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Peijin Han, Postdoctoral Research Fellow, Johns Hopkins Medicine
My paper was about the radiation dose and its influence patterns on salivary gland sub volumes, regarding to radiation induced xerostomia and patients recovery from xerostomia. We found that the influence of radiation dose to salivary gland is different from xerostomia injury and recovery. I analyzed the dose-volume histogram (DVH) data extracted from the sub volumes of the parotid glands, submandibular glands, and oral cavity. The outcome data is the physician report xerostomia based on Common Terminology Criteria for Adverse Events (CTCAE).
We used Springer Nature’s Research Data Support service because we thought our publication of the de-identified analytic data could help researchers to better understand how we construct the dataset, and how we perform the analysis. If researchers from other institutions want to do a validation study, it’s now easier for them to know what the dataset looks like.
I think the most beneficial part of Research Data Support service is it can help with the further validation study, as well as collaborations between institutions. For example, our findings were limited because we don’t have a large sample size. We highly appreciate if other institutions would like to validate our results with a larger patient population. It is very interesting to see the results of these validation studies, and I think these kinds of studies can definitely give us more information about our research topic.
Through data sharing and model validation between institutions, I would expect we can produce a more ‘robust’ xerostomia injury and recovery prediction model, which can be embedded in current treatment planning system. I hope we can do a better job to prevent or improve radiation-induced toxicities, and improve patients’ quality of life.
I would like to recommend the Research Data Support service to other researchers. As long as the ‘de-identified’ rules been followed, I think it would be very good to publish the data. The service was beneficial and very easy to use.
Olga Viedma, Associate Professor, University of Castilla–La Mancha
This paper provides a spatio-temporal assessment of the changing effects of climate, landscapes and socioeconomic drivers on wildfires. This was done by modelling the number of fires per cell per year using two types of mixed models: Longitudinal Negative Binomial (LNB) and Zero-Inflated Negative Binomial (ZINB), with time as an interacting factor. I decided to use Springer Nature’s Research Data Support service to get more credit and readership of my data and associated publication. Overall, to get more citations.
The most beneficial part of the Research Data Support service was to promote transparency and reproducibility. Also, I wanted to get high quality metadata records and make my research data easier to find and use by researchers in my field of study. I would recommend Research Data Support to other researchers because it is a real useful tool to access to several databases. I would use it again because I want to raise the visibility of my research.
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