Wissen zum Nachbauen: TIB startet Open-Source-Plattform für die Forschung ​ ​

Die neue digitale Bibliothek der TIB Hannover verknüpft als Open-Source-Projekt Wissenschaftsergebnisse direkt mit Original-Daten und Programmcodes für alle.

heise.de

Rethinking the production and publication of machine-readable expressions of research findings - Scientific Data

Scientific Data - Rethinking the production and publication of machine-readable expressions of research findings

doi.org

Dance Your PhD 2025: Rethinking the Production of Research Findings

This video is a submission for the special AI/quantum category of the 2025 “Dance your PhD” competition run by AAAS and Science: bit.ly/4c8Ricx Despite significant advances in digital technologies, modern scientific results are still communicated using antiquated methods. Since the first scientific article published in 1665, we have managed the switch from physically printed articles to PDFs, but these electronic documents are still text-based and not machine-readable. This means your computer cannot interpret the information they contain without some level of human assistance (e.g., detailed prompts, large amounts of training data). With millions of scientific articles published annually, researchers and other data users stand to benefit greatly from approaches that enable machine-assisted information organization and reuse. In this video, we explore the limitations of text-based PDF articles from a machine’s perspective and demonstrate how using knowledge bases that structure scientific information in a machine-readable format can address some of these challenges. Using color to represent different kinds of scientific information (think figures, tables, and statistical analyses), we look at a machine’s ability to interpret information in a text-based format compared to a machine-readable format. We use Zumba®, which uses structured dance sequences to create easy-to-learn choreographies, to represent the inherently structured nature of much scientific information, which is easily lost in PDFs. This video is inspired by research conducted at the Lab Knowledge Infrastructures led by Dr. Markus Stocker at the TIB – Leibniz Information Centre for Science and Technology in Germany. The video was produced by Lauren Snyder, a postdoctoral researcher in the lab and a licensed Zumba® instructor. We would like to extend a very special thank you to Zumba® for their permission to use and perform their original song, Guadalajara (PPL-/PPCA-free music). We are also very grateful to ZJ™ Rony Gratereaut for the Zumba® choreography that we adapted for this video. Learn more about the researcher and machine-readable scientific information here: Lauren Snyder: @laurendsnyder.bsky.social (Bluesky), @dr.zumba_lauren (Instagram) Machine-readable reborn articles: https://reborn.orkg.org For any questions related to the video, please contact Lauren at lauren.snyder@tib.eu REFERENCE Markus Stocker, Lauren Snyder, Matthew Anfuso, Oliver Ludwig, Freya Thießen, Kheir Eddine Farfar, Muhammad Haris, Allard Oelen, and Mohamad Yaser Jaradeh (2024). Rethinking the production and publication of machine-reusable expressions of research findings (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2405.13129 CREDITS Directed, Written, & Produced by Lauren Snyder with creative inspiration from Ricardo Perez Alvarez Cast (alphabetical order) Vinodh Ilangovan Ida Keller Ekaterina Mogilnaia Alica Oppermann Tobias Oppermann Susen Orth Sonja Rexin Mia Richter Maya Schaefer Lauren Snyder Filmed by Kevin Baumann & Ricardo Perez Alvarez Edited by Kevin Baumann Choreography ZJ™ Rony Gratereaut & ZIN™ Lauren Snyder Music Credits Zumba® Original - Guadalajara (PPL-/PPCA-free music) The research portrayed in this video is led by researchers at the TIB – Leibniz Information Centre for Science and Technology, and is associated with the Leibniz-Lab “Systemic Sustainability” project funded by the Leibniz Association and the FAIR2Adapt Horizon Europe Project. This project has received funding from the European Union’s HorizonEurope programme under the grant agreement number 101188256. Any dissemination of results here presented reflects only the consortium view. The Commission is not responsible for any use that may be made of the information it contains.

bit.ly

Open Research Knowledge Graph

orkg.org

Schlechter Ruf: Die Zumutungen deutscher Berufungsverfahren

Der Aufwand: irrsinnig, die Chancen: gering. Berufungsverfahren in Deutschland sind von diesem Missverhältnis geprägt. Ein Plädoyer dafür, die Zeit von Wissenschaftler_innen nicht weiter zu verschwend...

