Manage and publish your research data
Find out the best practice for managing your research data.
Managing and publishing research data has several benefits for researchers:
- Comply with funder and publisher requirements
- Increase visibility of your published research, and gain more citations
- Publish negative data to gain citations for work that in the past would have been considered wasted time
- Avoid becoming a newspaper article about years’ worth of lost data
We provide workshops to get you started, a data management plan template to keep you organised and the Data@Lincoln platform where you can publish your data at the end of your project. For more advice, you can talk with the Records and Research Data Analyst.
The Records and Research Data Analyst, is available to assist staff, post-doctoral candidates and post-graduate students on elements of Research Data Management best practice including:
- data publication
- storage and backup, including steps you can take to keep your data safe
- keeping data organised so you can find (and understand) it again
- data compression and encryption, including when to use them and safety measures to take.
Research Data Management training is available for staff, post-doctoral candidates and post-graduate students. Workshops are available for the following subject areas. Workshops 1 and 2 are part of the Postgraduate Workshop Series and all three workshops can be delivered on demand if four or more participants sign up. Contact Talia Skinner to schedule one of these workshops.
- The What, Why and How of Research Data Management – Learn why it has become important for researchers to learn about Research Data Management. We will touch on storage and backup, metadata, file and folder names and data publication.
- How to fill out a Data Management Plan – Fill out a Data Management Plan for your study or project while a staff member guides you through the university’s Qualtrics-based DMP tool.
- Research Data Management for Supervisors – This 45-minute course is intended to get busy researchers up to speed with the minimum they need to know about Research Data Management.
The Lincoln University Data Management Plan (DMP) format
The Lincoln University DMP format is based on best practice and is designed to collect the necessary information in the minimum amount of time. The format uses check boxes using Qualtrics survey software. Each question also includes a text box so that researchers can give as much extra detail as they think is needed for each answer.
What is a Data Management Plan?
A Data Management Plan (DMP) is a document that lays out how you will manage your research data during a research study and after its completion.
Create your own Data Management Plan.
Why do researchers need to write a Data Management Plan?
The environment researchers work in is rapidly changing as they produce larger amounts of data in multiple formats. Writing a DMP is a good way to ensure that you have thought through the process of what will happen to your data at each stage of the study. A DMP can also help significantly cut down on unpleasant surprises.
A growing number of research funders and publishers are also mandating the use of DMPs. These requirements can include publishing datasets.
My publisher/funder requires a different DMP format. What should I do?
Follow the DMP requirements set forth by your funder or publisher. The important factor is that you complete a DMP, full stop.
I have an idea for the University DMP format. What should I do?
Lincoln staff and students can publish datasets on Data@Lincoln to meet data publication requirements from funders and publishers and increase the visibility of your research. You might publish your data at the same time as the journal paper it underpins – or you might publish “negative results” that won’t lead to a full publication but might still interest other researchers.
Go to Data@Lincoln
This video (4mins:44s) will show you how to upload your data to Data@Lincoln, how to make your data discoverable, and how to get credit for it.
How much storage can I get?
Each researcher at Lincoln, be they staff or student, starts with 50GB of free storage on Data@Lincoln. Researchers can request more storage by contacting Talia Skinner.
Is data public or private?
The primary purpose of Data@Lincoln is for publishing data open access, so that it shows off your research and can be cited. (Altmetric ratings are provided for published datasets.) But there are options for embargoing your data if necessary for publication, commercialisation, ethical or cultural requirements. Contact Talia Skinner for more information.
What size files can I upload?
Files up to 5GB can be uploaded using the drag-and-drop method. If you have larger files, contact Talia Skinner as Data@Lincoln might not be the best place for them.
How can someone cite my data?
A Digital Object Identifier (DOI) is created when data is published on Data@Lincoln, and each item has a “Cite” button where you can select the citation style required. Metrics on the page count the number of times data is cited.
Whether you’re doing it to satisfy the requirements of funders or publishers, or to boost your citation rates, publishing datasets is becoming the norm in academia. Here are some tips for finding the right place to publish your data if Data@Lincoln isn’t right for you.
Publisher or funder requirement to publish data
Check with your publisher or funder as they may have specific requirements for where or how to publish your data. For examples see:
National Science Challenge:
- Criteria for Proposals for Second Period National Science Challenges Funding. See bullet point ‘Related Activities’.
- National Science Challenges: Mid-Way Review Panel Guidelines. See page 11 under Definitions, Related Activity.
How to determine if your publisher requires data publication.
- Data publication doesn’t just mean publishing the data on a website. Data publication usually requires a data repository such as Data@Lincoln, Dryad or GenBank.
- Check under the author instructions for headings such as data availability, data citation and data sharing.
- Don’t wait until the last minute to determine if you need to publish your data. Some publishers, such as PLOS ONE and Nature, require that authors make their data available at time of publication. Other publishers have different requirements for different journals.
A good reason for publishing your data in a discipline-specific repository is that it will make it easier for people interested in your field to find your results. re3data.org and Databib are registries of research data repositories that let you search for an appropriate place to publish.
Some popular discipline-specific databases are:
- Chemistry: PubChem
- Earth and environmental science: PANGAEA
- Genetic sequences: GenBank
- Life sciences: Dryad
- Social science: New Zealand Social Science Data Service.
Publishing negative results
Publishing your negative data on Data@Lincoln lets others use and cite the data even if you can’t publish a related paper.
Whether adding information to a new study or illustrating why a course of research wasn’t taken through citing negative research data, using data from another researcher’s study is becoming more commonplace. Lincoln University uses APA 7th referencing style.
For datasets with a DOI (digital object identifier)
Author/Rightsholder. (Year). Title of data set (Version number) [Description of form]. doi:10.###/###
Skinner, E.-T. & Fitchett, D. (2013). Basic data management practices. doi:10.6084/m9.figshare.781296
For datasets without a DOI
Author/Rightsholder. (Year). Title of data set (Version number) [Description of form]. Retrieved from URL
Pew Hispanic Center. (2004). Changing channels and crisscrossing cultures: A survey of Latinos on the news media [Data files and code book]. Retrieved from http://pewhispanic.org/datasets
For purchased datasets
Rightsholder, A. A. (Year). Title of dataset (Version number) [Description of form]. Publication Location; Name of producer if different from rightsholder.
Davis, J. (1988). Familiar birdsongs of the Northwest [Sound cassette]. Portland, OR: Portland Audubon Society.
For unpublished or personal datasets
Author, A. A. (Year). [Description of study topic]. Unpublished raw data.
Jones, A. W. (2012). [Personnel survey]. Unpublished raw data.