OAWeek 2024: Intrinsic and Extrinsic Approaches to Open Access

This post is in celebration of Open Access (OA) Week 2024. The theme for this year is "Community over Commercialization". 

How do we incentivize people to adopt Open Access practices? We can take lessons from motivational Psychology to think about routes to better practice. Before doing so, we need to consider the current (and often sorry state) of open access.

It could be argued that in some important ways, Open Access has failed. The system of access to academic goods as currently structured is built on significant benefits to publishers and costs to libraries and authors. This benefit has been accrued by publishers due to reputational benefits: being published in Nature, Science, or Cell is highly prestigious. Yet the benefits of this prestige are necessarily limited to a few groups with lots of resources. And the beneficial attributes of open access have been captured by commercial entities. Similar problems plague the open-source community, a shift to the open ethos is the only way out.  

The different types of open access also play different roles in the marketplace of academic goods. Green open access, or self-archiving artifacts, are community goods. While this can be susceptible to the tragedy of the commons, proper social investment can ameliorate maintenance and growth imperatives. This is often seen as the highest standard for open access but requires community investment. Building a sustainable infrastructure of preprints, open peer review, and overlay journals has been elusive.

The Economic Benefits and Costs of Different Colored Access

Black open access using tools such as Sci-Hub is considered piracy (hence the "black" label). From an economic perspective, piracy is symptomatic of a dysfunctional market. Indeed, part of open access' failure is due to the dominant position of publishers and their own economic imperatives. In fact, black open access can be considered a rational response to closing access to article in a research culture of sharing and finding alternate routes to success [1-3]. 

To focus more on the publisher's advantage, and the failure point of open access more generally, is the current state of Gold, Diamond, and Platinum open access. Gold open access involves payment of an APC (Article Processing Charges) fee to the publisher. This often reduces the burdens on libraries, as they previously paid excessive subscription fees. This is because APCs actually increase the burden on individual authors, with disappointing results on the prestige economy. Without market power for the authors (or home institutions), there is no incentive to build Diamond and Platinum access systems. In such systems, no APC fee is paid, and we get the prestige that people seek. One barrier to this is shifting the burden back to publishers, but with proper management of community resources it is the least bad option.

Up to this point, I have been speaking in economically coded language. Without thinking about various motivations, however, we cannot fully understand ways to move forward. Let's think about various intrinsic/extrinsic motivations of authors and their institutions to reclaim open access. Intrinsic motivations are properties of individual cognition, while extrinsic motivations are things that motivate individual behaviors from the outside world.

Intrinsic motivations

There are many intrinsic motivations that drive acceptance and adoption of open access. But there are many that do not, and these motivations often come into tension. Positive drivers include striving for a better community, an imperative for sharing results with the community, the ability to provide different platforms for scientific communication (datasets, hypotheses, theory, out-of-scope studies), and recognition for unsung components of the scientific process (such as technical reports or negative results). Negative drivers include a need to satiate cultural traditions, an inability to convey prestige through open means, a conflation of open access with fraud and low-quality work, and an inability to meet the quality needed to do open access successfully.  

Extrinsic motivations

The multitude extrinsic motivations include institutional support, the need for career promotion, community rewards and prestige, the pressure for cost savings, and technological ease of adoption. These can be a mix of positive and negative drivers that make adoption of open access hard to justify. Interactions with open-source software can also drive open access adoption, as the commitment needed to develop shared data and code can be easily extended to other academic artifacts.

What is the path forward? 

Sometimes considering motivations are not enough, and the community is much pettier and more irrational than we like to admit. It is worth thinking about eLife's model in open peer review, which in part lead to a backlash against the editorial staff [4, 5] by less sympathetic members of the scientific community (and barely-disguised corporate interests). Part of this is a disagreement about open strategies, but this is also about the gatekeeping nature the scientific community itself. The eLife model allows for papers to be preprinted, and then peer reviewed. The paper remains live on eLife's website even if the reviews recommend rejection (although the rejection is noted) [6, 7]. This is not novel amongst open peer review platforms but has rankled the more hierarchically oriented members of the scientific community. Perhaps we need to also consider "irrational management strategies", or what intrinsic motivations drive decisions that favor obsolete conventions.

References:

[1] Melvin et.al (2020). Communicating and disseminating research findings to study participants: Formative assessment of participant and researcher expectations and preferences. Journal of Clinical and Translational Science, 4(3), 233–242.

[2] Casci and Adams (2020). Research Culture: Setting the right tone. eLife, 9, e55543.

[3] Nosek et.al (2015). Promoting an open research culture. Science, 348(6242), 1422-1425.

