incubator.html

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<logo><img src="assets/img/knowledge-pixels-logo-rgb.svg" alt="Knowledge Pixels logo" /></logo>
<sub>building<br>the future<br>of knowledge</sub>
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<h2>Knowledge Pixels Incubator</h2>

<p>Our incubator program is where new use cases around nanopublications can start and grow.</p>

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<h3>What we are looking for</h3>

<p>We are looking for individuals interested in:</p>
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<li>Making the first steps of applying the nanopublication ecosystem to their use case</li>
<li>Exploring ways to obtain funding to implement their use case through co-creation with Knowledge Pixels</li>
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<h3>What you get</h3>

<p>As part of the incubator program you will receive:</p>
<ul>
<li>Supervision and guidance</li>
<li>Weekly office hours with our developers</li>
<li>Prioritized feature requests</li>
<li>Materials to help you pitch your use case</li>
<li>Visibility of your use case via our website, Nanodash, and other channels</li>
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<h3>FAQ</h3>

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Do I need to be a programmer to apply?
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<ul>
<li>You don't need to be a programmer, but you should be comfortable of doing technical work, such as defining templates in Nanodash and formally modeling knowledge</li>
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Can I apply as a group or as an organization?
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<li>
We ask you to apply as individual. You can have others helping you and your organization be named and involved, but we need a single contact point as applicant and throughout the project.
<strong>Update:</strong> We are now also accepting duo projects, with two individuals applying.
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How long do incubator projects run?
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<li>Incubator projects have a default life span of six months, but they can terminate early and extensions are possible too</li>
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Do you have a question that is not listed here?
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<li>We are happy to answer further questions via <a href="mailto:info@knowledgepixels.com">info@knowledgepixels.com</a></li>
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<h3>How to apply</h3>

<p>
To apply, send a short paragraph describing your use case, motivation, organization (if applicable), and potential funding opportunities to <a href="mailto:info@knowledgepixels.com">info@knowledgepixels.com</a>.
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<h2>Current Incubator Projects</h2>

<p>Here you find our currently running incubator projects.</p>

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<div class="portrait" id="incubator2daniel">
<a title="Ralf Rebmann, CC BY-SA 4.0 &lt;https://creativecommons.org/licenses/by-sa/4.0&gt;, via Wikimedia Commons" href="https://commons.wikimedia.org/wiki/File:Daniel_Mietchen.jpg">
<img alt="Daniel Mietchen" src="assets/img/incubator2daniel.jpg" style="float: right; margin: 2em;">
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<h3 id="incubator2">#2: nanopublication-Enhanced Open Science Communication (nEOSC)</h3>

<p><em>by <a href="https://www.fiz-karlsruhe.de/de/bereiche/lebenslauf-und-publikationen-dr-daniel-mietchen" target="_blank">Daniel Mietchen</a>, FIZ Karlsruhe</em></p>

<p>
This project uses nanopublications to enhance the sharing of scientific information in a machine-readable fashion and around the research cycle.
It tackles practical needs like formally acknowledging contributors, pointing out issues such as broken DOIs, and documenting the state of dynamically changing resources. 
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<div class="portrait" id="incubator3margreet">
	<img src="assets/img/incubator3margreet.jpg" alt="Margreet Bloemers" style="float: right; margin: 2em;"/>
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<h3 id="incubator3">#3: Integrating DCAT-compliant nanopublications and EHDS-metadata</h3>

<p><em>by Margreet Bloemers, <a href="https://www.zonmw.nl/" target="_blank">ZonMw</a></em></p>

<p>
In this incubator project, we will develop an approach for an integrated analysis of metadata collected with two different, DCAT-AP compliant metadata systems:
(1) nanopublication templates of the FAIR Funding Framework (FFF) and (2) the metadata scheme that forms the basis for the National Health Metadata Catalogue (under development in the Netherlands) with metadata on datasets that are available for secondary use.
The National Catalogue is a mandatory implementation for the European Health Data Space (EHDS) in each EU-member state.

The FFF provides a uniform approach for funders and research organisations aiming to collect reusable (FAIR) information for tracking research outputs and funder activities,
using nanopublication-based metadata on components of the (1) funder’s grant procedures, (2) research lifecycles, and (3) tools and services used in research domains.

