Nanopublications are a way to share small bits of structured knowledge along with bibliographic and provenance metadata. In this session, we will take a look at some existing nanopublications and consider how such mechanisms could fit into different parts of the research cycle, e.g. to express gratitude for resources used, or to signal updates or other changes to existing resources.

For more info, check out https://nanopub.net/ .

Within the Wikimedia community, the concept of Hubs is being explored as a new level of organization. Some Hubs already exist, usually with a geography-based focus. This could be complemented by theme-based initiatives, of which a Science Hub would be an option. In this session, we will explore how the pros and cons of such a structure and whether and how to go about creating it. For more information, check out https://meta.wikimedia.org/wiki/Science_Hub .

A key element of the research landscape are things we do not know. These knowledge gaps are shared even less systematically than what we do know, so while there are a lot of knowledge bases, databases and other information infrastructures, it is much harder to find systematic circumscriptions of what is not known. In this session, we could explore how to go about creating one.

In two previous barcamps we came together to reflect on successes that came from do some form of Open Science. This year, we will run the third edition.

We will talk about:

Which successes have you achieved by practicing Open Science in your career that you would not have achieved otherwise?

Which success stories do you know from others?

I would like to collect success stories that we can all share across our networks and use to illustrate the concrete benefits of OS practices.

The harsher political climate and anti-science authoritarian regimes are an increasing threat to open and free research and researchers. It would be good to discuss how researchers and their communities can stay or become resilient in these circumstances. What are strategies to prevent, protect, resist, withstand and repair research and our communities. What are the various communities that are relevant in this regard? This can range from small communities to provide solidarity and mental support when researchers that are openly communicating get harassed to communities resisting governments policies that intrude on academic freedom to communities that help protect open infrastructures that get defunded, deleted or get battered by AI bots. In these cases and others, what are the mechanisms and communities that are most helpful in weathering the storm? I have a model that could inspire the discussion (https://akademienl.social/@jeroenbosman/114499490285712095), but that focusses on the resilience strategies. In this session I would like to focus on the communities: personal, local, national, international, disciplinary, tool/platform focussed, value-based etc. There might be a connection to Henriks proposal below.

Open Research Data Management Infrastructure: Building the Backbone of Open Science

The Challenge:

Even when good open research data infrastructure exists, researchers often don't adopt it. And even when they do adopt it, how do we keep it running? The biggest infrastructure challenges often aren't technical - they're human and financial. How do we build data management infrastructure that researchers actually want to use, and how do we fund it sustainably?

What We'll Explore:

The adoption challenge: Why do researchers stick with suboptimal tools? How can we design research data infrastructure that fits naturally into existing workflows?

The sustainability challenge: How do we fund open infrastructure long-term? What funding models work beyond initial grants?

Discussion Points

What makes you choose one research tool over another? When have you abandoned a "better" tool for convenience?

How can we make research data management tools feel like essential workflow tools rather than compliance exercises?

What are the hidden barriers to adoption that infrastructure builders often miss?

What can we learn from tools researchers love and apply to research infrastructure?

How do successful open infrastructure projects sustain themselves? What can we learn from examples like arXiv, ORCID, or Wikipedia?

Why This Matters Now

As research becomes increasingly data-intensive, robust data management infrastructure is essential for scientific progress. But the best infrastructure is useless if researchers won't use it - and even great, well-adopted infrastructure fails if we can't fund it sustainably. Let's discuss how to bridge both gaps.

Without public data, there is no Open Science.

How can we make sure that this data keeps being accessible?

Let's discuss possible ways to achieve that, as well as the challenges ahead.

I can contribute the experience we (Safeguarding Research & Culture - https://safeguar.de) have with using a BitTorrent-Swarm to store public data and keep it accessible: https://sciop.net

Geospatial metadata has the potential to connect research across disciplines. Relations in space and time between articles, data, and people can help to answer research questions in novel ways.

Which area(s) and location(s) does a research paper investigate?

Where and when was research data collected?

While this seems straightforward information for many research datasets and publications, this is rarely modeled as useable information in the current scholarly communication infrastructure (journal websites, data repositories, catalogues, ..).

In this session, we explore what are the new connections that geospatial metadata can facilitate, and which are the most relevant infrastructures, services, and tools that need to be enhanced to make this happen. We will try to create a convincing storyline targeting the identified stakeholders so that they will help to implement geospatial metadata in an open and useful way.

How can we harness Open Science to create a more sustainable and equitable future?

Open Science has the potential to drive innovation and accelerate progress toward achieving the Sustainable Development Goals (SDGs) by making knowledge freely accessible, fostering collaboration, and ensuring transparency in research. This session will explore how Open Science principles, such as open access, data sharing, citizen science, and stakeholder engagement, can support evidence-based decision-making for global challenges like climate action, health, food security and education.