[4] eLife latest in string of major journals put on hold from Web of Science. RetractionWatch. https://retractionwatch.com/2024/10/24/elife-latest-in-string-of-major-journals-put-on-hold-from-web-of-science/

[5] Abbot (2023). Strife at eLife: inside a journal’s quest to upend science publishing. Nature News, March 17. https://www.nature.com/articles/d41586-023-00831-6

[6] F1000 Staff (2022). Open peer review: establishing quality. March 7.  https://www.f1000.com/blog/peer-review-establishing-quality

[7] McCallum et.al (2021). OpenReview NeurIPS 2021 Summary Report. https://docs.openreview.net/reports/conferences/openreview-neurips-2021-summary-report

OAWeek 2022: Managing Virtual and Hybrid Meetings

Welcome to International Open Access Week, 2022 edition! Last year, we discussed the vision of a distributed research organization. This year, we will explore this theme a bit further. One aspect of distributed organizations is the need to work both synchronously and asynchronously. This brings the real-world experience closer to the collaborator without the travel, carbon emissions, or expense of being at a centralized institute. As our collaborators live in many time zones and have different lifestyles, it is important to capture their full attention in different ways. 

One way this is done is through the live attendance and replay of group meetings. The Orthogonal Research and Education Lab (OREL) offers a number of regular topical meetings, in addition to a general meeting on Saturdays, that engages collaborators from all over the world using a number of different pedagogical and technological techniques. 

An example of a virtual distributed meeting with collaborators dropping in from different parts of the globe.

An open meeting has a number of moving parts that need to be thoughtfully considered to ensure success. The first of these is choosing a meeting platform. OREL has found success with Jitsi, as it is lightweight and free to use (open source). While Jitsi can be used as a service, installing it on your own server opens up its many customizable features. Jitsi even works with Virtual Reality, with interactions between the 2-D meeting world and immersive 3-D being available in the Wolvic browser and Meta Quest casting option.

Sample scenes from screensharing within Meta Quest and the casting option.

Secondly, programming the meeting is a non-trivial detail that can make the most of your time. For our Saturday Morning NeuroSim meetings, we have settled on the following format: updates, light features, discussion, open collaboration, and finally, papers of the week. Agenda-setting should be flexible with respect to your attendee's availability. Not everyone can make an entire meeting, so allowing them to "drop into" participation is encouraged. 

Notetaking and live feeds are also good for augmenting our meetings. The OREL Lab Manager (Jesse Parent) We use notetaking tools such as Obsidian and Notion with allied feeds (Slack and Discord) for coordinating the various fragments of ideas and themes that emerge during meeting time. Feed technology is also good for sharing papers, and the vision of a stream feed is key to realizing the multimedia aspect of real-time meeting immersion, even when attendees are asynchronous.     

Different types of notetaking and stream feeding within a meeting (from the Cognition Futures Reading Group).

As a tool for participatory engagement, this can be done in a number of different ways. Lead by Daniel Ari Friedman and Bleu Knight, the Active Inference Institute has taken the route of invited livestreams and summary podcasts. These materials introduce collaborators to difficult academic concepts while making them more accessible. While YouTube has options for live streaming, it is not always the best option. I use OBS Studio (free and open source) to compose a desktop recording and edit before making it public. 

Recorded meetings are also good for coding demos, particularly when they do not go as planned. One can either prepare a recording in advance to include in the meeting recording or strip the demo down to a minimal approach using a CoLab notebook. This reduces the friction of failed screenshares and execution errors, while also easing the burden of performing in front of a group.

Coding demos from a recent Saturday Morning NeuroSim meeting.

But completely virtual experiences are not the only option for bringing people together from around the world. OREL has been experimenting with hybrid meetings. This type of meeting brings the ethos of virtual meetings to more traditional in-person meetings. This enables more inclusive participation from distant geographical points. Last Spring, we experimented with our own virtual meeting experience at the New York Celebration of Women in Computing (NYCWiC), hosted live at Fort William Henry, NY. The hybrid session "Frontiers in Data Privacy and Tech Ethics" featured a buffet of topics on AI and technology ethics. Soem of the participants were live, while others were virtual (recorded or located in different parts of the globe). For this type of meeting, experimenting with ways to optimize live/virtual synchronization and media capture quality are essential. We plan to experiment with this more in the near future. 

Virtual (top) and in-person (bottom) components of the session.

Opening Access, Virtual, Distributed Lab Edition

Welcome to Open Access Week 2021! This year's theme is building structural equity. In the Orthogonal Research and Education Lab and the DevoWorm group, this has been an ongoing priority: from the recruitment of scholars to the production and engagement with research. This week we will highlight some of the ways we open up the research process, and how this is the only way the principles of open access (Figure 1) can be fully realized.

Figure 1. From the short film "What is Open Access" (PhD Comics, 2012).

One thing that enables Open Access is an open collaboration structure. Both Orthogonal Lab and DevoWorm are based on a virtual, distributed framework. People can join in and collaborate as long as they have an internet connection and the initiative to work on a related problem. The communication structure is likewise flexible: you can join in our weekly meetings, participate in our Slack channels or Github teams, or join in on a collaborative doc. We also sponsor or participate in various open educational initiatives. Two of these are Google Summer of Code and Neuromatch Academy.