The project aims to deliver a scalable approach for creating rich, machine-actionable information on projects, datasets and other outputs.
The approach must facilitate dataset-related metadata to get exposed on the EHDS-National Catalogue. This information can be supplemented with project-related information from FFF nanopublications.
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<div class="portrait" id="incubator4erik">
    <img src="assets/img/incubator4erik.jpg" alt="Erik Schultes" style="float: right; margin: 2em;"/>
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<h3 id="incubator4">#4: FAIRification of mass spectrometry workflows using FDOs</h3>

<p><em>by Erik Schultes, <a href="https://www.universiteitleiden.nl/en/science/drug-research/metabolomics-and-analytics-centre" target="_blank">Metabolomics and Analytics Centre (MAC)</a></em></p>

<p>
Mass spectrometry research confronts challenges endemic to data-intensive science:
vendor-specific proprietary formats from multiple Mass Spectrometry instruments, complex multi-consortium governance, and the near-impossibility of tracking provenance across thousands of
heterogeneous digital objects spanning clinical samples, instrument logs, processing workflows, and publications.
Traditional approaches that retrofit FAIR principles onto existing repositories fail at scale and perpetuate the research integrity and reproducibility crises.
This project addresses this systemic failure by implementing nanopublication-based FAIR Digital Objects (FDOs) as minimal, but precise metadata tags at the source,
combining automated and human curated machine-actionable assertions that establish unambiguous provenance chains before data enters any workflow.
This source-level FAIRification demonstrates that trusted AI in biomedicine requires fundamentally reliable data infrastructure
where agentic AI can automatically assess the quality, context, and trustworthiness of every datum from its moment of creation. 
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<div class="portrait" id="incubator5elena">
    <img src="assets/img/incubator5elena.jpg" alt="Elena Del Pup" style="float: right; margin: 2em;"/>
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<h3 id="incubator5">#5: A community-driven linked knowledge base for plant specialized metabolism</h3>

<p><em>by Elena Del Pup, <a href="https://www.wur.nl/" target="_blank">Wageningen University &amp; Research</a></em></p>

<p>
Plant specialized metabolites are a major source of medicines, novel foods, and natural products, yet the knowledge needed to discover and characterize them remains scattered across publications, databases, and tools. This project uses nanopublications to build <a target="_blank" href="https://plantmetwiki.bioinformatics.nl/">PlantMetWiki</a>, a queryable, community-driven knowledge base that links experimentally characterized plant biosynthetic pathways with repositories such as PlantCyc, plantiSMASH, MIBiG, and LOTUS. By representing pathway data, multi-omics predictions, and community annotations as nanopublications, the knowledge base enables machine-readable sharing and continuous integration of new findings. Researchers will be able to query across experimental and predicted data to prioritize promising biosynthetic candidates for wet-lab validation, while contributing their own results back to the community as Linked Open Data.
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<div class="portrait" id="incubator6mitja">
    <img src="assets/img/incubator6mitja.jpg" alt=""Mitja M. Zdouc style="float: right; margin: 2em;"/>
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<h3 id="incubator6">#6: Nanopublications in Natural Product Drug Discovery</h3>

<p><em>by Mitja M. Zdouc, <a href="https://zdouclab.org/" target="_blank">ZdoucLab</a>, <a href="https://www.univie.ac.at/en/" target="_blank">University of Vienna</a></em></p>

<p>
Many medicines are derived from natural products (NPs), small molecules produced by a variety of organisms. NP drug discovery screens these organisms for specific biological properties, with the aim to discover new molecules. However, traditional publication formats are strongly biased towards positive results, are of limited machine-readability, and are often only published years after experiments have been conducted. In this project, we explore nanopublications as a format to publish NP drug discovery results in a prospective, machine-readable, and unbiased manner. By modeling the discovery workflow as nanopublications, we are building a federated, free open source knowledge graph of experimental NP research data. Such a resource will democratize access to knowledge, connect heterogeneous, monolithic databases, and lead to an abundance of linked open data, accelerating NP drug discovery.
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<h2>Past Incubator Projects</h2>

<p>These projects have successfully concluded</p>

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<div class="portrait" id="incubator1gertjan">
<img src="assets/img/incubator1gertjan.jpg" alt="Gertjan Bisschop" style="float: right; margin: 2em;"/>
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<h3 id="incubator1">#1: FAIR Vocabularies for Chemical Risk Assessment</h3 id="incubator1">

<p><em>by Gertjan Bisschop, <a href="https://vito.be" target="_blank">VITO</a></em></p>

<p>
As part of the PARC (Partnership for the Assessment of Risks from Chemicals) consortium, we are developing a FAIR data platform that will help assess the health impact of chemicals.
A crucial component of this platform is the management of vocabularies.
Since the platform is intended to support ongoing and evolving research from institutes across Europe, we consider dynamic, community-driven vocabulary management to be essential.
We believe that nanopublications offer a strong foundation for achieving this goal.
Our initial focus will be on the vocabularies associated with the Personal Exposure and Health domain, with the aim of extending this approach to other domains within PARC, encouraging the reuse of the workflows and pipelines we develop.
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