165 Matching Annotations
  1. Jul 2022
    1. Why traditional startups struggle to disrupt the academic publishing industry.

      Publishing industry disruption - commentary. Includes a clear simple vision for what science publishing could do.

    1. In January, Schmidt Futures, a science and technology-focused philanthropic organization founded by former Google chief executive Eric Schmidt and his wife Wendy, launched the Virtual Institute for Scientific Software (VISS), a network of centres across four universities in the United States and the United Kingdom. Each institution will hire around five or six engineers, says Stuart Feldman, Schmidt Futures’ chief scientist, with funding typically running for five years and being reviewed annually. Overall, Schmidt Futures is putting US$40 million into the project, making it among the largest philanthropic investments in this area.

      Schmidt Futures funding long-term software engineers to maintain scientific software.

  2. Feb 2022
    1. offer some form of tenure insurance

      Maybe this is what some kinds do through reputation / networking that comes from being funded, irrespective of the project outcome.

    2. suppose you decide to compare two funding schemes, based on a sample of discoveries made under the two schemes

      what if instead of looking at the output (discoveries) you look at the input (the people, the ideas)

      For example: * What's the mix of applications to do the legwork to add/build evidence for a known question or theory where it is needed, versus pursuing shiny new ideas (hypotheses with no/low evidence as yet) * Who's applying for funding - and who is not applying. Is any scientist well-served somewhere within the funding ecosystem? If not, whose ideas and thinking are we (society) missing out on with the current funding scheme designs?

    3. "It's ridiculous to be comparing funding schemes at all".

      There's value in understanding the diversity of funding schemes.

      In a world with only one type of funding pattern, it's change within that structure or don't change.

      In a world with NIH grants and HHMI efforts and FROs and VCs funding individuals and scientist-entrepreneurs self-funding research from their own spin-outs, etc, etc, there's more opportunity to experiment with changes without requiring all funding to change.

    4. they're trying to identify companies different in some crucial, fundamental way than anything they've seen before. In that sense, they study the bulk of the curve in order to escape it

      chasing the new, the disruptor

    5. This implies two very strange rules for VCs. First, only invest in companies that have the potential to return the value of the entire fund. This is a scary rule, because it eliminates the vast majority of possible investments. (Even quite successful companies usually succeed on a more humble scale.) This leads to rule number two: because rule number one is so restrictive, there can't be any other rules.

      Facebook does not exist in a vacuum

      I think reducing the model to only evaluate for direct monetary profit is overly reductive model, even if VC's primary aim is monetary profit. For example, one company may not return the highest profit but may contribute some kind of technological or social advance that enables/augments profit (and further advance) from other companies. (i.e. how to include "enabling advances" in the evaluative model for VCs? Which previous smaller companies/contributions were necessary for Facebook to happen?)

      This multi-dimension model is closer to science too - there may be direct immediate gain from a discovery, but not recognising the enabling gain from other discoveries may lead to missing the opportunity to enable the next big discovery.

    6. it's extremely difficult to quantify the value of a discovery

      May be worth comparing UK REF to other models by which performance is evaluated in order to prescribe the next tranche of government (or other) funding.

  3. Aug 2021
  4. Feb 2021
    1. There is Microsoft Academic which after its relaunch in 2015 seems to be the closest competitor. The newt kid on the block is Semantic Scholar developed by the non-profit Allen Institute for Artificial Intelligence.

      Alternatives to GScholar - Semantic Scholar might be interesting for snowballing.

    2. Google Scholar does not return all resources that you may get in search at you local library catalog. For example, a library database could return podcasts, videos, articles, statistics, or special collections.

      See other sources for videos, podcast, grey lit

    3. Within your Google Scholar library, you can also edit the metadata associated with titles. This will often be necessary as Google Scholar citation data is often faulty.

      use GScholar library to edit then download citation data

    4. All the search results include a “save” button at the end of the bottom row of links, clicking this will add it to your "My Library".To help you provide some structure, you can create and apply labels to the items in your library. Appended labels will appear at the end of the article titles.

      Save interesting papers to check out later using Google Scholar (signed in my library) - click the star to save a listing, add tags to help with sorting / retrieving later.

    5. The Scholar Button is a Chrome extension which add a dropdown search box to your toolbar - allowing you to search Google Scholar from any website. Moreover, if you have any text selected on the page and then click the button it will display results from a search on those words when clicked.
    6. Adjusting the Google Scholar settings is not necessary for getting good results but offers some additional customization, including the ability to enable the above-mentioned library integrations. The settings menu is found in the hamburger menu located in the top left of the Google Scholar page.

      save time by setting up GScholar as needed in Settings

    7. The trick is to build a list of keywords and perform searches for them like self-driving cars, autonomous vehicles, or driverless cars. Google Scholar will assist you on that: if you start typing in the search field you will see related queries suggested by Scholar!

