1/ 🧵 Dental research generates data, but is data available and is machine-actionable?
That's the question we asked w/ @ASofiMahmudi @raittioe @IlzeMal & @baiba_vilne in #openaccess @JDentRes journals.sagepub.com/doi/full/10.11… thanks to @mikrotik_com & @bbcentre_eu #FAIR #openscience
2/ Raw data allows replication and validation of results. Additionally, if it is in a machine-accessible format, this would allow new hypotheses to be explored using the available data
#reproducibility #researchtransparency #opendata #FAIRdata
3/ in order for machines to access data, it must be Findable, Accessible, Interoperable and Reusable. This is known as #FAIRdata
4/ Sharing data in #FAIRdata allows other researchers to access it, but it is primarily intended for 🤖, as they see the data in a different way.
In this way they can catalog, process or reuse this data or join it with other data, maximizing the effects of the research.
5/ Using tools created primarily by @SteliosSerghiou and @FAIRsFAIR_EU we programmatically analyzed the availability and quality of data available in dental publications @EuropePMC_news from 2016 to 2021. Thus we were able to evaluate how machines view the available research data
6/ We found that of 7 549 available publications, 112 (1.5%) shared research data; Table 1 shows the results by journal and year. Of 165 journals, we found data in only 21. We did not find a trend by year.
7/ When evaluating compliance with FAIR criteria, we found that the average compliance was 32.6%. The items with the lowest compliance were reusability (24%) and interoperability (27%). #dentalFAIRdata
8/ We observed that there was no clear trend in #FAIRdata compliance for dental publications between 2016 to 2021 nor for journals. #dentalFAIRdata
9/ When analyzing the detail, the item with the least compliance refers to the description of the metadata and whether the data is in a format that can be reused (open format such as csv) or closed (such as xlsx, doc, etc). #dentalFAIRdata
10/ What do these results mean? The fact that 98.5% of the research evaluated does not share data makes the measures being taken by major funding agencies such as @NIH, @UKRI_News, and @HorizonEU make sense and should be implemented urgently. #opendata #dentalFAIRdata
11/ recent research @JClinEpi showed that even when authors put "Data available upon request" only 7% of contacted authors shared the data ( jclinepi.com/article/S0895-… ) so journals should start demanding data or authors justify why they can't share it. #opendata
12/ On the other hand, the fact that the few data are shared in unstructured format instead of #FAIRdata hinders their use by other researchers, limiting their reproducibility as well as their machine-actionability. What can researchers do to improve this situation?
13/ First of all learn about FAIR principles. A good guide is here openaire.eu/how-to-make-yo…, howtofair.dk or by asking at your research office.
14/ Before you begin your research, develop a data management plan. You can use @TheDMPTool or argos.openaire.eu/home from @OpenAIRE_eu
When you finish the research, make sure to deposit the data in repositories, such as @ZENODO_ORG , @figshare @OSFramework
15/ Also make sure that the data is shared in a recommended #openformat #opendata
16/ Be sure to publish all #metadata, i.e., the data that indicates what the data is about. You can check for standards here from @FAIRsharing_org : fairsharing.org/search?fairsha…
17/ When you publish your data, make sure that you clearly indicate whether you allow the use of the data and under what conditions by means of a license.
18/ The fact that your data is #FAIRdata does not mean that everyone has access, and there may be conditions (confidentiality, commercial agreements) that may well limit access, but the *data should be as open as possible and as closed as necessary*
19/ So when starting your research, plan your data management! You can use a tool like @TheDMPTool or argos.openaire.eu/home from @OpenAIRE_eu.
20/ Then when publishing your raw data, you can verify compliance with the #FAIRdata principles using the @FAIRsFAIR_EU tool at fairsfair.eu/f-uji-automate…
21/ When you share your data in FAIR format in repositories like @ZENODO_ORG or @OSFramework - @figshare - you ensure that your results can be independently replicated and validated, and that's just what doing science is all about!
22/ The full report #openaccess at @JDentRes journals.sagepub.com/doi/full/10.11… and you can follow @FAIRsFAIR_EU @OpenSciTalk @InCollaboratory @SteliosSerghiou @EoscLife @resdatall @EmbassySci @GOFAIRofficial @OpenAIRE_eu #opendata #openscience to learn more about #fairdata
BONUS: this publication follows #openscience principles, with the protocol osf.io/zs5dk , final report journals.sagepub.com/doi/full/10.11… and dataset zenodo.org/record/6460190 published #openaccess
BONUS: the publication does not contain P-values or significance tests.
BONUS Reviewers provided advice and comments that significantly improved the paper. Also, the attention to detail from @NickJakubovics, editor of the @JDentRes was amazing 🤩 check this 👇
END/ Finally kudos to the great team of @ASofiMahmudi @raittioe @IlzeMal and @baiba_vilne and to the support through the @mikrotik_com research grant and the bbcentre_eu that made this #metaresearch possible. Download the full text here: journals.sagepub.com/doi/full/10.11…
ah, this research is part of a special issue of the @JDentRes about Data-Driven Dentistry, so stay tuned for more information.
x/ in case you asked, this is the #FAIRness 🤖 of the dataset from this research Evaluation: f-uji.net/view/172 Dataset: zenodo.org/record/6460190
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