Figure 2. The global reach (physical and virtual) of the Orthogonal Lab.

This brings together participants from multiple continents and research specialties, while also enabling students, professional academics, and lifelong learners to collaborate in ways large and small. We participate in the academic community through virtual and hybrid conferences, peer-reviewed publication venues, book chapters, and preprints. Self-publication platforms (blogging platforms) and social media are also good for advancing fledgling ideas and chronicling progress. Along with an emphasis on open code and data, these venues are utilized to maximize access and reusability.

More recently, we have been focusing on the role of professional development in enabling the virtual, distributed research process. As many of our contributors aspire to further their research careers through participation, we have become more active in cultivating an individual's research agenda. Between active recruitment of participants and enabling them to take ownership of a research topic, we can contribute to greater equity and diversity in the research enterprise.

            

Finally, our Open Access agenda includes an interdisciplinary focus, as both Orthogonal Lab and DevoWorm engage individuals from a variety of different backgrounds. There is an intentionality towards enabling interdisciplinary skillsets, as well as a focus on providing individuals space to pursue these connections between traditional disciplines. For more information on how these components work to form a virtual, distributed lab, see our preprint "Building a Distributed Virtual Laboratory Adjacent to Academia". 

While there are still many administrative and functional barriers to pursuing this as a full-fledged research organization on par with a large corporation or University, this is a unique and emergent way of opening access. If you would like to participate, please contact us. Additionally, be sure to check out the #OAWeek hashtag for this blog (Synthetic Daisies), as we have content going back to 2016 on a variety of topics. 

ASAPBio Session on the "Past, Present, and Future of Preprints"

For Open Access Week 2020, Synthetic Daisies will feature an exciting panel discussion on preprints. On Monday (19th), I was part of a panel called "Past, Present, and Future of Preprints", hosted by ASAPBio. I live tweeted the event from the Orthogonal Research and Education Lab Twitter account. If you were not able to attend in person, the recording is on YouTube! The session started with a short introduction from each of our participants: Antonis Rokas, Soumya Swaminathan, Richard Sever, Ross Mounce, and Anjana Badrinarayan.

Yamini Ravichandran and Marco Fumasoni started us off with a short introductory presentation, followed by an introduction by each of our panelists. This part of the session culminated with Marco posing an initial question to the panel.

It turns out that there are many contributing factors to preprint adoption. Some of them involve legacy patterns from manuscript submissions and publications. But preprints also democratizes access to both the production and consumption of scientific literature. It turns out that cultural traditions (within fields and countries), researcher agency, and community incentives are also quite important.

The theme of research culture came up time and time again. But research culture is not only a motivating factor; pro-preprint behaviors can lead to other virtuous practices. For example, Ross Mounce suggests that preprints can encourage a culture of versioning, where different versions of a paper are viewed as important steps in the research process rather than simply being erratum.

There was also a discussion of the role traditional journals play in the research dissemination process. One future direction of preprint culture is to decouple papers from journals. Towards the end of our session, we heard a choice quote from Antonis Rokas and the Rokas Lab.

This combines nicely with observations earlier in the session regarding citation metrics: with the movement towards iteratively-developed preprints with multiple supporting components (open data sets, supplemental figures and notes), there will be a need to distinguish article quality from journal quality. Altmetrics are one path forward, but a more robust system is needed. 

Thanks to everyone for participating! Thanks also go to Sarah Stryeck, Jessica Polka, and of course Iratxe Puebla for being a great community manager! Happy Open Access Week! 

UPDATE (11/3): A recording of the session is now on YouTube!

OAWeek: share your own case study!

This post is part of a series published over the course of OAWeek 2019.

Do you use, share, or have an opinion about open data? The Data Reuse Initiative would like to hear from you! In honor of OAWeek 2019, we are looking for personal and research group testimonials on how you share or otherwise practice open data. Submit at your leisure (there is no deadline), but we would like to hear from you!

RULES:
* submit a testimonial (under 200 words) by submitting a pull request to our Github repository or submit to this Google Form.

* if you choose to submit an image (screenshot, diagram, or cartoon), please issue a pull request on Github.

* if you cannot access either of the links, or need help with your submission, please [contact us](mailto:balicea@openworm.org).

OA Week: Digital Badges on Open Data

This post is part of a series published over the course of OAWeek 2019. Today's post will preview a series of digital badges related to Data Reuse. These badges were designed in conjunction with the new Data Reuse Initiative.

Overview of Data Reusability I. Click to enlarge.

The first digital badge (Data Reusability I) provides the learner with some practical skills in data sharing. The practical examples are mostly biology-oriented, but is useful for learners from a wide range of fields. Activities include work with a selected article from the journal Genome Biology, posting a sample data set to Figshare, and working with data sets published on the Dryad repository. While these activities provide just a taste of the work involved in sharing data, it nonetheless imparts some key skills in interacting with and publishing data in an open fashion. 