      GScholar search will help build search terms lists

    1. 8 Democratic Societal Collaboration in a Whitewater World David Lee, Margaret Levi, and John Seely Brown 9 From Philanthropy to Democracy: Rethinking Governance and Funding of High-Quality News in the Digital Age Julia Cagé 10 Technologizing Democracy or Democratizing Technology? A Layered-Architecture Perspective on Potentials and Challenges Bryan Ford

      Chapters to explore

  5. Nov 2019
    1. “(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention”
    1. Nearly half of our applicant survey respondents reported posting at least 1 preprint, with several commenting that preprinting provided evidence of productivity outside of formal publication. A number of applicants commented that preprinting provided evidence of productivity outside of formal publication. Search committee survey respondents further confirmed that while published papers carry the most weight, preprints are generally viewed favorably. Future use of preprints as evidence of productivity records may have significant positive impacts on early career researchers, for whom timing of publications and job searches require critical considerations.
    2. Our limited survey of the search committee faculty members provided various insights. The majority (67%) said preprints were viewed favorably, although their strength may not be equivalent to published peer-reviewed work (Table S33).
    3. Preprints, or manuscripts submitted to an open-access server prior to peer-reviewed publication, are becoming increasingly popular among early career researchers, particularly in the life sciences (33,34,35) and are shown to boost article citations and mentions (29–31,37). We opted to address whether this increase in preprint submissions had an impact on the academic job market. While not all respondents answered our questions about preprints, we did receive 270 responses on this issue. Our survey data showed that 55% of these respondents (148 candidates) had posted at least one preprint throughout their career and 20% had posted between 2-6 preprints with an average of 1.57 preprints per person throughout their career thus far (Figure 2E, Table S8, S15). At the time of faculty job application, 40% of these respondents had an active preprint that was not yet published in a journal, with an average of 0.69 active preprints per person. Preprinted research was enormously helpful for a number of candidates (who explicitly commented) that preprints served to demonstrate productivity before their paper was published (Tables S26, S27).
  6. Aug 2019
  7. Jul 2019
    1. If you (like me) don't have access to this paper, you're not going to see the note about additional materials in the paper.

      To help, you can find accessible materials about this research from the lab's website: https://www.crowtherlab.com/our-research/ which links to https://crowtherlab.pageflow.io/trees-against-climate-change-the-global-restoration-and-carbon-storage-potential#215055 . There are also lots of materials linked from their twitter profile (you need to login to twitter to find these, sorry): https://twitter.com/CrowtherLab.

      Such important work should not be published behind a paywall.

  8. Jun 2019
    1. Data for bioRxiv preprints from start to November 2018 (covering metadata and traction on social media)

      Continues to be updated, viewable from rxivist.org and associated Zenodo data records (see link from rxivist)

      Preprint available at https://www.biorxiv.org/content/10.1101/515643v2

    1. Data for bioRxiv preprints from start to November 2018 (covering metadata and traction on social media)

      Continues to be updated, viewable from rxivist.org and associated Zenodo data records (see link from rxivist)

    1. The sample of 776 published articles with preprints was matched to 3647 published articles without preprints. Published articles with preprints had significantly higher Altmetric scores than published articles without preprints (median, 9.5 [IQR, 3.1 to 35.3] vs 3.5 [IQR, 0.8 to 12.2], respectively; between-group difference, 4 [IQR, 0 to 15]; P < .001) and received more citations (median, 4 [IQR, 1 to 10] vs 3 [IQR, 1 to 7]; between-group difference, 1 [IQR, −1 to 5]; P < .001).

      Preprinted work gets more attention as a publication later than non-preprinted articles.

    1. Data for submission growth and co-authorship networks from the 9 largest OSF preprint servers (all started in the past few years)

      Preprint of this work is available at: https://osf.io/5fk6c/

    1. hidden systems

      Content not found on Prolifiko anymore. Content seems to be available as PDF from ResearchGate: https://www.researchgate.net/publication/265037737_Becoming_a_productive_academic_writer (I don't have an RG account so not checked & can't be sure this is the original content linked to.)

  9. May 2019
    1. If there are frequent unanimous decisions in any of your exercises, groupthink may be an issue. Suggest that teams investigate new ways to encourage members to discuss their views, or to share them anonymously.

      How to spot when groupthink is an issue.

    2. Advice for the Facilitator The ideal scenario is for teams to arrive at a consensus decision where everyone's opinion is heard. However, that doesn't always happen naturally: assertive people tend to get the most attention. Less forthright team members can often feel intimidated and don't always speak up, particularly when their ideas are different from the popular view. Where discussions are one-sided, draw quieter people in so that everyone is involved, but explain why you're doing this, so that people learn from it. You can use the Stepladder Technique   when team discussion is unbalanced. Here, ask each team member to think about the problem individually and, one at a time, introduce new ideas to an appointed group leader – without knowing what ideas have already been discussed. After the first two people present their ideas, they discuss them together. Then the leader adds a third person, who presents his or her ideas before hearing the previous input. This cycle of presentation and discussion continues until the whole team has had a chance to voice their opinions. After everyone has finished the exercise, invite your teams to evaluate the process to draw out their experiences. For example, ask them what the main differences between individual, team and official rankings were, and why. This will provoke discussion about how teams arrive at decisions, which will make people think about the skills they must use in future team scenarios, such as listening   , negotiating   and decision-making skills, as well as creativity skills for thinking "outside the box."

