Network graph representation of COVID-19 scientific publications to aid knowledge discovery

Article activity feed

1. 

   ScreenIT

   Mar 1, 2021

   SciScore for 10.1101/2020.10.12.20211342: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   The open-source software tool Gephi was used to create a visualisation of the network using the collections of terms and connections that made up the network structure.[	Gephi suggested: (Gephi, RRID:SCR_004293)

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   Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

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   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   Another limitation is that the network only shows the first level connections or the direct connection between …

   SciScore for 10.1101/2020.10.12.20211342: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   The open-source software tool Gephi was used to create a visualisation of the network using the collections of terms and connections that made up the network structure.[	Gephi suggested: (Gephi, RRID:SCR_004293)

   ---

   Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

   ---

   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   Another limitation is that the network only shows the first level connections or the direct connection between papers and concepts. It does not find connections between concepts that span several papers – although this can be achieved by traversing the network visually. We addressed these limitations of network size and the search for deep connections by implementing a breadth-first search on the network structure. The search is efficient and can be applied across very large networks, even when all the knowledge sources are used simultaneously. This approach can find the shortest path connections (the trail of papers) between any concepts. This study has demonstrated that an approach using graph databases and network analysis can be developed rapidly and is a useful approach for understanding large volumes of medical literature, quickly grasping the current state of our knowledge, and discovering previously unknown or unnoticed relationships between emerging medical concepts. The unusual circumstances of a global pandemic have given rise to assembly of an unprecedented volume of medical literature and this work demonstrates a powerful approach to condensing the literature into insights that help us fight this disease. Further development of this approach will enable ongoing analysis and deep searching of large collections of literature, such as PubMed, and application to other disease areas, as well as for target or biomarker discovery.[12–14]

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   Results from TrialIdentifier: No clinical trial numbers were referenced.

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   Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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   Results from JetFighter: We did not find any issues relating to colormaps.

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   Results from rtransparent:

   • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
   • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
   • No protocol registration statement was detected.

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2. Version published to 10.1136/bmjhci-2020-100254

   Jan 1, 2021
3. 

   Version published to 10.1101/2020.10.12.20211342v1 on medRxiv

   Oct 14, 2020