“ARTiFACTS provides a simple, user-friendly platform, purpose built for academic and scientific research that leverages blockchain technology. Researchers can record a permanent, valid, and immutable chain of records in real-time, from the earliest stages of research for all scientific and scholarly artifacts, including citing/attribution transactions….
By using the ARTiFACTS platform, researchers will be able to immutably prove ownership and existence of novel work, expand access to their scientific and academic research artifacts, provide and receive ‘real-time’ attribution for novel work and more comprehensively and rapidly build and demonstrate their body of scholarly contributions….
Establish proof-of-existence and confirm provenance at any time
Protect and manage IP while concurrently facilitating collaboration and knowledge sharing
Provide and receive valid, break-proof attribution and assignment of credit
Participate in growing a comprehensive, community archive for all scientific and scholarly artifacts….”
“CREDIT is a cloud-enabled SaaS tool for data management to provide an opportunity to authors to register their Additional Research Outputs(AROs) reflecting RAW, REPEAT & NULL/NEGATIVE entities generated at various stages of research workflow to ensure their reusability & gaining credit. Hence contributing towards enriching research articles & reproducible science. CREDIT framework & interface is developed on FAIR data principles….The appearance of these badges happens dynamically, hence creates a possibility that the metrics around the data, when readers engage with it would be fed back to the main published article in real-time (accessible via the badge – Enhancing Discoverability and also giving credits to Authors). And in the near-future we also have plans to roll out Badges that can be embedded in PDF articles….”
“Our mission is to make the world’s scientific code more reusable, executable and reproducible
Code Ocean is a cloud-based computational reproducibility platform that provides researchers and developers an easy way to share, discover and run code published in academic journals and conferences.
More and more of today’s research includes software code, statistical analysis and algorithms that are not included in traditional publishing. But they are often essential to reproducing the research results and reusing them in a new product or research. This creates a major roadblock for researchers, one that inspired the first steps of Code Ocean as part of the 2014 Runway Startup Postdoc Program at the Jacobs Technion Cornell Institute. Today, the company employs more than 10 people and officially launched the product in February 2017.
For the first time, researchers, engineers, developers and scientists can upload code and data in 10 programming languages and link working code in a computational environment with the associated article for free. We assign a Digital Object Identifier (DOI) to the algorithm, providing correct attribution and a connection to the published research.
The platform provides open access to the published software code and data to view and download for everyone for free. But the real treat is that users can execute all published code without installing anything on their personal computer. Everything runs in the cloud on CPUs or GPUs according to the user needs. We make it easy to change parameters, modify the code, upload data, run it again, and see how the results change….”
“It’s great when academic research is covered by the media but too often this coverage fails to link back to or properly cite the research itself. It’s time academics insisted on this and Andy Tattersall outlines the benefits of doing so. As well as pointing more people to your work, the use of identifiers allows you to track this attention and scrutinise where and how your research has been used. At a time when academic work is vulnerable to misreporting, such a simple step can help ensure the public are able to view original research for themselves….”
“The web is awash with uncredited images. The tech startup Mediachain Labs is hoping to get photographers the credit they’re due.
They’ve done this by ingesting a trove of images with Creative Commons licenses from over 30 image sharing platforms such as Flickr, along with the attribution found on those platforms. It then used neural network-powered content identification technology to de-duplicate over 400 million images, leaving it with a base of 125 million photos.”