      Advice to avoid groupthink

  10. Apr 2019
    1. Pingback:

      Q: Where can I post a preprint?

      There are a number of preprint servers available, ranging from discipline specific servers to more broad servers, like SAGE’s own preprint server, Advance, that covers all research in the humanities and social sciences. For a comprehensive list of preprint servers, check out ASAPbio’s survey of preprint servers.


  11. Mar 2019
    1. Supplementary Tables and Figures[supplements/581892_file06.pdf]

      Supplementary tables and figures -- including survey and more complete description of results

    2. Supplementary File 2[supplements/581892_file05.txt]

      Analysis code (R) in .txt format

    3. Supplementary File 1[supplements/581892_file04.xlsx]

      Full raw survey data in .xlsx format

    4. Supplementary Text 1[supplements/581892_file03.pdf]

      PDF Instruction Manual of how to do the evaluation, as found on OSF: https://osf.io/4zk8x/

    1. I could not find the manuscript figures (or text) anywhere besides the PDF. Therefore, I had to take screenshots to extract the figures for my journal club presentation. It would be useful to add the figures to one of the existing repositories or data depositions.

      Rich Abdill has updated the Zenodo record with figure PDFs and made these CC0: https://zenodo.org/record/2603083#.XJUjbFP7SRs

      Version log note: "22 Mar 2019: PDFs of each figure from the paper have been added to the repository. In addition, the license has been changed from CC-BY-NC to CC0."

    2. It would be helpful, for example, to compare the number of bioRxiv postings to new articles added to PubMed each year.

      Agree. Jessica and I have been looking at this using prepubmed data and Pubmed numbers: from these, preprints are currently ~2% all biomedical literature each year and growing (slowly)

    3. access

      On the point re timing of downloads (before/after publication), Bianca Kramer has explored this question: https://twitter.com/MsPhelps/status/1089836238482403328

      Data & analysis at https://tinyurl.com/Rxivist-further-analysis (https://docs.google.com/spreadsheets/d/18-zIlfgrQaGo6e4SmyfzMTY7AN1dUYiI5l6PyX5pWtg/edit#gid=1455314569)

      OA status of journal does not seem to be a factor in the # or % of preprint downloads in the first year after journal publication --> suggests the correlation between IF & downloads is not related to the link between high IF and low OA.

    4. a useful feature
    5. Rxivist may also be of great utility to science journalists looking for preprints to cover.

      There is some debate as to whether preprints should be covered in the general media with some recommending that journalists do not report on a preprint: http://thenode.biologists.com/preprints-and-science-news-how-can-they-co-exist-a-meeting-summary/events/

    6. provides individually customisable searches of preprints for users, and this could be one avenue of growth for Rxivist.

      Also an interesting suggestion.

    7. this list in particular could help trainees looking for labs with progressive ideas about publishing (since getting on the leaderboard effectively requires posting multiple preprints).

      This is an interesting use case. I wonder if it might be worth repurposing on ECRcentral somehow?

    8. hope that it guides the efforts of organisations like ASAPBio in targeting funding agencies (for e.g. in the non-biomedical life sciences) and groups in their advocacy efforts.

      Absolutely, we plan to make use of these data and build on them to understand advocacy and outreach needs and opportunities. We welcome collaborations: please feel free to contact me on naomi dot penfold at asapbio dot org.

    9. the distribution of month-day publication dates for preprinted journal articles was more uniform:

      This is valuable information, thank you

    10. One interesting finding from this section is that three-quarters of preprint authors are only listed on a single preprint. Therefore, there are many researchers with exactly one preprint experience (and likely not as the submitting author). This finding may be helpful when designing outreach activities related to preprinting.

      Thank you for pointing this out. This is informative for ASAPbio outreach strategy.

    11. the publications-per-journal analysis in a later section could be contextualized by assessing the total number of articles published by each journal.

      Agree and willing to help with this.

    12. Disclosure: My annotations are provides from both professional and personal perspectives: I am Associate Director at ASAPbio, which works to promote the productive use of preprints in the life sciences. I am not affiliated with bioRxiv. The preprint first author, Rich Abdill, has joined the ASAPbio ambassador group since posting this preprint.

    13. My personal view is that the healthiest ecosystem for modernizing scholarly communication should have multiple preprint repositories to allow the most innovation and competition. Hopefully, preprint servers can begin to report similar data in standardized formats, such that resources like Rxivist can easily pull data from all compliant preprint servers.

      I agree (personal opinion).

      We’d (ASAPbio) like to produce similar and extended analysis that covers more preprint servers. Now advertising for a Vsiitng Scholar to work with Juan Pablo Alperin and colleagues at ScholCommLab: https://www.scholcommlab.ca/join-us/vsp-preprints/

    14. It would be helpful to add a visualization of the database schema to the Methods to help readers quickly surmise the contents of the database. This schema should be automatically generated from the PostgreSQL database.

      Wholeheartedly agree, would be very useful!