Overview of Data Reusability II. Click to enlarge.

The second digital badge (Data Reusability II) provides a tutorial that reviews public data sharing competencies in more depth. For this set of exercises, we have used the Mozilla Data Sharing Planning Template as a model for best practices community standards. Earners of this badge will develop competencies in metadata creation, data cleaning/processing, documenting data set provenance, assigning credit for the published work, and enabling easy and reproducible reuse of the data set. Check them out!

OA Week: History of Open Access

This post is part of a series published over the course of OAWeek 2019.

Timeline of scientific output from [1]. Click to enlarge.

This post will walk us through the History of Open Access (with a focus on Open Science) infographic mentioned in our inaugural blog post for this series. Randall Munroe [1] has previously summarized the progression of open science as a function of the scope of scientific output. The events and milestones for the featured historical overview were confirmed by internet search and synthesized from a survey of various tools and publications common in the field. This post characterizes the historical eras according to a developmental biology theme: from the embryo to developmental plasticity to an adult stage of life-history.

History of Open Access (1942-present), color-coded by historical era. Yellow: early, blue: transitional, green: contemporary. Click to enlarge. For a citable version and an alternate display type, please see [2].

1942-1999: Embryonic Ideas and Tools (early). Click to enlarge.

In the early period, there was an emergence of tools, ideas, and attempts to synthesize independent efforts. Early efforts such as the World Data System, MedLine, and Project Gutenberg served as inspiration for later efforts (particularly the development of MedLine into PubMed). Tools such as digital preprints (arXiv) and the internet (HTML, XML) served to provide the infrastructure of open science. Even tools such as Cyc (extraction of scientific rules from data) served to enable greater openness in the practice of science. The end of this era is marked by "Exploring the Development of the Independent, Electronic Scholarly Journal", a survey of open access journals in what coincides with the early internet era.

2000-2008: Institutional Plasticity (transitional). Click to enlarge.

The transitional period (or institutional plasticity) was a time for creating many of the institutions and established norms of the open science community. Many foundational ideas were either established (Creative Commons, digital object identifiers) or came to fruition (Human Genome Project) during this period. It is also of note that at least four declarations of practice were published during this period.

2009-present: A Juvenile No More! (contemporary). Click to enlarge.

The contemporary period has been defined by even more sophisticated tools (Altmetrics), quasi-historical summaries of past work for future development (Reinventing Discovery, The Future of OA), and the discussion of institutional standards at a greater level of specialization (FAIR Principles). This era is also marked by the use of open science to practice collaborative open science (Polymath Project), putting all of the pieces developed in previous eras into place.

NOTES:
[1] Munroe, R. (2013). The Rise of Open Access. Science, 342(6154), 58-59. doi:10.1126/science. 342.6154.58

[2] Alicea, B. (2019). History of Open Access Infographic. Figshare, doi:10.6084/m9.figshare. 9975713

Open Access Week 2019: Introduction

Welcome to OAWeek 2019! This year's features are being published in conjunction with the Orthogonal Research and Education Laboratory, the eLife Ambassadors program, and the associated Data Reuse Initiative.

The first feature for this year is an infographic called the History of Open Access [1]. Our history begins in 1943 with some Philosophy of Science [2], and proceeds through key innovations, publications, and institutions the span the late 20th and early 21st centuries. Below is a preview of the infographic, and will be discussed in more detail on Tuesday the 22nd.

History of Open Access infographic (Omega version).

The second feature is a series of digital badges (microcredentials) on Open Data practice [3]. The first badge in the series walks the learner through several lessons on how to identify, locate, and work with open datasets. The second badge walks the learner through preparing an open data set for publication. This lesson is based on the Mozilla Data Reuse Planning Template which help people adhere to best practices when making data public and shareable. These badges will be released on Thursday the 24th. Then, on Friday the 25th, we will give you the chance to make your own contributions (details to come). So join us for our week of celebrating Open Access!

NOTES:
[1] Figshare, doi:10.6084/m9.figshare.9975713

[2] Robert Merton, The Sociology of Science: theoretical and empirical investigations.

[3] Molloy, J.C. (2011). The Open Knowledge Foundation: Open Data Means Better Science. PLoS Biology, 9(12), e1001195.

OAWeek 2018: Barriers to Practice

In our final OAWeek post, I will present the current barriers to "open" practice. While there are many potential barriers to living up to the principles of complete openness, there are four major reasons why people or institutions make the decision to be open and their reasons for doing so. These include (but are not limited to): technological, financial, formal conventions, and learning curve.

