Good planning will smooth the path for implementing data citation in your organisation. Consider key questions early, learn from what others have done and talk with ANDS staff about the services and support we offer.
To guide your planning for data citation consider these key issues:
- Resource planning: have you identified the people and skills, infrastructure, support and resourcing you will need to successfully implement data citation?
- Business rules & procedures: have you determined guidelines or business rules for identifying citable data (PDF, 0.2 MB)?
- Metadata framework: are you able to provide at least the minimum metadata requirements to form a data citation?
- Data and metadata storage: are you able to guarantee that the data and metadata will be persistently stored and managed for the appropriate time for a scholarly record?
Once you've worked through these questions and have completed the ANDS Cite My Data DOI Service Checklist (DOCX, 0.23 MB), you are ready to get the data citation ball rolling.
An early and important decision will be whether you plan to assign DOIs (Digital Object Identifiers) to your published data using the ANDS DOI Service (Cite My Data). This is highly recommended because:
- the assignment of a DOI to data is considered best practice and indicates that the dataset will be well managed and accessible for long-term use
- a DOI provides easy and persistent access to research data available via the internet
- DOIs enhance discovery, retrieval and management of data to enable data reuse and verification of research result
- DOIs support automated tracking of data outputs by indexing services such as the Thomson Reuters Data Citation Index as well as altmetrics such as number of views, downloads and 'likes'.
- Tracking it back to the source: managing and citing research data - NISO forum
- Simons, N. (2012) Implementing DOIs for research data D-Lib Magazine, Vol.18, no-5-6, doi:10.1045/may2012-simons
In this video, Louise Corti discusses policy decisions on granularity, versioning and when to apply a new DOI to a dataset.
Now that you've assembled your team and undertaken the planning phase, it's time to move forward with creating the infrastructure and supporting resources needed to implement data citation and DOIs in your organisation. This will involve:
- Implementing your data storage and metadata storage strategy
- Implementing a process to capture citation metadata for citable data collections
- Implementing the ANDS DOI Service (Cite My Data). Start by reading the ANDS DOI Service Policy and Technical Documentation and check whether you can re-use existing software
- Creating supporting documentation and promotional materials.
- DataCite - an international initiative to facilitate access to research data
- DataCite Metadata Schema for the Publication and Citation of Research Data: the introduction examines the broader issues of data citation and associated metadata.
Having the infrastructure and resources in place to enable data citation is a significant achievement for an institution. It lays the foundation for increasing the research profile of individual researchers and data custodians as well as the institutions they are affiliated with. To truly realise the benefits of data citation, institutions need to foster a culture that encourages, supports and promotes data citation.
This will involve a range of stakeholders including researchers, librarians, data custodians, data managers, data producers and data users. What key messages and strategies will underpin this cultural shift? Every institution is different, and no "one size will fit all", however, your institution might want to consider the following key messages:
- The scholarly publishing and data citation landscape is rapidly evolving with an increased emphasis on research data.
- Internationally, there is an increasing trend toward research funders (including the NHMRC and ARC) encouraging or mandating open access to research data.
- Research shows that publishing your data, with a DOI and citable reference can increase your citation rate and impact.
- We (your institution) have the capability to enable researchers and data custodians to take advantage of the benefits of data citation.
- There are rapidly increasing ways to publish and promote your data through Research Data Australia and data journals.
To deliver the key messages across your institution, you may want to consider developing resources and strategies to promote:
- the benefits of data citation
- how to cite your and other people's data in your publications
- linking between publications and related dataset: see an example in Research Data Australia which links original and derived datasets, software and publications.
- potential rewards and impact of data citation
- how to access your data citation services for further information and help.
Until these key messages get traction, and individuals start citing data in their publications, it will be difficult to realise the benefits and measure the impact of publishing research data.
- Nature Publishing Group announces the launch of 'Scientific Data' - a new open-access, online-only platform for the publication of descriptions of scientifically valuable datasets.
This video explains what Griffith University are doing to establish a culture of data citation.
Formal publication and citation of data supports the recognition of research data as a first class research output. It also enables the generation of citation metrics for research data outputs. Indexing services such as Thomson Reuters Data Citation Index capture data citation metrics, making formal recognition and reward mechanisms based on data publishing now possible.
Other less formal measures may also apply to published data. These include a range of altmetrics such as number of views, number of downloads, social media "likes" and recommendations. Such metrics are becoming increasingly common across a range of data publishing models including data repositories and data journals. Altmetrics can be an early indicator of the impact or reach of a dataset, before the long tail of formal citation metrics can be assessed. Digital Science's Altmetric service aggregates online attention for research outputs, such as mainstream and social media, online reference managers, Wikipedia, blogs, F1000, and public policy documents. Scientific Data is one data journal that displays Altmetric scores for data.
- Piwowar, H (2013) Altmetrics: Value all research products. Nature. Vol.493, no.159, doi:10.1038/493159a
Additional resourcesThis video discusses the Thomson Reuters Digital Citation Index. Look out for the following highlights:
- ICPSR (starts at 5.32): data sharing, how ICPSR is encouraging good practice, benefits of the DCI.
- California Digital Library (starts at 18.40): open source tools academic libraries are using to support data rich researchers.
- Pangaea (starts at 29.30): data publishing prerequisites, infrastructure and building blocks in use.
- Thomson Reuters (starts at 41.20): about the DCI and Q&A from webinar participants.
Data citation offers an extension to current measures of research impact. Benefits to the institution of being able to accurately track the impact of data through data citation include:
- fulfilling funder requirements which stipulate publishing research outputs
- raising the profile of your institution, its research and researchers
- adding citable references to data outputs on biosketches and in CVs
- an additional metric to complement traditional publications metrics
- tracking the reach, impact and reuse of research investments
- taking advantage of emerging opportunities to quantify data impact through:
- Piwowar, H and Priem, J (2013) The Power of Altmetrics on a CV. Bulletin, April/May 2013. Association for Information Science and Technology.