open.substack.com

Dance Your PhD 2025: Rethinking the Production of Research Findings

This video is a submission for the special AI/quantum category of the 2025 “Dance your PhD” competition run by AAAS and Science: bit.ly/4c8Ricx Despite significant advances in digital technologies, modern scientific results are still communicated using antiquated methods. Since the first scientific article published in 1665, we have managed the switch from physically printed articles to PDFs, but these electronic documents are still text-based and not machine-readable. This means your computer cannot interpret the information they contain without some level of human assistance (e.g., detailed prompts, large amounts of training data). With millions of scientific articles published annually, researchers and other data users stand to benefit greatly from approaches that enable machine-assisted information organization and reuse. In this video, we explore the limitations of text-based PDF articles from a machine’s perspective and demonstrate how using knowledge bases that structure scientific information in a machine-readable format can address some of these challenges. Using color to represent different kinds of scientific information (think figures, tables, and statistical analyses), we look at a machine’s ability to interpret information in a text-based format compared to a machine-readable format. We use Zumba®, which uses structured dance sequences to create easy-to-learn choreographies, to represent the inherently structured nature of much scientific information, which is easily lost in PDFs. This video is inspired by research conducted at the Lab Knowledge Infrastructures led by Dr. Markus Stocker at the TIB – Leibniz Information Centre for Science and Technology in Germany. The video was produced by Lauren Snyder, a postdoctoral researcher in the lab and a licensed Zumba® instructor. We would like to extend a very special thank you to Zumba® for their permission to use and perform their original song, Guadalajara (PPL-/PPCA-free music). We are also very grateful to ZJ™ Rony Gratereaut for the Zumba® choreography that we adapted for this video. Learn more about the researcher and machine-readable scientific information here: Lauren Snyder: @laurendsnyder.bsky.social (Bluesky), @dr.zumba_lauren (Instagram) Machine-readable reborn articles: https://reborn.orkg.org For any questions related to the video, please contact Lauren at lauren.snyder@tib.eu REFERENCE Markus Stocker, Lauren Snyder, Matthew Anfuso, Oliver Ludwig, Freya Thießen, Kheir Eddine Farfar, Muhammad Haris, Allard Oelen, and Mohamad Yaser Jaradeh (in press). Rethinking the production and publication of machine-reusable expressions of research findings. Scientific Data. CREDITS Directed, Written, & Produced by Lauren Snyder with creative inspiration from Ricardo Perez Alvarez Cast (alphabetical order) Vinodh Ilangovan Ida Keller Ekaterina Mogilnaia Alica Oppermann Tobias Oppermann Susen Orth Sonja Rexin Mia Richter Maya Schaefer Lauren Snyder Filmed by Kevin Baumann & Ricardo Perez Alvarez Edited by Kevin Baumann Choreography ZJ™ Rony Gratereaut & ZIN™ Lauren Snyder Music Credits Zumba® Original - Guadalajara (PPL-/PPCA-free music) The research portrayed in this video is led by researchers at the TIB – Leibniz Information Centre for Science and Technology, and is associated with the Leibniz-Lab “Systemic Sustainability” project funded by the Leibniz Association and the FAIR2Adapt Horizon Europe Project. This project has received funding from the European Union’s HorizonEurope programme under the grant agreement number 101188256. Any dissemination of results here presented reflects only the consortium view. The Commission is not responsible for any use that may be made of the information it contains.

bit.ly

Dr Ricardo Perez-Alvarez on harmonizing food production and nature - TIB-Blog

A landscape ecologist at the University of Giessen in Germany channels his curiosity about nature into his research.

blog.tib.eu

Rethinking the production and publication of machine-reusable expressions of research findings

Literature is the primary expression of scientific knowledge and an important source of research data. However, scientific knowledge expressed in narrative text documents is not inherently machine reu...

doi.org

IOS Press Ebooks - Handbook on Neurosymbolic AI and Knowledge Graphs

Neural approaches have traditionally excelled at perceptual tasks like pattern recognition, whereas symbolic frameworks have offered powerful methods for knowledge representation, logical inference, a...

dx.doi.org

Body size variation in a tropical seabird along a latitude-productivity gradient - Journal of Ornithology

Body size can vary across geographical gradients, and these clines have been mainly attributed to temperature (i.e., the heat conservation hypothesis). However, in tropical areas, this pattern is not ...

doi.org

Symbiodiniaceae diversity in Pocillopora corals in different environments of the Colombian Eastern Pacific: symbiont specificity in spite of coral-host flexibility - Coral Reefs

Reef-building corals live in close mutualism with dinoflagellate algae (family Symbiodiniaceae), which play key roles in coral physiological performance and survival. Association patterns between host...

doi.org

Open Research Knowledge Graph - EOSC Association

Case study The Open Research Knowledge Graph (ORKG) is a platform for creating, curating, publishing, and reusing FAIR scientific knowledge,... Read more

eosc.eu