BIG-MAP's Projects
Batt-O-Matic is a web form interface for generating FAIR battery metadata based on RDF standards.
A Battery Interface Ontology based on EMMO
A streamlit app for visualizing public information and results from the BIG-MAP project
Registry for BIG-MAP apps and codes. Find the apps
Mirror of the internal Fraunhofer ISC repository of the Battery Value Chain Ontology (BVCO)
Examples for the BIG-MAP WP5 workshop on data handling at CEA on June 15-16, 2023.
A simple app to create a linked metadata entry- for a tabular csv file.
Demonstrate Battery Data Semantic Search
Code for calculating the path of least resistance between two points in a scalar field using nudged elastic band.
Dosing unit with GUI for precise liquid dosing. Control via serial connection to the dosimeter. Start/stop of the dosing process, method maintenance, instrument status query. Two scripts for GUI and communication.
Optimization of LIBs electrolyte using one shot active learning
Optimizer application for the FINALES2 materials acceleration platform (MAP).
This respository contains resources and examples for generating Findable, Accessible, Interoperable, and Reusable (FAIR) battery data.
fast active learning environment
Further development of FINALES
A repository for collecting the schemas used in the FINALES2 project.
The ASAB tenant created for the use with FINALES.
The AutoBASS tenant created for the use with FINALES.
The Cycler tenant created for the use with FINALES.
The Overlort tenant created for the use with FINALES
The transportation tenant created for the use with FINALES.
An application ontology for the BIG-MAP lab notebook, based on EMMO and BattINFO
Python Package for electrochemical analysis
Materials Acquisition Form
Uses RDF linked data to make interoperable parameter descriptions for P2D Li-ion battery models
Ontology Enabled Data Interface
Toolset to import/ synchronize ontologies with a Semantic Mediawiki
This tutorial for orchestrating distributed materials acceleration platform was prepared for the BIG-MAP AI School held in January 2022 by Fuzhan Rahmanian and Jack Flowers
An app for high-throughput analysis of spectra