About SciSchema.org

SciSchema.org is a collaborative, community-driven initiative with a mission to create, maintain, and promote schemas for machine-readable scientific process descriptions.

SciSchema.org aims to make scientific methods more transparent, comparable, reusable, and machine-actionable. The initiative develops schemas for experimental, computational, and analytical processes across scientific domains.

The project combines domain expertise, semantic technologies, and AI-assisted schema mining workflows implemented through the schema-miner software platform.

Community discussion takes place through the SciSchema.org Google Group. For project-related inquiries, contact: sciknoworg [at] gmail [dot] com

Organization

SciSchema.org is coordinated as an open scientific community initiative. The day-to-day direction of the project, including schema design principles, community organization, tooling, and publication workflows, is led by Jennifer D'Souza. Technical development is supported by the schema-miner software effort.

Research Foundations

SciSchema.org emerged from research on AI-assisted scientific schema discovery, schema engineering, and ontology grounding. The initiative builds upon the schema-miner software platform and a series of research efforts investigating how large language models and domain experts can collaboratively develop machine-readable representations of scientific processes.

The development and evaluation of schema-miner and schema-miner^pro are documented in the following publications:

• Sadruddin, S., D'Souza, J., Poupaki, E., Watkins, A., Babaei Giglou, H., Rula, A., ... & Kessels, E. (2025). LLMs4SchemaDiscovery: A Human-in-the-Loop Workflow for Scientific Schema Mining with Large Language Models . In European Semantic Web Conference (ESWC 2025), pp. 244–261. Cham: Springer Nature Switzerland.
• Sadruddin, S., D'Souza, J., Poupaki, E., Watkins, A., Karasulu, B., Auer, S., ... & Kessels, E. (2026). schema-miner^pro: Agentic AI for Ontology Grounding Over LLM-Discovered Scientific Schemas in a Human-in-the-Loop Workflow . Semantic Web, 17(3), 22104968261431521.

People

A number of people have made substantial contributions to SciSchema.org. These include:

• Jennifer D'Souza founded SciSchema.org and leads the initiative. She oversees the scientific vision, community organization, schema design principles, publication strategy, and overall project direction.
• Sameer Sadruddin serves as the lead developer of schema-miner, the software platform supporting AI-assisted schema discovery and schema engineering workflows within SciSchema.org.
• Anisa Rula is an early close community collaborator and contributes to the development of SciSchema.org as a semantic technology and community initiative.

Founding Contributors

The founding contributors helped shape SciSchema.org through early schema development, domain expertise, and validation across a range of scientific processes. These include:

• George Demetriou of the University of Manchester contributed work on CRISPR-Cas9 process schemas.
• Gagana B, an independent researcher in India, contributed work on Stroop task schemas.
• Tarun Kumar of HPE Labs contributed work on RNA-Seq differential gene expression analysis workflows.
• Shaokai Yang of the University of Alberta contributed work on neutrino event reconstruction schemas.
• Frank Krüger and Sascha Genehr of Wismar University of Applied Sciences, and Kai Budde-Sagert of the University of Rostock contributed work on electrical cell stimulation schemas.
• Yan Sha of the University of Alberta contributed work on Torrance Tests of Creative Thinking schemas.
• Alyssa Columbus of Johns Hopkins University contributed work on Polymerase Chain Reaction schemas.
• Anamaria Leonescu of University College London contributed work on metal-organic cage synthesis schemas.
• Dongjun Jeong of Narnia Labs contributed work on fatigue testing schemas for metallic materials.
• Defne Circi, Anlan Chen, and Cate Brinson of Duke University contributed work on solvent-casting schemas for polymer composites.
• Nazia Riasat of North Dakota State University contributed work on bulk RNA-seq library preparation and sequencing schemas.
• Samson Olagbile of Dangote Fertiliser Limited contributed work on steam reforming schemas.
• Kevin Shen of SES.AI contributed work on Dynamic Mechanical Analysis schemas.
• Syed Ather of Georgia Institute of Technology contributed work on iterative tomographic image reconstruction schemas.
• Ana de Souza Bossler, Andrés Fullana, and Enric Bas of the University of Alicante contributed work on catalytic pyrolysis of mixed plastic waste.
• Francesco Lodola and Chiara Florindi of the University of Milano-Bicocca contributed work on multi-electrode array recording schemas.

Related Initiatives

SciSchema.org builds upon and complements broader efforts in semantic scholarly communication, knowledge graphs, and machine-actionable scientific knowledge.

• Open Research Knowledge Graph (ORKG), an open infrastructure for the representation, organization, and comparison of scholarly knowledge.
  
  Auer, S., D'Souza, J., Farfar, K. E., Jaradeh, M. Y., Jiomekong, A., Karras, O., Oelen, A., Snyder, L., Stocker, M., & Vogt, L. (2025). Open Research Knowledge Graph: A Large-Scale Neuro-Symbolic Knowledge Organization System . In Handbook on Neurosymbolic AI and Knowledge Graphs, Frontiers in Artificial Intelligence and Applications (FAIA), vol. 400, IOS Press, pp. 385–420.