataset Search. When uploading the datasets, include as many relevant labels and tags as possible, and write a description that uses some of the words that researchers might use to search for that subject. This is important because most databases do not search for words within the datasets itself; only the words in the labels, tags and descriptions.
Once you upload your data to a repository, your data should be assigned a DOI (digital object identifier). This is a persistent link to the dataset; you (and others) can use this link to share the location of the dataset and to promote the use of the data. If you deposit your data into an external repository, you can still link this DOI to the Griffith Research repository (GRO).
Information about the data
To make it easy to understand, prepare clear and comprehensive documentation outlining how the data was collected, what instrumentation was used, what software was used to analyse and save the data, what conventions you used in naming, and any other details that will assist researchers to process your datasets fully and correctly to faithfully replicate an analysis of your data.
How datasets can be used
A clear statement about how the datasets can be used, and how you can be acknowledged for your work, is in the copyright licence that you assign. For highest impact, consider assigning an Attribution 4.0 International (CC BY 4.0) licence allowing anyone to use and adapt your datasets while requiring that you be given appropriate credit. This licence is commonly recommended by funding agreements; however, it is important to consider both the funding and the publishing agreements when assigning the licence.
Check the copyright page of this guide or contact the Griffith university copyright officer for more details.
- Many funding agencies and publishers will require a copy of your data is made available via a repository ie Griffith Research Online (GRO)
Preserving and Archiving Data sets
When archiving your datasets, there are factors which can influence the decisions you make. Your choices can be limited by:
- the requirements of funders
- the guidelines from journal publishers
- the practices within the academic discipline
- legislation (i.e., human subjects)
One or more of these requirements may determine your choice of access, repository, and copyright licence.
To release a dataset with a copyright licence, you must first have sufficient rights to the dataset. Details such as intellectual property rights can be confusing, particularly if it is being determined retrospectively. For more Information, go to Griffith’s Copyright matters page, where you can also find the contact details for the Information Policy Officer.
Before submitting a dataset to an archive make sure you can fill out the following checklist:
Copyright elements
| Element | Notes |
|---|---|
| Are there images? | Who owns the rights to the images? |
| Are the images of people? | Do you have ethical clearance for these images? |
| How was the data collected? | - Observational? - Computational? - Long form collection? |
| Who collected the data? | Where multiple parties are involved, we need to get permissions from the other parties to publish the data |
| Who funded the project? | Important but should not affect the publication |
| Does the data set involve people? | If no, no problem, if yes, do you have ethical clearance from the participants to publish |
| Was any other body involved? | Funding agency, government body, external institution? |
| Was the data collected or analysed by more than one body? | |
| Was the project a collaboration with a government body or institution? | |
| What, if any, Licencing arrangements are in place? | What type of licence do you wish to apply to the data? |
Record all relevant data when submitting your datasets to a repository. Comprehensive description of how the data was gathered and stored will maximise the benefits of storing the datasets in a repository. These benefits include
- greater reuse and citations by other researchers if you make the datasets open
- your research can be faithfully replicated by other researchers questioning your findings.
- you can replicate your own research if you wish to revisit your research in the future.
This information assists researchers (including you in the future) to use the dataset correctly, whether it is for replicating your research, interrogating your findings, or drawing upon your work in new research.
Most repositories will need information around the following elements:
| Topic/Question | Description/notes | Follow up |
|---|---|---|
| Singular data set or collection of data? | ||
| Does the dataset meet deposit requirements for deposit in Griffith research online (GRO)? | GRO is for data required for new manuscripts, or new/old data supporting projects funded by ARC/NHMRC. | Does the data meet the requirements for High use in the GRO team? |
| Who funded the research? | ||
| Where is the data currently stored? | Griffith university storage • External drives • Other? | |
| Does the dataset have a DOI? | GRO can create DOI’s, however most external data repositories will also mint a DOI for you that can be linked back to the GRO repository | |
| Is the data in a publishable state/ready state? | Does the meet open research/FAIR/CAIR guidelines? Is the data: • De- identified • De- sensitised. | |
| Have you used File & folder naming conventions | Is this convention intuitive or described in a read me file? | |
| Access level of the data | What level of access do you need for the dataset? Open or mediated access? | |
| Do you want to deposit the data or link to the dataset in GRO? | Does the physical data need to go into the Griffith repository? | |
| Historical datasets | Where do you wish to deposit the data? If you deposit to an External repositories, please link the DOI back to GRO. | What we do with Historic data? Previous funded research? Where to store it? Look at external repositories and link back to GRO |
| Metadata | You need the minimum 6 metadata elements Identifier, title, creator(s), publisher, publication, year, resource type | the followings show example metadata schema |
| OPEN ACCESS? | Can the data go into an open access repository? do you have a repository in mind? In certain cases GRO will not hold the data. If you wish to archive the data you will need to find an external repository. | Funding permissions may impact where the data can be stored and how it is accessed. |
| Copyright licencing | find out which licence to use for your Data; For all data reuse purposes licencing is required. More details in the copyright section or contact the Copyright officer for more details. | Griffith copyright |
Re-Using Data
Re-using and the analysis of exsiting datasets is an excellent way to expand, compare and test your research data. Where data exists in similar areas you can re-use the existing sets instead of creating or studying well researched areas, eg: gathering school data or public polling.
Using an exsiting dataset can help you to scrutinize your research findings, show areas of need in the data and in some cases generate new areas of research from the existing data.
To find and examine exisiting datasets explore the libraries Find data pages.