    1. Why did some practices not implement new antibiotic prescribing guidelines on urinary tract infection? A cohort study and survey in NHS England primary care

      An earlier version of this work is available as a preprint on bioRxiv: https://doi.org/10.1101/355289

      Disclosure: I work for ASAPbio, a non-profit organisation working to improve transparency in science, including through the productive use of preprinting in the life sciences.

    1. Neuronal Origin of the Temporal Dynamics of Spontaneous BOLD Activity Correlation

      An earlier version of this work is available as a preprint on bioRxiv: https://doi.org/10.1101/169698

      Disclosure: I work for ASAPbio, a non-profit organisation working to improve transparency in science, including through the productive use of preprinting in the life sciences.

    1. Refresh my memory: Episodic memory reinstatements intrude on working memory maintenance

      An earlier version of this work is available as a preprint on bioRxiv: https://doi.org/10.1101/170720

      Disclosure: I work for ASAPbio, a non-profit organisation working to improve transparency in science, including through the productive use of preprinting in the life sciences.

    1. Working Memory Load Modulates Neuronal Coupling

      An earlier version of this work is available as a preprint on bioRxiv: https://doi.org/10.1101/192336

      Disclosure: I work for ASAPbio, a non-profit organisation working to improve transparency in science, including through the productive use of preprinting in the life sciences.

    1. A 2.8-Angstrom-Resolution Cryo-Electron Microscopy Structure of Human Parechovirus 3 in Complex with Fab from a Neutralizing Antibody

      An earlier version of this work is available as a preprint on bioRxiv: https://doi.org/10.1101/410217

      Disclosure: I work for ASAPbio, a non-profit organisation working to improve transparency in science, including through the productive use of preprinting in the life sciences.

    1. A neurodevelopmental disorder caused by mutations in the VPS51 subunit of the GARP and EARP complexes

      An earlier version of this work is available as a preprint on bioRxiv: https://doi.org/10.1101/409441

      Disclosure: I work for ASAPbio, a non-profit organisation working to improve transparency in science, including through the productive use of preprinting in the life sciences.

    1. Why Are CD8 T Cell Epitopes of Human Influenza A Virus Conserved?

      An earlier version of this work is available as a preprint on bioRxiv: https://doi.org/10.1101/408880

      Disclosure: I work for ASAPbio, a non-profit organisation working to improve transparency in science, including through the productive use of preprinting in the life sciences.

    1. Hemagglutinin Stalk-Reactive Antibodies Interfere with Influenza Virus Neuraminidase Activity by Steric Hindrance

      An earlier version of this work is available as a preprint on bioRxiv: https://doi.org/10.1101/400036

      Disclosure: I work for ASAPbio, a non-profit organisation working to improve transparency in science, including through the productive use of preprinting in the life sciences.

    1. critics worry that grant reviewers will not be able to distinguish between peer-reviewed research and early data, and that the policy will promote hype of incomplete results.
  12. Dec 2018
    1. Daniel Himmelstein (UPenn)

      See Daniel's blog about the impact of licensing choice, and current choices by authors (at time of writing), which includes an interesting footnote about what happened when biorxiv presented the most open license (CC-BY) at the top of their options: https://blog.dhimmel.com/biorxiv-licenses/

  13. Oct 2018
    1. Latour never sought to deny the existence of gravity. He has been doing something much more unusual: trying to redescribe the conditions by which this knowledge comes to be known.

      The process matters, as does who gets to be involved in it.

    2. As Latour has long maintained, critical-zone scientists themselves — like many environmental researchers — play a part in the cyclical processes they study: Others use their research to make changes to the very environment they are measuring, in turn challenging the traditional image of scientists as disinterested observers of a passive natural world.

      Highlights responsibility on shoulders of people who share results/interpretations upon which recommendations are built

    3. They tackled the comments with playful self-deprecation.

      Example of making the process of improvement fun, removing barriers to criticism.

    4. encouraging scientists to include humans as a variable in their studies.

      Allow people ownership of the method, to improve trust in the results

    5. limit their domain to science, thinking it inappropriate to weigh in on political questions or to speak in an emotional register to communicate urgency

      counter-movement: #ScienceIsPolitical

    6. Far from simply discovering facts, scientists seemed to be, as Latour and Woolgar wrote in “Laboratory Life,” “in the business of being convinced and convincing others.” During the process of arguing over uncertain data, scientists foregrounded the reality that they were, in some essential sense, always speaking for the facts; and yet, as soon as their propositions were turned into indisputable statements and peer-reviewed papers — what Latour called ready-made science — they claimed that such facts had always spoken for themselves. That is, only once the scientific community accepted something as true were the all-too-human processes behind it effectively erased or, as Latour put it, black-boxed.

      Instead of presenting observations and what they might mean, we sell stories and narratives about what they do mean. The best-connected storyteller has a network advantage and tends to out-market alternatives. Discussion about whether this is valid or not is forgotten after publishing when peer review is assumed done and dusted.

    1. Statement from Global Young Academy about Plan S: conceiving worst case and best case scenarios, and calling for ECRs to be involved in implementation discussions.

      A worst case scenario: OA journals have uncontrolled APCs (in the long term, short-term cap is insufficient) and OA excludes those who can't pay to publish, thus widens inequalities.

