**Webinar Recordings** - [Applying Open Science Practices to Your Research][1]. A webinar for the influenza research community. Oct 18, 2021 - [Using Open Science in Your Research With OSF][2]. October 13, 2021. (password 626Fs9b^) - In this webinar, COS provides an overview of why institutions and researchers should apply open science practices to their work. [Link to recording from 20 August, 2021][3] - In this webinar, COS provides an overview of educational content to help individuals know where to go when getting started with open science. [Link to webinar recording from 8 July, 2021][4] @[toc](Overcoming the knowledge barrier. Getting started with open science and knowing where to go.) ## Preregistration and Registered Reports ## ### Background reading and resources ### - [The Preregistration Revolution][5] - The UK Reproducibility Network's (UKRN) [primer on pre-registration and registered reports][6]. - [Practical considerations for navigating Registered Reports][7] (with [accompanying OA materials][8]) - Evidence of its need and effect [on this annotated reading list][9]. - [More examples, templates, and reading available here][10]. ### Examples ### - [OSF Registry][11] - [OSF Registry, filtered by several common templates][12] - [A curated wiki of high quality, clear preregistrations][13] - [Articles that won the Prereg Prize for reporting the results of preregistered research][14] - [Badged articles][15] (Articles that share data (blue), materials (orange), or preregistrations (red)) ## Coded analysis and statistical planning ## ### Primers ### - [Open Code and Software: a Primer from UKRN][16] - [Good enough practices in scientific computing][17] - "This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill. These practices, ... encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts..." - [Getting Started with Git][18] - GitHub is a great way to work on version controlled code or projects in a way that let's you keep track of issues as they arise. ### Online courses ### - [Improving your statistical inferences][19] (Coursera, Lakens) - [Statistics with R Specialization][20] (Coursera, Duke) - [Data Scientist with R][21] (Datacamp) - [Statistics and R][22] (Harvard) - [Learn R][23] (CodeAcademy) ## Data Transparency ## ### Primers and tutorials ### - [Practical Tips for Ethical Data Sharing][24] - "This Tutorial provides practical dos and don’ts for sharing research data in ways that are effective, ethical, and compliant with the federal Common Rule." - [How to make a data dictionary][25] (or "codebook") - A data dictionary tells others (including your collaborators, lab members, and your future self!) the exact meaning of each data item you collect. - [Data Sharing: a Primer from UKRN][26] - Includes considerations of human data, consent, anonymisation, and protected access. - [Recommended language for informed consent with data sharing in mind.][27] ### Data Management Plans ### - [COS guides on creating a data management plan (DMP) document][28] - [DMPTool][29] ## Preprints ## - [ASAP Bio][30] - [OSF Help Guide on Preprints][31] - [Preprints: a Primer from UKRN][32] ## The Open Scholarship Knowledgebase (OSKB) ## Discover open scholarship resources created and curated by the research community. The [OSKB][33] collects education materials for researchers (and other stakeholders, such as funders or librarians) in collections for data analysis, publishing practices, and reproducibility. - [Researchers][34] ## General resources for open science across disciplines ## - [NIH Clearinghouse for Training Modules to Enhance Data Reproducibility][35] - These modules, comprised of videos and accompanying discussion materials, were developed by NIH, and focus on integral aspects of rigor and reproducibility in the research endeavor, such as bias, blinding, and exclusion criteria. The modules are not meant to be comprehensive, but rather are intended as a foundation to build on and a way to stimulate conversations. - [UKRN's Collection of Primers for Open Research][36] - "Each primer includes an overview of the topic in the introductory “What?” section, reasons for undertaking these practices in the “Why?” section, followed by a longer “How?” section that provides guidance on how to do that open research behaviour practically." - [General Principles of Preclinical Study Design][37] - "In this chapter, we will focus on hypothesis testing type of preclinical studies and explain general concepts and principles in relation to the design of in vivo experiments, provide definitions of experimental biases and how to avoid them, and discuss major sources contributing to experimental biases and how to mitigate these sources." - [Striving for transparent and credible research: practical guidelines for behavioral ecologists][38] - "...we present clear guidelines and tutorials on what we think open practices represent for behavioral ecologists. In addition, we indicate