Technological. The past few years have seen a boom in innovations and digital tools that enable open access, open science, and open source. Based on the above figure, we can see that the all areas of the conventional scientific process have been touched by this revolution. Distribution, publishing, notetaking, bibliographies, and engaging the broader community have all been impacted by new tools and (more importantly) their adoption by a critical mass of scientists. The development of formal pipelines for organizing this proliferation of tools into actionable steps [1] has also been a technological advance. Despite this convergence, this is not a single "killer app" that will solve the open problem. Nor should there be, as killer apps are often concentrated in the hands of single entities that are vulnerable to profiteering. Importantly, open-enabling technologies must be available to smaller research groups, particularly generators of smaller datasets [2], to get the most out of the scientific community's efforts.

101 Innovations in Scholarly Communication. ORIGINAL SOURCE: https://innoscholcomm.silk.co/  License: CC-BY.

Financial. While many tools are relatively cheap to use, other aspects of open science can be quite costly to individual scientists or even laboratories. In Wednesday's post on the three "opens", the various models of open access were discussed. Depending on which route to open access and/or open science is chosen, there are costs associated with manuscript, data archiving, curation, and annotation. A successful "open" strategy should include a consideration of these costs to ensure sustainability over the long term. There are also issues with the cost and public funding of large-scale community resources such as open access journals, preprint servers, data repositories that must be solved without making their use unaffordable or (by extension) unavailable. One open question is the incentive structure for sharing resources and making them accessible. This is particularly true for datasets, which require incentives related to research efficiency, social prestige, and intellectual growth [3]. Such incentives can also help to reinforce higher reproducibility standards and overall levels of scientific integrity [4]. 

An example of a set of formal conventions chosen from a large number of potential tools. COURTESY: Nate Angell, Joint Roadmap for Open Science Tools. License: CC-0.

Formal Conventions. Another barrier to "open" is cultural practice. In moving from concept to finished product, we do so by following a set of internalized practices. While science requires much formal training, many scientific practices are taught implicitly during the course of laboratory and scholarly research. Several recent studies characterize openness as a matter of evolving norms [5, 6] which define openness in terms of collegiality, and does not punish non-open endeavors. One critical aspect to encouraging open practices is education. However, there does seem to be a generational shift in attitudes and educational opportunities surrounding open practices. This has occurred at the same time information and computational technologies have emerged that encourage sharing and transparency. Whether this will change standards and expectations in a decade is unclear -- although governments and funding agencies are now embracing open access and open science in ways they previously have not.

Learning curve as compared to the diffusion of innovations [7]. COURTESY: Wikimedia.

Learning Curve. With all of the potential tools and steps in making research open, there is a learning curve for both individual scientists and small organizations (e.g. laboratory). While the learning curve for some practices (e.g. preprint posting) are trivial, other "open" practices (e.g. transparent protocol and methods) require more commitment and formal training. The learning curve is one major factor in the difference between merely "making things open" and making things accessible. In the domain of open datasets, accessibility can be hampered due to the fragmentation of resources across many obscure locations rather than a highly-discoverable set of repositories with fixed identifiers [8]. There are two additional barriers to accessibility and/or practice adoption: difficulty of learning and cultural learning. Difficulty in learning a specific tool or programming language does make a difference in how open practices are, and the harder or more time consuming a certain task is, the less likely the associated practice will be adopted. Cultural learning involves being exposed to a specific practice and then adopting that practice. This generally has little relation to difficulty, and depends more on personal and institutional preference. It is important to keep both of these in mind, both for adopting an "open" strategy and expectations of members of the broader community.


NOTES:
[1] Toelch, U. and Ostwald, D. (2018). Digital open science: Teaching digital tools for reproducible and transparent research. PLoS Biology, 16(7), e2006022. doi:10.1371/journal.pbio.2006022.

[2] Ferguson, A.R., Nielson, J.L., Cragin, M.H., Bandrowski, A.E., and Martone, M.E. (2014). Big Data from Small Data: Data-sharing in the ‘long tail’ of neuroscience. Nature Neuroscience, 17(11), 1442-1448. doi:10.1038/nn.3838.

[3] Gardner, D. et.al (2003). Towards Effective and Rewarding Data Sharing. Neuroinformatics, 1(3), 289-285. AND Piwowar, H.A., Becich, M.J., Bilofsky, H., Crowley, R.S. (2008). Towards a Data Sharing Culture: Recommendations for Leadership from Academic Health Centers. PLoS Medicine, 5(9), e183. doi:10.1371/journal.pmed.0050183.

[4] Gall, T., Ioannidis, J.P.A., Maniadis, Z. (2017). The credibility crisis in research: Caneconomics tools help? PLoS Biology, 15(4), e2001846. doi:10.1371/journal.pbio.2001846.

[5] Pham-Kanter, G., Zinner, D.E., and Campbell, E.G. (2014). Codifying Collegiality: recent developments in data sharing policy in the life sciences. PLoS One, 9(9), e108451. doi:10.1371/ journal.pone.0108451.