      A best case scenario: publishers receive funding from funders to act as a service, no reader or author has to pay. Publishers are evaluated for the service they provide and thus the academic community can reward the better services, and good OA publishing thrives.

  14. Aug 2018
    1. potentiall


    2. these

      typo? 'the' reads better

    3. Dokie.li

      This writes to HTML, right? Might be worth stating that, as this follows discussion of potentially writing in JATS XML.

    4. but impractical to non-technical users

      A larger problem may be that (as I understand it) there is currently no agreed 'common' JATS XML from which content disseminators could then specialise. So agreeing a flavour of JATS XML to write in may be a bigger issue. Same applies to the markdown conversion point.

    5. Archival is facilitated by making it trivially easy to create local copies of large sets of content

      Is it possible to create a tool that warns you when fewer than 3 peers hold any of your registered content?

    6. open by design


    7. peer to peer

      peer-to-peer (for consistency)

    8. The private information will then not be available in the version history of the Dat filesystem.

      Note to self: this might require tooling that ensures the content creator has checked for private info before sharing, much like authors should check before they post a preprint or dataset and developers should check for passkeys etc before they push code. Errors still occur in those cases.

    9. By including only versioned links the registrations are specific and unique.

      Does the researcher draft the between-version contents within their local filesystem, i.e. akin to my local .md files that I only push to github once I'm ready?

      UPDATE: Yes, stated in next section.

    10. and can also help improve secure and private transferring of sensitive data

      This phrase doesn't seem to follow grammatically from the rest of the sentence: it is not clear what "can also help improve...".

      Do you mean "However, because... not mediated. This can also help..." ?

    11. Alice her

      Typo? Alice's or her?

    12. scholarly profile metadata

      Are these terms compliant with schema.org where appropriate? That might help with interoperability with current systems. That said, I don't know how much ORCID or others comply with schema.org.

    13. researchers can modify their profiles freely because they retain full ownership and control of their data

      What impact do you foresee on the degree of trust the community at large places on a profile that is not under centralised 'perceived-to-be-authoritative' control? Is that trust required or is this a notion from a centralised authority state?

    14. Figure 1

      I found the double-ended arrows in this quite confusing (direction versus type not clear). Potential alternative: a shape that widens where 'more', narrows where 'less', so the type is labelled in text but the quantity is depicted pictographically by width of the line/shape.

  15. Jul 2018
    1. Fully reproducible code is available in the form of jupyter notebooks (https://jupyter.org) with instructions to install all necessary software, download sequence data, assemble it, and run genomic analyses (https://github.com/dereneaton/Canarium-GBS) (DOI 10.5281/zenodo.1273357). For all genomic analyses in this study we used the ipyrad Python API and the ipyrad-analysis toolkit (https://github.com/dereneaton/ipyrad) which provides a set of wrappers around common genomic analysis tools to run highly parallelized analyses using simple Python scripts.

      Example of author sharing all code via jupyter notebooks in a github repo. They have archived to Zenodo and include both URLs in the text. Their analysis relies on an existing toolkit - it is not obvious from the manuscript whether this toolkit has been deposited anywhere.

      Journal: PLOS ONE Subject area: plant biology, ecology (check?)

    2. We used the program STRUCTURE v2.3.4 [16]

      Cited reference is open access and describes the method

    3. NA extractions were attempted for all taxa for which recent and sufficient tissues were available. Of the samples that were successfully extracted, at least two individuals for each taxon were included when available. This yielded 44 Malagasy Canarium accessions, to which we added an additional four Southeast Asian Canarium species to serve as outgroups. Genomic libraries were prepared for genotyping-by-sequencing (GBS) following the protocol described by Escudero et al. [14], but with the addition of a size selection step. After restriction digestion, fragment sizes were visualized on an Agilent 2100 Bioanalyzer and selected in the range of 300–800 bp using a Pippin Prep system. The final library containing 48 barcoded individuals was sequenced on two lanes of an Illumina HiSeq 2500 at Yale University’s Center for Genome Analysis to generate 75 bp single-end reads.

      Protocol not fully open. Based on closed access paper. Extension to method is clearly described.

    4. Fully reproducible code is available in the form of jupyter notebooks (https://jupyter.org) with instructions to install all necessary software, download sequence data, assemble it, and run genomic analyses (https://github.com/dereneaton/Canarium-GBS) (DOI 10.5281/zenodo.1273357). For all genomic analyses in this study we used the ipyrad Python API and the ipyrad-analysis toolkit (https://github.com/dereneaton/ipyrad) which provides a set of wrappers around common genomic analysis tools to run highly parallelized analyses using simple Python scripts.

      Well-described dry lab notebooks with open code, and Python analysis toolkit is open source.

    1. Source code of the model presented here is available on GitHub (https://github.com/lukasgeyrhofer/phagegrowth) (Payne et al., 2018) and its archived version is accessible through Zenodo: https://dx.doi.org/10.5281/zenodo.1038582 and https://github.com/elifesciences-publications/phagegrowth.

