Jülich Open Science Speaker Series invites you to come hear,

Dr. Crystal Steltenpohl (Center for Open Science)

discuss her work on,

Alignments & Tensions between Qualitative Methods & Open Science

9 April 24, 15:00 CEST

ZOOM:
https://apps.fz-juelich.de/umfragen/index.php/240409?lang=en

More info: https://fz-juelich.de/en/zb/news/event

Hello,

There has recently been the development of eg defense funds for bugs or finding other fraudulent science. The problem is, at least in my opinion, that the people doing them have a long history of bullying, making fun of their targets, and etc.

It is a classic case of the people who want to be the police are probably the last people you actually want policing. As the old saying goes, there is always a little bit of truth in the joke, and the jokes have been getting out of hand the last years.

The study that i heard about was literally awarded to one of the worst offenders of this type, and is explicitly a 'bug bounty' program for non-randomly selected studies.

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Basically it allows people to select their own targets for hunting, and then will pay people for finding the errors. to me it is somehow scientifically perverse.

I am not sure there is anything we can do about it, but at least when you start seeing these bug bounty awards in the next year or so just think to yourself - are these people acting in the best interests of science or themselves?

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Again, those people who want to become the science police are probably the last people you actually want as the science police (just like normal police). thx

https://preview.redd.it/k9iu36d9o1qc1.png?width=602&format=png&auto=webp&s=fb283269b9e20a67ebec1022e790d4a6c48d711d

In a groundbreaking study published in Nature Communications, researchers have unveiled a revolutionary method for stimulating neural tissues wirelessly, using injectable microparticles activated by ultrasound. This cutting-edge technology promises to transform the treatment of neurological diseases, sensory impairments, and movement disorders, providing a new ray of hope for millions suffering worldwide.

Traditionally, conditions like Parkinson's disease, essential tremor, dystonia, obsessive-compulsive disorder (OCD), and epilepsy are treated through a surgical procedure that implants a neurostimulator along with rigid electrodes into the patient's brain. These electrodes send electrical impulses to specific brain regions controlling movement, offering significant relief. However, the complexity of the surgery and the need for a wired connection between the device and electrodes pose significant challenges and risks.

The innovative approach introduced by the study bypasses these hurdles by using tiny, injectable microparticles that can be activated externally through ultrasound. This method eliminates the need for invasive surgery and wired connections, paving the way for a safer, more accessible treatment option. Here, the authors developed cell-sized 20 μm-diameter silica-based piezoelectric magnetic Janus microparticles (PEMPs), enabling clinically-relevant high-frequency neural stimulation of primary neurons under low-intensity focused ultrasound.

Taking advantage of such functionalities, the PEMP design offers unique features towards wireless neural stimulation for minimally invasive treatment of neurological diseases.

Here you can read the article: Article link

SiDock is a volunteer computing project where people donate CPU cycles towards patent-free antivirals. They are picking their next target via public vote, such a fun project to be involved in and it's cool to get to influence scientific development this way:

https://www.sidock.si/sidock/forum_thread.php?id=268

We just launched ClimateTriage.com, a platform helping you to contribute to open source projects focused on climate technology and sustainability. Start making your first meaningful contribution to climatechange, sustainable energy, biodiversity and natural resources.

Repo: https://github.com/protontypes/climate-triage
Blog Post: https://opensustain.tech/blog/launch_climate_triage/

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large‐scale data‐driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross‐disciplinary work done within the EOSC‐Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC‐Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive‐ and industry‐related resources, by means of cross‐disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences.

My university has apparently done whatever one does to become a member of Dryad, an open-science platform (maybe just a data repository, IDK). The administrators who made this decision (without checking with anyone on campus who actually does research) have a history of pushing "open" things that are actually corporate partnerships, short-lived enterprises, niche "nobody-uses-it" services, etc.

The Dryad website certainly looks good at first glance, but I'm wondering if anyone has any experience with Dryad or (if you know some stuff about open data repositories and things like that) an assessment of how useful the service is, how much it advances open science principles, whether it's just a corporate whitewash, how long it's likely to be around, etc.

Any and all experiences and knowledge are welcome. I'm wondering if I should invest some of my energy in this, or just use something more widely known and non-corporate, like OSF.

https://onlinelibrary.wiley.com/doi/10.1002/hast.1507 "Editors and reviewers should not rely solely on generative AI to review submitted papers."

while it would have been nice if the authors of this broad statement would have actually looked at AI currently in use at publishers rather than just broadly considering ChatGPT, there is no big argument from the AI community with this statement, see https://doi.org/10.1186/s13104-022-06080-6

New paper on the Lessons From the ISIDORe and BY-COVID Consortia for Pandemic Preparedness

https://doi.org/10.5334/dsj-2023-035

The Horizon Europe project ISIDORe is dedicated to pandemic preparedness and responsiveness research. It brings together 17 research infrastructures (RIs) and networks to provide a broad range of services to infectious disease researchers. An efficient and structured treatment of data is central to ISIDORe’s aim to furnish seamless access to its multidisciplinary catalogue of services, and to ensure that users’ results are treated FAIRly. ISIDORe therefore requires a data management plan (DMP) covering both access management and research outputs, applicable over a broad range of disciplines, and compatible with the constraints and existing practices of its diverse partners.

Here, we describe how, to achieve that aim, we undertook an iterative, step-by-step, process to build a community-approved living document, identifying good practices and processes, on the basis of use cases, presented as proof of concepts. International fora such as the RDA and EOSC, and primarily the BY-COVID project, furnished registries, tools and online data platforms, as well as standards, and the support of data scientists. Together, these elements provide a path for building an umbrella, FAIR-compliant DMP, aligned as fully as possible with FAIR principles, which could also be applied as a framework for data management harmonisation in other large-scale, challenge-driven projects. Finally, we discuss how data management and reuse can be further improved through the use of knowledge models when writing DMPs and, how, in the future, an inter-RI network of data stewards could contribute to the establishment of a community of practice, to be integrated subsequently into planned trans-RI competence centres.