some of the currently most appropriate and freely available tools for adopting these practices." - [Detecting and avoiding likely false-positive findings – a practical guide][39] - "...we highlight promising strategies towards making science more objective. Specifically, we enthusiastically encourage scientists to preregister their studies..., to blind observers to treatment groups during data collection and analysis, and unconditionally to report all results..." - "[A Practical Guide for Transparency in Psychological Science][40]" - "we provide a practical guide to help researchers navigate the process of preparing and sharing the products of their research (e.g., choosing a repository, preparing their research products for sharing, structuring folders, etc.)." - [COS Webinars][41] - [Open and Reproducible Research on Open Science Framework][42] - This protocol gives authors step-by-step instructions for using the free and open source Open Science Framework (OSF) to create a data management plan, preregister their study, use version control, share data and other research materials, or post a preprint for quick and easy dissemination. - Framework for Open and Reproducible Research Training ([FORRT][43]) - FORRT provides a pedagogical infrastructure designed to support the teaching and mentoring of open and reproducible science tenets in tandem with prototypical subject matters in higher education. ## Open Science Communities ## - Society for the Improvement of Psychological Science ([SIPS][44]) - Society for Open, Reliable, and Transparent Ecology and Evolutionary Biology ([SORTEE][45]) - [STEM Data Hub - Open Science in Education Research][46] - [Network of grassroots open science communities][47] - [Carpentries][48] **Start your own open science community** - [Open Science Community Starter Kit][49] - [ReproducibiliTea][50] [1]: https://cos-io.zoom.us/rec/share/yhPQWc8kciORl1iGdA5SBY9jQ9c4QY-USek63b5DfXFBx52MfeGMF8osGtYLRE1Y.Z9Opz52rj0jimMd8 [2]: https://cos-io.zoom.us/rec/share/BK36v-0pPoyrSgH25xrwj66fo0Bg1uUbEfQpTSN87GvlivwGiLm7wg1wKRPo2H70.ZgV3db0wRkUX0sNF [3]: https://cos-io.zoom.us/rec/share/_V4CpWfdWfJPPPzn4wYAJ5YKJE8IpDXsHP-cIrrM427kmmaAIQByHP-vBq-8fyKC.NWsqMjhL6NlLfkNi?startTime=1629486321000 [4]: https://www.youtube.com/watch?v=UKcaugb9HAA [5]: https://www.pnas.org/content/115/11/2600 [6]: https://osf.io/8v2n7/ [7]: https://www.cell.com/trends/neurosciences/fulltext/S0166-2236%2819%2930124-9 [8]: https://osf.io/5gazv/wiki/home/ [9]: https://osf.io/kgnva/wiki/Open%20Science%20Literature/ [10]: http://cos.io/prereg [11]: https://osf.io/registries [12]: https://osf.io/registries/discover?provider=OSF%20Registries&type=OSF%20Preregistration%7CPrereg%20Challenge%7CPreregistration%20Template%20from%20AsPredicted.org [13]: https://osf.io/e6auq/wiki/Example%20Preregistrations/?view [14]: https://www.zotero.org/groups/479248/osf/collections/D77RMN4N [15]: https://www.zotero.org/groups/2146879/open_science_badges/library [16]: https://osf.io/qw9ck/ [17]: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005510 [18]: https://towardsdatascience.com/getting-started-with-git-and-github-6fcd0f2d4ac6 [19]: https://www.coursera.org/learn/statistical-inferences [20]: https://www.coursera.org/specializations/statistics [21]: https://www.datacamp.com/tracks/data-scientist-with-r [22]: https://online-learning.harvard.edu/course/statistics-and-r?delta=2 [23]: https://www.codecademy.com/learn/learn-r [24]: https://journals.sagepub.com/doi/10.1177/2515245917747656 [25]: https://help.osf.io/hc/en-us/articles/360019739054-How-to-Make-a-Data-Dictionary [26]: https://osf.io/wp4zu/ [27]: https://osf.io/g4jfv/wiki/Consent%20Forms/ [28]: https://help.osf.io/hc/en-us/articles/360019931133-Creating-a-data-management-plan-DMP-document [29]: https://dmptool.org/ [30]: https://asapbio.org/ [31]: https://help.osf.io/hc/en-us/articles/360021566914-Preprints [32]: https://osf.io/m4zyh/ [33]: https://www.oercommons.org/hubs/OSKB [34]: https://www.oercommons.org/groups/researchers/5050/?__hub_id=76 [35]: https://www.nigms.nih.gov/training/pages/clearinghouse-for-training-modules-to-enhance-data-reproducibility.aspx [36]: https://www.ukrn.org/primers/ [37]: https://link.springer.com/chapter/10.1007/164_2019_277 [38]: https://academic.oup.com/beheco/article/28/2/348/3069145?login=true [39]: https://onlinelibrary.wiley.com/doi/full/10.1111/brv.12315 [40]: https://online.ucpress.edu/collabra/article/4/1/20/112998/A-Practical-Guide-for-Transparency-in [41]: https://www.cos.io/services/webinars [42]: https://currentprotocols.onlinelibrary.wiley.com/doi/full/10.1002/cpet.32 [43]: https://forrt.org/ [44]: http://improvingpsych.org/ [45]: https://www.sortee.org/ [46]: https://www.cos.io/communities/stem-education-hub [47]: https://groups.google.com/a/cos.io/g/network-of-open-science-grassroots-networks [48]: https://carpentries.org/ [49]: http://startyourosc.com/ [50]: https://reproducibilitea.org/