      Example of authors archiving their own code. The eLife process is to fork the author's repo to the eLife github repo to save a snapshot of the repo at the time of acceptance. The authors here have also chosen to archive to Zenodo (via the Github release --> Zenodo mechanism?). Both the Zenodo DOI and the eLife fork are included in the text as archive/snapshot copies of the original (also cited).

      Note the author's original repo is included in the references.

      Journal: eLife Subject area: ecology, evolutionary biology

    2. doi: 10.5281/zenodo.1038582RRID:SCR_004129Zenodo repository

      In this example, the archived code repository has been listed in the eLife Key Resources Table

    1. PLOS ONE publish papers with minimal evaluation

      I think PLOS ONE would disagree: their review is based on scientific validity, just removes the branding element. It's still supposed to be rigorous.

    2. Post-publication peer review in its most validated form, involves a journal such as Frontiers asking academics to perform a published interactive dialogue with authors during the review process, giving a level of accountability and responsibility.

      I don't understand this definition - this sounds like transparent review to me, not to do with post-publication.

    1. Scientific progress and human and environmental well-being are our collective responsibility. Open exchange of people and ideas are key to fulfilling such collective responsibilities. If you have the opportunity, please help to facilitate more open exchange, of talent and of knowledge. If you are in academia, share your publications, share your teaching materials, share your code, share your data, share your time. Support and encourage visits to your institution, based on scientific excellence only. If you’re from a country that’s ranked high on the Passport Index, go and visit other institutions around the planet and share your expertise. I believe that every bit helps. For my part, I’ll try to raise 100K Euro per year, over the next 10 years, to bring an information retrieval researcher to my university for a 12-month visiting position. Scientific excellence will be the entry ticket, not the country in someone’s passport.

      a Dutch researcher not allowed into US due to a trip to Iran to present research and meet researchers there.

  16. Jun 2018
    1. publish a cannabis genome to a blockchain

      This suggests they are publishing the genome itself to the dash blockchain — this is incorrect. The proposal actually says they are publishing the record of production of new strains of cannabis to the dash ledger such that they can prove they created a new strain (and when) and thus protect themselves from patent trolls. As a colleague said, they could then share the hash of the hash with the patent office. https://www.dashcentral.org/p/MedicinalGenomics

    1. reach out to her

      Please hyperlink:


    2. . S

      Include extra sentence?

      "Key learnings were that inclusivity is really hard, designing for including participants in the programming helps folks to make it work for them, and that the quality and attitude of the people in the room really mattered for how successful the event was so curation of those people was crucial."

    3. Long term


    4. Rik Smith-Una / ScienceFair


    5. the event
    6. experience with planning

    7. the


    8. offline friendly


    9. offline friendly


    10. mobile friendly


    11. going

      is going

    12. list(

      separate with space

    13. years

      one year's or many years' ?

    14. databse


    15. sponosored


  17. May 2018
    1. Interesting comment on this preprint from Gaetan Burgio

      "This fascinating paper shows that prestige is a major driver in #academia for 1) Faculty hiring 2) diffusion of scientific ideas leading to media release, citations, conference invitations .... In short #academia is not a place for meritocracy #ECRchat"

      Source: https://twitter.com/GaetanBurgio/status/1001042437953937408

    1. A separate analysis of the Wikimedia data dump by Ross Mounce, who directs open-access programmes at the London-based philanthropic foundation Arcadia Fund, reveals the ten most-cited DOI articles across all of the encylopaedia’s language editions (see ‘All Wikipedia language editions’). Six of the articles are the same, but the first entry is notably different. The top-referenced DOI article is a 2007 paper updating a century-old classification of the global climate, which has a whopping 2.8 million citations — but only 169 on English Wikipedia (the second-most-cited source across all editions has just over 21,000 references).The climate study is so heavily cited because millions of its citations come from pages created by an automated computer program. The bot, developed by physicist Sverker Johansson at Dalarna University in Falun, Sweden, had produced nearly 3 million articles as of July 2014, according to Wikipedia. One-third of the articles are in Swedish and the rest are in Cebuano and Waray, two languages spoken in the Philippines. The bot has produced millions of articles about geographic locations such as towns and islands, and most of those articles include information about the local climate type, which reference the climate study, says Johansson. He adds that he has no precise figures for the bot-generated citations of the climate paper, “but 2.8 million is in the right ballpark”.

      This was done at the eLife Innovation Sprint, May 10-11, 2018. The work is documented at: https://github.com/rossmounce/DOIs-in-Wikipedias

  18. Dec 2017
    1. Wikimedia Resource Center

      Could we do this for open science?

    2. Thalos is a secure and distribuited system for file storage in cloud

      Q for myself: How is this different to Dat? Investigating on Thursday.

    3. HBASet: Polygenic expression maps of the brain

      How is this different to the Allen Institute resources? From the project GitHub: "these valuable resources are underused for the analysis of polygenic brain disorders because the data is not easily accessible beyond the level of a single gene." From experience, I'd agree.

    4. How does research treat underrepresented minorities?

      Watch this

    5. Planet Friendly Web Guide

      Watch this. Any simple rules to bear in mind for new innovations?

