In 2015, a Sloan Foundation grant to Open Knowledge led to the creation of the “frictionless data” standard, a set of protocols for packaging tabular datasets in uniform ways that could be used, if adopted widely enough, to greatly simply the logistics of exporting, transporting, and importing data. This grant funds efforts by Open Knowledge to broaden adoption of the frictionless data standard through outreach to scholarly organizations, data platforms, analysis tools, and specific research fields. Over the three-year grant period, Open Knowledge will use grant funds to conduct outreach and support activities, structured partly as high-touch field/context-specific pilots, and partly as broader outreach and engagement to the wider user community.

Major video game rendering engines are capable of rich 3D environmental rendering and physics simulation, not to mention built-in virtual and augmented reality capabilities. They are, however, rarely utilized in scholarly research, in part because researchers who have explored their use for data visualization have had to manage the arduous task of configuring and structuring their research data in order to load it into the game engine. This grant funds a two-year initiative by Huy Vo of the City College of New York to dramatically lower barriers to the use of game engines for scientific visualization. In the first year, Vo will develop a standardized workflow and open source plug-in for the popular Unity 3D gaming engine that will enable the easy importation of research data, generation of geometries, and construction of interactive visualizations. In year two, Vo will pilot the plug-in himself in two research collaborations (one with CUNY researchers on climate adaptation and the reliability of power sector infrastructure, one with AT&T Research Labs on mobile antenna placement). He will also use it as the platform for student projects in a CUNY data visualization course.

The International Geo Sample Number (IGSN) grew out of an initial need to foster better citation of geological samples. As of mid-2018, there are over 6.5 million individual physical specimens represented within the IGSN, and a network of 25 IGSN “allocating agents” across five continents. After a number of years of growth within geoscience, the IGSN is confronted with increased interest from other disciplines; for example, the IGSN has already been used to register IDs for biological specimens and archaeological artifacts. Rather than encourage the development of a number of different discipline-specific registries, Lehnert and an international team of collaborators plan to redesign IGSN to support physical samples and specimens from across the sciences. Funds from this grant support technical development of the IGSN platform and a series of working meetings to bring together current IGSN registrars, other stakeholders, and persistent identifier (PID) experts to strategically plan the organizational and technical future of the initiative.

This grant provides three years of support for gatherings of WikiCite, a project within the Wikipedia ecosystem designed to both improve citation within Wikipedia and to expand the Wikidata project in ways useful to the scientific community. Grant funds will support a dedicated annual WikiCite meeting, as well as a series of smaller satellite meetings at other Wikimedia events. The organizers will also maintain a strong presence at other scholarly communication meetings, bringing the energy and technical sophistication of the Wikimedia community to bear on innovation in scholarly communication more broadly.

This grant funds a project led by Jonathan Crabtree, Director of Cyberinfrastructure at the University of North Carolina’s Odum Institute, to improve and expand the capabilities of the Dataverse open source data repository platform. Odum is responsible for executing and implementing the Replication and Verification Policy for the American Journal of Political Science (AJPS) and uses Dataverse as the underlying platform where authors who publish in AJPS can upload their data and software code to ensure results may be replicated. Because Dataverse was originally designed for data and not software, however, the process can be unwieldy and time consuming. Crabtree and his team plan to use the Jupyter computing platform and the open source software “containerization” toolkit Docker to create a “Confirmable Reproducible Research (CoRe2) environment” for Dataverse that would combine the ability to containerize computational research with communication and workflow tools. This would greatly speed and partially automate the process of verifying that submitted research results can be verified using the code and data uploaded. Grant funds will provide support for this project for three years.  years.

This grant funds a series of four projects by Mercи Crosas, Chief Data Science and Technology Officer at Harvard’s Institute for Quantitative Social Science to expand and improve software handling capabilities of the Dataverse open source data repository platform. First Crosas will integrate Dataverse with Encapsulator, an open source tool that allows the creation of a computational “time capsule” that preserves the exact computational environment used to conduct a piece of data analysis. Second, Crosas will create links between Dataverse and Code Ocean, a computational reproducibility platform that was spun out of Cornell Technion’s incubator program. Third, Crosas will develop a set of metadata versioning and exploration tools that will increase incentives for data curation by returning richer usage statistics to data providers and publishers. Finally, Crosas will model and pilot a fee-based curation service that would allow the sustainable scaling of data and code curation in Dataverse. This work, like all other development on and organizational innovation within the Dataverse community, will be freely available and useful to the dozens of other institutions running the software to power their own data archives.

The Center for Open Science’s (COS) preprint platform was designed to serve a variety of scholarly communities, especially lowering barriers to entry for those disciplines new to preprint publication whose needs were not being served by the larger, more highly powered preprint servers like arXiv. This grant funds a project by COS founder Brian Nosek to use the COS preprint platform as the setting for a series of experiments that will test how user trust is affected by different preprint platform features. Nosek proposes to use the launch of already-planned features like annotation and visual icons to run a set of experiments on the assignment of trust by readers of scientific research. While the budget includes some technical development, the bulk of the requested funding will support the COS “metascience” team to take a mixed-methods research approach, combining surveys with analysis of usage data from the preprint servers to understand the impact of annotation and “reproducibility badges” on readers’ perceptions of trustworthiness of individual preprints and of the preprint server overall.

Somewhere between 50% and 60% of internet users use Google Chrome to browse the web. Chrome, unfortunately, doesn’t natively display mathematics using the standard XML markup language MathML. This forces sites like Wikipedia to generate static images of mathematical notation from the underlying MathML when Chrome can’t render the markup on its own. Not only does this have implications for accessibility, it also inhibits the development of innovative new interfaces and applications that would rely on dynamic interaction with mathematical notation via browser-based programming languages like JavaScript. Funds from this grant will support a project led by the National Information Standards Organization to implement full MathML rendering in Chromium (the open source codebase underlying the Chrome web browser). Technical development will be undertaken by developers at Igalia, an open source software consultancy that has played a key role in MathML integration in other major web engines.