[6] Fecher, B., Friesike, S., and Hebing, M. (2015). What Drives Academic Data Sharing? PLoS One, 10(2), e0118053. doi:10.1371/journal.pone.0118053.

[7] Rogers, E. (1962). Diffusion of Innovations. Free Press of Glencoe, New York.

[8] Culina, A., Woutersen-Windhouwer, S., Manghi, P., Baglioni, M., Crowther, T.W., Visser, M.E.  (2018). Navigating the unfolding open data landscape in ecology and evolution. Nature Ecology and Evolution, 2, 420–426. doi:10.1038/s41559-017-0458-2

OAWeek 2018: Open Access, Open Science, Open Source

For this OAWeek post, we will discuss the connections between open access, open science, and open source. As an organizing principle, I will introduce each concept with a working definition, and then discuss relationships with other "open" concepts.


Open Access: availability to the general public, research output can be distributed freely without restrictions.

A typology of different forms of Open Access publishing.

As a publishing phenomenon, open access can take a number of forms [1, 2]. Aside from a distinction between peer-reviewed and non peer-reviewed materials, Open Access publishing is color-coded as green (self-archiving) or golden (archival at the publisher's site for a fee) [3]. There is also a version of golden open access called diamond open access, the difference being that diamond open access does not require the author to pay a fee to the publisher [4]. Self-archival can be done through a personal server (website), a preprint site such as bioRxiv, or a site that allows for public hosting of documents (ResearchGate, Figshare). Golden open access usually requires an APC fee, the funds for which go to the publisher. While cheaper, self-archival requires adherence to a set practices that ensure ease of access.

In a narrow sense then, open access is a publishing issue seemingly unconnected to open science and particularly open source. Yet in fact, open access is both critical to and an enabling factor in open science and open source. Aside from making materials open (free or affordable), they mush also be made accessible. There are many other benefits to open access [5], but the most important of which is that they enable access to many different components of a set of scientific results.


Open Science: make research and data (scholarly outputs) publically accessible. This requires efforts to make scholarly outputs transparent and accessible, which should enable reproducibility.


Open Science is an extension of open access in that not only is the manuscript made public, but the research products are made public as well [6, 7]. An open pipeline (or system) might include any number of the following: version-controlled manuscript editing, preprints, preregistration of study design, open datasets, demonstrable analyses, open source code, social media engagement, post-publication review, and open manuscript review. While it is up to the scientist or scientific organization what components to utilize, each component has value to both the scientist [8] and the scientific audience.

One way to make the benefits of being open explicit without violating the rights of scientists to their original work is to adopt an open license. While there are a number of options for both open science and open source, one popular type of license is Creative Commons (CC) [9]. There are many types of CC license, but one commonly used in open science is CC-BY (or alternatively CC-BY-NC). The BY license allows others to distribute and/or recombine your work with acknowledgement of the original author (you). BY-NC licenses explicitly disallow commercial derivatives.

A successful open science strategy is more than simply the production of science and the least publishable unit. Open science also includes access to educational materials, such as screencasts, lecture notes, and even course development [10]. As a suitable example, Open Science MOOC provides all of their course modules at the level of a consumable lesson and a Github repository of sharable lesson plans.


Open Source: make source code publically available and editable. Software architecture is licensed so that it can be modified in collaborative fashion.

In many ways, open source (OS) can be considered a crucial component of open science, as the ability to collaboratively and transparently solve problems is a key part of the ethos. Yet open source has its own set of concerns surrounding project-building and the management of contributors. The development of open source software is not simply the production of free software, as there are significant version control and human resource issues that go into OS [11]. Open source projects (such as Wikimedia Foundation or Linux Foundation) tend to operate at a much larger scale than open science collaborations. In the case of hybrid open science/open source organizations (such as the OpenWorm Foundation), there are a number of management concerns that also draw from making research methods and data transparent.

Open Source provides not only an avenue to transparency, but also as a tool for collaboration. An open source infrastructure that provides version-control [12] and source code annotation in the public domain can serve to enable public discussion and encourage future development outside of a specific project or set of experiments. The ability to open up code used in analysis and simulation aids in the peer review process. For published methods, open source provides a means for people to improve upon and use the code base. Open source efforts such as the open hardware movement allows labs to share standardized plans for DIY lab equipment, lowering the costs of science.


NOTES:
[1] Jeffrey, K.G. (2006). Open Access: an introduction. ERCIM News. https://www.ercim.eu/publication/Ercim_News/enw64/jeffery.html.

[2] Suber, P. (2012). Open Access. MIT Press, Cambridge, MA

[3] Kienc, W. (2015). Green OA vs. Gold OA. Which one to choose? Open Science blog, June 3.

[4] Kelly, J.M. (2013). Green, Gold, and Diamond?: A Short Primer on Open Access. Jason M. Kelly blog, January 27.

