Machine-actionable Knowledge for Earth Science
Introductory talk
- Speaker: Anna-Lena Lorenz
- Date: 2025-06-12
Key Points
- Scientific knowledge is still mostly communicated in human-readable formats.
- Open Research Knowledge Graph (ORKG) is a system that improve FAIR principles in scientific communication.
- ORKG describes knowledge with concise, machine-actionable Metadata.
- ORKG presents result values of publications.
- The ORKG Python package orkg is available to interact with the ORKG API.
- With the LaTeX package SciKGTeX, structured publication metadata can be integrated in writing workflows.
My notes
- Public large-scale scholarly datasets are useful reference corpora for benchmarking metadata extraction workflows.
- The ORKG seems like a global open-source version of the obsidian graph view with result values included.
My Questions
- The location parameter is not very specific
- Confidence levels should be clearly defined
- How do we handle sources (quality, trustworthiness)?
- Will this lead to (false) equivalency traps?
Advancing FAIR principles in scientific communication through reborn articles
- Speaker: Lauren Snyder
- Date: 2025-06-12
Key Points
- Machines cannot interpret most scientific data
- But what if we could produce scientific data in a machine-readable form?
- The Python package dtreg uses schemas for graphics
- ORKG Reborn yields machine-readable information about the figures and machine environments under which publications were produced.
- ORKG reborn also yields machine-readable information about single statements in publications.
- ORKG reborn focuses on the breakdown of scientific publications into single statements and aims to contextualize them with metadata and persistent identifiers such as DOI.
My notes
- It seems to be an interesting approach to break down scientific publications into single statements.
How to get the most out of ORKG for your discipline
- Speaker: Anna-Lena Lorenz
- Date: 2025-06-12
Key Points
- Each discipline has different needs and requirements
- We can set up observatories for our discipline
- Domain experts work with data curators on this observatory
- This helps for organizing, ensuring quality standard, creation of templates, promoting ORKG and staying in contact with the development team.
Links
ORKG
ORKG reborn
See also: Open Research Knowledge Graph, Knowledge graph, Metadata, ORKG reborn, MOC Open Science Data and Knowledge Graphs