  19. Nov 2017
    1. References

      Explore these

    2. Research Data Infrastructures in the UK Open Research Data Task Force (2017) London: Universities UK.

      Can't find this anywhere.

  20. Oct 2017
    1. What if there were a model in which commercial players could develop and support open infrastructure using service-based business models that didn’t involve ownership of this infrastructure or create dependencies on any single provider? What would a system like that look like?

      It would be good to share clear examples of these.

      Where's the upfront investment to get this kind of model going? (That's what VC does; substantial amounts are needed, which is risky for the grant route.)

      How would this be sustainable in the long run? (Several examples, need to examine both successful and unsuccessful.)

    2. groups like Crossref and ORCID are starting to develop open alternatives
  21. Sep 2017
    1. Rossner and Yamada 2004, Cromey 2010

      See also Bik, Casadevall and Fan (2016) about the prevalence of image duplication in biomedical literature. Prevalence about 4% articles in most recent end of dataset (2014). http://mbio.asm.org/content/7/3/e00809-16.full

    1. The idea of classifying hypotheses as supported or refuted by ongoing works, as a means to identify "strongly supported" or "strongly refuted" claims is an interesting one. I would like to see further discussion of how this could be applied.

      Namely, it seems the R-factor is something that should be applied to a specific scientific claim, as opposed to a whole research article. Being able to quickly identify the evidence that supports (green), refutes (red) or relates unclearly (yellow) to a claim, directly from the claim in said literature, could aid comprehension (not to mention discoverability) of the surrounding literature, and highlight claims that are well-supported or lacking in independent replications. Do the authors feel that one paper is sufficiently related to one central claim for application of the R-factor the the paper? Alternatively, I would argue that judging the "veracity" of component evidence presented within an article could be more informative.

      Further, limiting these data to the "cited by" literature from that paper could skew the perspective, depending on which article you are viewing the claim in - to understand the overall "veracity" of a claim, it seems the reader would need to navigate back to the first mention of that claim in order to find the longest chain of evidence. Instead, I would be interested to explore the feasibility of a claim-centric (as opposed to paper-centric) count, and to understand whether this is already achieved by existing practises (such as meta-analyses of the literature). Perhaps an alternative approach would be to ensure that meta-analyses that include an article are more clearly visible from that article (e.g. highlighted in a "cited-by" section), and an extension to that would be to link that more recent work to the specific assertions that it relates to in the current article.

      I would also be interested in whether the authors' have any thoughts on the reporting bias towards positive results (it may be hard to judge replicability, if failed replications remain in desk drawers), as well as on more nuanced evaluations of related evidence: is some evidence stronger than others? Is it feasible to define a scientific claim, or is it dependent on context/species/other factors?

      Finally, I would be concerned about applying such a metric to individual researchers. An examination of unintended consequences for such a metric would be useful to discuss.

      Competing interests: None identified. Full disclosure: I am Innovation Officer at eLife. My academic background is not in meta-research of reproducibility.

  22. Jul 2017
    1. Change article-to-journal from 1:1 to 1:many. If journals' role is focused on peer review rather than publication, then we can broaden the model so that the same paper can appear in many 'journals'


      Is the journal's role there to act as a channel - and the individual chooses their preferred channel?

      Who takes on responsibility for good production (links, etc) as mentioned earlier? Surely don't want duplication of efforts there. Or is that what occurs in step before journals come in and present published papers?

    2. re-mix or re-presentation so that the remixed information is accessible and useful to the right reader at the right time, in the right place and in the right format

      Would love to dig into more detailed imagined use cases here.

    3. The document would be stored as XML or some other machine readable format, so the reader can be offered a choice of format.

      It should already be?

    4. generated structure and preserved links. To cite in the introduction, you'd just highlight text & paste in the identifier

      This would make it easier to trace the context of a citation, in a way that researchers could flag inappropriate or misleading citations, as well as judge whether a citation to a retracted article is erroneous or intended.

    5. We end up with a big package of research objects and metadata well integrated with each other. With time, each element can evolve based on further work by the authors or community feedback—it’s a ‘living article’—and this evolution is tracked for the record and provides credit to the contributors

      Akin to the Crossref 'article nexus' model https://www.crossref.org/blog/the-article-nexus-linking-publications-to-associated-research-outputs/

      I think a place to surface all the associated content with the article is missing right now.

    6. a place where the information is marked as assessed (with reviews named and available)

      What level of assessment? Is this journal-independent?

      We've talked about these levels:

      • quick QC before preprint posting (but minimal so as not to block)
      • assessment of scientific rigour (traditional peer review)
      • identifying research that peers deem to be particularly important / groundbreaking / of interest to a wider audience (a place for journals?)
    7. through dynamic links that allow for versioning, forking, and (for narrative) threading

      Love this idea!

  23. datproject.org datproject.org
    1. Dat by default only stores the current set of checkedout files on disk in the repository folder, not oldversions

      Are the old versions still retrievable in some way?

    2. Sources Dat is able to connect to go into a list ofknown good sources, so that the Internet connectiongoes down Dat can use that list to reconnect to knowngood sources again quickly.