[5] PLoS. Why Open Access? https://www.plos.org/open-access.

[6] Guide to Open Science Publishing. F1000Research.

[7] McKiernan, E.C., Bourne, P.E., Brown, C.T., Buck, S., Kenall, A., Lin, J., McDougall, D., Nosek, B.A., Ram, K., Soderberg, C.K., Spies, J.R., Thaney, K., Updegrove, A., Woo, K.H., and Yarkoni, T. (2016). How open science helps researchers succeed. eLife. 2016; 5: e16800. doi:10.7554/eLife. 16800.001.

[8] Ali-Khan, S.E., Jean, A., MacDonald, E., Gold, E.R. (2018). Defining Success in Open Science. MNI Open Research, 2, 2. doi:10.12688/mniopenres.12780.

[9] Creative Commons. About the licenses. https://creativecommons.org/licenses/

[10] Jhangiani, R. and Biswas-Diener, R. (2017). Open: the philosophy and practices that are revolutionizing education and science. Ubiquity Press. doi:10.5334/bbc.

[11] Fogel, K. (2017). Producing Open Source Software: how to run a successful free software project. Version 2.3088 http://producingoss.com/

[12] Blischak, J.D., Davenport, E.R, and Wilson, G. (2016). A Quick Introduction to Version Control with Git and GitHub. PLoS Computational Biology, 12(1), e1004668. doi:10.1371/journal.pcbi. 1004668.

Welcome to Open Access Week 2018!

Welcome to Open Access Week! Orthogonal Research and Education Laboratory is contributing to the week's activities through three blogposts: in this post, we will briefly discuss Open Annotation, while Wednesday will feature "Open Access, Open Science, and Open Source" and Friday will feature "Barriers to Practice".

Synthetic Daisies blog celebrated Open Access Week in 2016 (Working with Secondary Datasets, How Am I Doing, Altmetrics?) and 2017 (Version-Controlled Papers, Open Project Management). All posts will be tagged with #OAweek for easy retrieval.

To kick off the discussion, we will now quickly discuss Open Annotation and the role it can play in enabling literature searches, peer-review, and collaboration. Two of the most well-known open annotation tools are Hypothes.is and Fermat's Library. A few posts from the Hypothes.is blog serve to establish the benefits and potential of open annotation and how it is currently being implemented on the web.

According to [1], open annotation can serve as a framework for new practices such as collective document review. This is a common function of collaborative document systems such as Overleaf and Authorea. However, the Hypothes.is vision for seems to be building a so-called "ecosystem" for commenting that can be used for peer review, reader notes, or links to relevant additional readings [1, 2]. In such a system, comments can be transferred across versions of a document, from draft to preprint to published manuscript [1].

Under the hood, open annotation relies upon standards such as the W3C Open Annotation data model. Once implemented, this allows for a separation of the discussion (annotations) from the main page [2]. This provides opportunities for meta-browsing [3] and distributed discussion threads that can be centralized in a common repository. There are also many opportunities for novel uses of open annotation, ranging from collaborative note-taking to adding references and data to an existing paper.

NOTES:
[1] Staines, H. (2017). Making Peer Review Transparent with Open Annotation. Hypothes.is blog, http://web.hypothes.is/blog/transparent-peer-review.

[2] Gerben (2014). Supporting Open Annotation. Hypothe.is blog, https://web.hypothes.is/blog/ supporting-open-annotation/.

[3] Wiesman, F., van den Herik, H.J., and Hasman, A. (2004). Information retrieval by metabrowsing. Journal of the American Society for Information Science and Technology, 55(7), 565-578.

Open Access Week 2017: Version-Controlled Papers

The subject of a recent workshop [1], the next-generation scientific paper will include digital tools that formalize things such as version control and data sharing/access. Orthogonal Laboratory is developing a method for version-controlled documents that integrates formatting, bibliographic aspects, and content management. While this is not a novel approach to writing and composition [2], this post will cover how to apply a version-controlled strategy to presenting a scientific workflow. Below are brief sketches of our system for generating next-generation papers.

The first element is the process through which a document is generated, styled, and published (assigned a unique digital identifier or doi):

The key element of our system is a version control repository. We are using Bitbucket, but Github or a more specialized platforms such as Authorea or Penflip might also be sufficient. The idea is to build documents using the the Markdown language [3], then incorporate stylistic elements using CSS and HTML. VScode is used to manage spellcheck and grammar in the Markdown documents (containing the authored content). Reference management is done via Zotero, but again, any open source alternative will do.

The diffs function [4] of version control can be used to operate on final versions of Markdown files for the purpose of alternating between document versions. The idea is to not only find a consensus between collaborators, but to use branches strategically to push alternative versions of content to the doi as desired. This combinatorial editing framework could be desirable in appealing to different audiences or stressing specific aspects of the work at different points in time. Note that this is distinct from the editorial function of pulls and merges, which are meant to be more "under the hood".

