Monday, 7 June 2021

5 ways sharing your research data could help enhance your career (and 3 ways to get started)

 

 Source: https://www.springernature.com/in/researchers/the-source/blog/blogposts-open-research/5-ways-sharing-your-research-data-could-help-enhance-your-career/18560392

5 ways sharing your research data could help enhance your career (and 3 ways to get started)

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The Source
By: Guest contributor, Wed Nov 11 2020
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Author: Guest contributor

There’s increasing evidence that sharing the research data which underpins your published article can have tangible benefits for you, and for your research career. 

Written by Rebecca Grant, Research Data Manager at Springer Nature

When you deposit your data in a repository and link it to your research article, it can be found, accessed and reused by researchers in different institutions, different regions, and even different disciplines. There are obvious benefits to science when researchers share data - but what specific benefits can you expect?

1. More citations of your published
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research articles

When you share the dataset that underpins your article, it’s not just the article that might be reused or cited; data sharing is also associated with an increase in citations to your research article of up to 25%.*

2. Greater discoverability and enhanced visibility

Sharing data in a repository makes it visible, and easily found by researchers other than those reading the journal you’ve published in. Data repositories are increasingly searchable on Google and indexed in resources like Google Dataset Search. The metadata you add to your data’s repository record helps others to understand how it was generated and what it consists of.

3. Get credit for your work and gain recognition

Not content with just increased citations of your article? More and more journals allow authors to cite datasets in reference lists, so if someone reuses your data, you get an additional citation for it.

4. New opportunities for collaboration

When your data can be easily found, other researchers can reuse it; or they may wish to work with you collaboratively to build on the data you’ve already shared.

5. Improve the veracity, robustness and reproducibility of your results

Science is in the midst of a reproducibility crisis, and many researchers report that they can’t reproduce others’ research (or even their own) .** Sharing data openly can encourage studies which replicate studies, and allow others to test the validity of your results.

Get started with research data sharing

Want to try data sharing? There are a few simple steps you can take to get started. You’ll need to identify which parts of your data you want to share, decide where to share it, and write a data availability statement to ensure that others can find it.

If your research generated large volumes of data, or multiple versions, it might not be clear what data you’re meant to be sharing. You can check with the policies of your funding agency, or the journal you’re publishing in, to find guidance on what you should share.

There are literally thousands of data repositories available online, including repositories which are specifically for certain data types or research disciplines; those provided by your institution or funder; or some which accept data in any format. It’s beneficial to select the repository which is most commonly used in your discipline - reading how other researchers in your field share their data can help you to establish which repository that might be.

Data availability statements are the best way to link your research paper to your dataset. They’re a simple paragraph which outlines where your data are and how they can be accessed (ideally in a data repository!). Journals are increasingly encouraging authors to add this statement to submitted manuscripts.

Need more help sharing data?

Research Data Support

Springer Nature Research Data Support service is a curation service for any published researcher (or those who are in the process of publishing in a Springer Nature journal or book). Researchers that use the service may feel that they don’t have the time, expertise or knowledge needed to organise data in a useful way, meet funder or institutional requirements on data sharing and get more credit and readership of their data and associated publication. 

Our team of expert research data editors do all the time-consuming work of creating high quality metadata records, making your research data understandable and easier to find and use by researchers in your field of study: time that you could use to carry out new research. We make sure that other researchers can find and cite your work, so that you get the credit you deserve.

Find out more about Research Data Support.

Data publishing

Data publishing supports researchers who want to share their datasets through peer-reviewed publications, without having to be at the stage of presenting further analysis and conclusions, as in a traditional research paper. Springer Nature supports and encourages data publications: we publish two dedicated data-publishing journals, Scientific Data and BMC Research Notes, and a number of our subject-specific academic journals offer article types suitable for data-only publications.

Our data papers put an emphasis on making data FAIR through recommended repositories, data citations and rapid publication.

To find out more, visit our research data publishing page, or get in touch directly via email.

*The citation advantage of linking publications to research data. Giovanni Colavizza,Iain Hrynaszkiewicz,Isla Staden,Kirstie Whitaker,Barbara McGillivray. https://doi.org/10.1371/journal.pone.0230416 

** www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970

If you would like to learn more about research data, our upcoming free webinar on 8 December, Sharing Research Data: What Publishers Want Authors to Knowwill provide an introduction to good practice in research data sharing and tips and guidance for getting started. Register here.

About the author

Rebecca Grant is Research Data Manager at Springer Nature, where she contributes to projects and services which support research data management and sharing, including the implementation of standard research data policies across Springer Nature journals. She leads the development of research data training as part of Nature Research Academies, and is a qualified data trainer certified by the Open Data Institute. Her doctoral thesis explored the connections between archival theory and research data management practice.

Author: Guest contributor

Guest Contributors include Springer Nature staff and authors, industry experts, society partners, and many others. If you are interested in being a Guest Contributor, please contact us via email: thesource@springernature.com.

Benefits of research data sharing for you

 

 Source: https://researchdata.springernature.com/posts/benefits-of-research-data-sharing-for-you

Benefits of research data sharing for you

There’s increasing evidence that sharing the research data which underpins your published article can have tangible benefits for you, and for your research career.