      How does this benefit people working in areas of intermittent internet access?

      Currently, they would store data they need locally. Does this mean they can share it P2P, reduce the amount they store locally, yet still be able to access it even when internet down?

    3. Dat does not provide an authentication mechanismat this time.

      An authentication system could be useful for protected data (e.g. patient, clinical, personal data, where researchers must prove identity and be granted right to access data for further research). It may be worth looking into how this is currently managed and whether Dat could make it easier for these administrators.

    4. Link rot, when links online stop resolving

      This shouldn't be a problem for scientific datasets as they have DOIs. Have I misunderstood?

    5. Hashes are arranged in a Merkletree,

      For clarity, a diagrammatic representation of this could be useful (I'm a more visual learner)

    6. It also has implications for reproducibilityas it lets you refer to a specific version of a dataset.

      Does this mean that a journal could point to a specific version of a dataset, pertaining to that which a peer-reviewed article is based on? This version of record is important.

      An additional link could then point forward to the most up to date version of the data, with a summary of the changes made since the publication version?

    1. To help chip away at this question, we’re publishing a series of articles from researchers leading initiatives to improve how academics are trained, how data are shared and reviewed, and how universities shape incentives for better research.

      Inside Higher Ed to publish series of blogs from researchers working on open science

    1. there are already scientists thinking in this direction

      Have you also heard about Dat and IPFS? https://datproject.org/ https://ipfs.io/

      And this blog: https://chartgerink.github.io/2017future/

    2. forced to charge researchers a hosting fee

      The publication fee is not simply a hosting fee. Actually, a third of the current cost per published article is due to the scientific editors being recompensed for the work they do in peer review - see more at https://elifesciences.org/inside-elife/a058ec77/what-it-costs-to-publish. Ideally, the scientist should be free to choose between services to disseminate their research, from simple cheap servers that just upload to the web, to more costly peer-reviewed destinations that employ staff to manage press, outreach, and so on.

    3. The often tragic stories of scientific software startups

      Are you able to provide some key examples here? Do you think it is possible to avoid this situation?

  24. May 2017
    1. Brewster Kahle

      Have you shared this with him?

    2. to obfuscate the author’s identity

      Permanently? Or would the researcher be identifiable in some way somewhen later?

      The reason I say this is that there may be some researchers who never want to be identifiable, particularly if their work is politically sensitive. Of course, there's a counter-argument for non-anonymity in order to have accountability.

    3. Alternatively, files could be encrypted and deposited at the same time as the entry to the ledger is made, where the private key needed to decrypt the files could be provided at the “time-available”. A system that incorporates “time-available” moves the discussion of whether materials should be shared at all to when they can be shared (i.e., not much can be justified to stay unavailable into perpetuity).

      Importantly, this decouples the act of preparing all the information for sharing from the time of being ready to share, such that the information sharing is of the highest quality (soon after the event) whilst acknowledging that research is not open-by-default and there are socioeconomic factors why it may never be (even in the new system proposed here).

    4. Although explaining the entire operating principle of the blockchain is beyond the scope of this piece, the essence is relatively simple.

      If you could add emoticon reactions via hypothes.is, right now I'd be struggling between a +1, a laughing face, and any representation that means 'my brain hurts when I think about blockchain'

    5. revenue could be built with usage fees to that service instead of the content

      Any paid service that enables the payee to gain greater access to research (by efficiency of discovery) could also contribute to inequality. Those with money can produce more work faster simply because they've been able to access the right information more quickly, and thus the cycle perpetuates. What do you think about this?

    6. needed to understand what steps were taken

      Or to learn the best practises outside of the limited physical places in an expert lab group, thus limiting who can contribute to the pursuit of knowledge creation.

    7. these implicit parts are finally able to show themselves

      More moments of communication that incorporate the many steps in research, i.e. pre-registered report, micropublications, data articles, software packages, evidence reviews to bundles small steps into larger breakthroughs in understanding --> opens up credit for all types of researchers: from the idea-generators, to the expert-practitioners (wet lab, data, etc) and values all contributions to the main goal: finding the/an answer to the question.

  25. Apr 2017
    1. subject-specific and gen-126eral repositories for data storage,

      Would you consider DataCite's re3data (searchable and filterable database of data repositories) another useful resource here? http://www.re3data.org/

  26. Mar 2017
    1. a local text file

      Is it ok to work straight into the issue template?

      Or is it best to copy the template into a local text file, edit that from the research, then submit?

    2. local text file

      jump to the template? and a quick how-to (copy and paste this template into a text editor e.g. wordpad, whatever)?

    3. that nobody else has claimed yet

      Is there an easy way to organise these as claimed / unclaimed? At the mo, I'm copying the ID then ctrl+f in the spreadsheet to cross-reference.

    4. the use of the platform

      I'd love to see a how-to guide come out of this.

      We've just tried to make one, see 'Beginner's Guide to Github' at: https://docs.google.com/document/d/1gTdPPr0ZMCKv5X-_XL9au6buwV6Fz194djjw3YXSFvs/edit#

      • written by me, a github beginner, so edits and corretions very welcome!
  27. Dec 2016