Pandoc serves as a conversion tool, and can style documents according to particular specifications. This includes conventions such as APA style, or document formats such as LaTeX or pdf [5]. Additional components include code and data repositories, supplemental materials, and post-publication peer review.

Orthogonal Lab generally uses a host such as Figshare to generate dois for such content, but there are other hosts that generate version-specific dois as well. It is worth noting that Github-hosted academic journals are beginning to appear. Two examples are ReScience and Journal of Open Science Software. What we are providing (for our community and yours) is a means to generate styled documents (technical papers, blogposts, formal publications) in a version-controlled format. This also means papers can be dynamic rather than static: content at a given doi can be updated as desired.


NOTES:
[1] Perkel, J. (2017). C. Titus Brown: Predicting the paper of the future. Nature TechBlog, June 1.

[2] Eve, M.P. (2013). Using git in my writing workflow. August 18. Also, much of this functionality is accessible in Overleaf using TeX and a GUI interface.

[3] Cifuentes-Goodbody, N. (2016). Academic Writing in Markdown. YouTube. AND Sparks, D. and Smith, E. Markdown Field Guide, MacSparky.

[4] Diffs are also useful in comparing different versions of a published document as events unfold. Newsdiffs performs this function quite nicely on documents containing unfolding news.

[5] A few references for further reading:

a) Building your own Document Processor Tools:
Building Publishing Workflows with Pandoc and Git. Simon Fraser University Publishing.

b) Git + Diffs = Word Diffs:
Diff (and collaborate on) Microsoft Word documents using GitHub. Ben Balter blog.

c) Using Microsoft Word with Git. Martin Fenner blog.

Open Access Week 2017: Open Project Management

To kick off the open fun for this year, we will start off with a short discussion on open project management. Although people should think of this in a tool-free manner, we will address broad principles using Slack and Open Science Framework (OSF).

Welcome to the Orthogonal Lab Slack space! Contact if you are interested in joining.

Slack as a laboratory group tool: I began using Slack several years ago when the OpenWorm Foundation started using it to facilitate shared communication and manage new members. Since then, it has become increasingly popular as a laboratory personnel and collaborative management tool [1]. I started the Orthogonal Lab Slack about a year ago, and it has been useful for disseminating intragroup messages, news, media, and short presentations. This is especially good for academic collaborations, particularly when the group members are not co-located [2].

Once your group has a Slack space (with a URL such as your-group.slack.com), you must a) create channels, and b) recruit members. Whether your group is large or small, Slack seems to scale well in most cases. Each channel is thematic, and allows for parallel communication between channel members. Media (files, images, links) can be shared with ease, and private messages are also possible. Additional functionality is possible through the use of bots (e.g. time-management tools such as todobot or slackodoro). In many ways, Slack is an alternative to the e-mail chain. However, integration with other platforms (such as Twitter or Skype) is also possible.

An infographic on Slack productivity in the academic workplace, courtesy of Paperpile.

COURTESY: Using OSF at the University of Notre Dame. YouTube.

Open Science Framework (OSF) as project pipeline and showcase: I have been using OSF for storing work at the project level for exposition to potential funders and other interested parties. More generally, OSF is used to promulgate both the progression and replicability of research projects [3]. From a technical perspective, OSF also features version control (using Git), doi creation, and storage space for papers, presentations, and data. OSF also offers an API and an open dataset on research activities. OSF also has a portal called Thesis Commons for theses and dissertations. You can also store datasets, digital notebooks, and link to Github-hosted code using the OSF project structure.

Potential destinations for objects of the OSF workflow. COURTESY: Ref [4].

The OSF offers a means to manage all scales of research output. Artem Kaznatcheev has provided an informal taxonomy of research output types as well as their scale of importance. According to this view, examples of the these scales include the following: standard (blog), kilo (conference pubs), giga (journal pubs), and tera (book/thesis) scales. Although arbitrary in terms of content, these scales might more closely define the number of hours invested in creating a particular type of research document. OSF projects can include combinations of research output types to provide a richer window into the research process.

Steps in the developing research (or, how to get to research outputs). COURTESY: Visual.ly

NOTES:
[1] Some examples include:
a) Slack inside the MacArthur Lab. SlackHQ blog, April 27 (2015).

b) Washietl, S. (2016). Six ways to streamline communication in your research group using Slack. Paperpile blog, April 12.

c) Perkel, J.M. (2016). How Scientists Use Slack. Nature News, 541, 123. Managing organizational to-do lists in Slack.

[2] OpenWorm Slack has a bi-weeky event called Office Hours where people meet and have topical conversations. Join us via Slack Pass if you are interested.

[3] Foster, E. and Deardorff, A. (2017). Open Science Framework (OSF). Journal of the Medical Library Association: JMLA, 105(2), 203-206.

[4] Anonymous (2016). Response from COS. Medium, April 2.