When you deposit your data in a repository and link it to your research article, it can be found, accessed and reused by researchers in different institutions, different regions, and even different disciplines. There are obvious benefits to science when researchers share data - but what specific benefits can you expect? 

Here are five ways sharing your research data could help enhance your career.

1. More citations of your published research articles

When you share the dataset that underpins your article, it’s not just the article that might be reused or cited; data sharing is also associated with an increase in citations to your research article of up to 25%.*

2. Greater discoverability and enhanced visibility

Sharing data in a repository makes it visible, and easily found by researchers other than those reading the journal you’ve published in. Data repositories are increasingly searchable on Google and indexed in resources like Google Dataset Search. The metadata you add to your data’s repository record helps others to understand how it was generated and what it consists of.

3. Get credit for your work and gain recognition

Not content with just increased citations of your article? More and more journals allow authors to cite datasets in reference lists, so if someone reuses your data, you get an additional citation for it.

4. New opportunities for collaboration

When your data can be easily found, other researchers can reuse it; or they may wish to work with you collaboratively to build on the data you’ve already shared.

5. Improve the veracity, robustness and reproducibility of your results

Science is in the midst of a reproducibility crisis, and many researchers report that they can’t reproduce others’ research (or even their own) .** Sharing data openly can encourage studies which replicate studies, and allow others to test the validity of your results.

How to get started with research data sharing

Want to try data sharing? Here are three simple ways to start sharing your research data, from writing a data availability statement, to finding a data repository for your discipline.   

Do you have a question about research data? 

Get free help and advice on sharing your research data: visit our research data help desk.

*Colavizza et al. (2020)

** www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970

Photo by Tomasz Frankowski on Unsplash

Dr. Rebecca Grant

Research Data Manager, Springer Nature

I am Springer Nature's Research Data Manager, where I develop products and services to support data management and sharing, including the implementation of standard research data policies across Springer Nature journals. I lead the development of research data training as part of Nature Research Academies, and I am a qualified data trainer certified by the Open Data Institute. My doctoral thesis explored the connections between archival theory and research data management practice.

How to increase the visibility of research articles: A Common Agenda of an Author and a Publisher

 Source: Ale Ebrahim, Nader (2021): How to increase the visibility of research articles: A Common Agenda of an Author and a Publisher. figshare. Presentation. https://doi.org/10.6084/m9.figshare.14527791.v1


Playing devil's advocate - Why the newly popular literature mapping tools may not be useful for the average researcher

 Source: https://musingsaboutlibrarianship.blogspot.com/2021/06/playing-devils-adovcate-why-newly.html

 


I have become increasing bullish on the rise of what I have called innovative literature mapping tools which have been emerging in the last two to three years thanks to the increasing availability of openly Scholarly metadata (in particular title, abstracts and citation data).

I would identify Barney walker's Citation Gecko released in 2018 as the first of it's class of  user friendly tools targeted at researchers that aim to help with literature (mostly narrative review) searches.

You typically enter some relevant seed paper and it will attempt to recommend related papers (typically using citation relationships) using it's built-in index of papers drawn from mostly open sources.  Some common tools and the indexes/sources of data used are listed below (as of June 2021).

Tool Major index & Sources used
Citation Gecko OpenCitations Index of Crossref open DOI-to-DOI Citations(COCI) & OpenCitations Corpus (OCC)
Local Citation Network Microsoft Academic Graph, Crossref, OpenCitations
Cocites NIH Open Citation Collection (NIH OCC)
Connected Papers Semantic Scholar Open Research Corpus
Paper Graph Semantic Scholar Open Research Corpus
Inciteful Microsoft Academic Graph,Semantic Scholar (abstracts), Crossref,OpenCitations
Litmaps Microsoft Academic Graph (primary source)
Citation Chaser Lens.org

Besides suggesting or recommending papers, you will also usually get a nice visualization or map of both the seed papers and papers recommended. Another commonality I have identified is that most of these tools are implemented as web services so there is no setup cost to install the software (though some open source ones like Citation Gecko do allow you the option to run a local install)

I think after due consideration, a more accurate terminology for them should be Citation based Literature mapping services but for now I will use the generic name "literature mapping tool".

These tools are very new with the latest ones emerging in 2020. Some of them like Connected Papers seems to have struck a chord. For example, this tiktok video on Connected Papers garnered 2.5 million views! My post on r/Phd on these tools (link to this medium post) got 400+ upvotes and dozens of awards and enthusiastic thanks and various social media accounts of these tools are showing very good responses from their fans. But are such reactions only based on first impressions?

As such I think it is often a good idea when advocating for something new to switch hats and consider why the new shiny idea might not be good. That is why in this post  I will play devil's advocate and try to argue why such tools really aren't that useful to the average researcher when doing literature review.

In this long post, I will first describe how such tools typically work and then distinguish them from other similar tools such as "Science mapping tools". 

Finally, I will then play devil's advocate on why such tools aren't really useful and possible answers to those doubts.