Collective Knowledge (CK)
Developers	Grigori Fursin and thecTuning foundation
Initial release	2015; 11 years ago (2015)
Stable release	2.6.3 (discontinued for the newCollective Mind framework[1]) / November 30, 2022 (2022-11-30)
Written in	Python
Operating system	Linux,Mac OS X,Microsoft Windows,Android
Type	Knowledge management,FAIR data,MLOps,Data management,Artifact Evaluation,Package management system,Scientific workflow system,DevOps,Continuous integration,Reproducibility
License	Apache License for version 2.0 andBSD License 3-clause for version 1.0
Website	github.com/ctuning/ck,cknow.io

TheCollective Knowledge (CK) project is anopen-sourceframework andrepository to enable collaborative, reproducible and sustainable research and development of complex computational systems.^[2] CK is a small, portable, customizable and decentralized infrastructure helping researchers and practitioners:

• share their code, data and models as reusablePython components and automation actions^[3] with unifiedJSONAPI, JSON meta information, and aUID based onFAIR principles^[2]
• assemble portable workflows from shared components (such as multi-objective autotuning andDesign space exploration^[4])
• automate,crowdsource and reproduce benchmarking of complex computational systems^[5]
• unifypredictive analytics (scikit-learn,R, DNN)
• enable reproducible and interactive papers^[6]

• ARM uses CK to accelerate computer engineering^[7]
• SeveralACM-sponsored conferences use CK to automate the Artifact Evaluation process^[8][9]
• Imperial College (London) uses CK to automate andcrowdsourcecompiler bug detection^[10]
• Researchers from theUniversity of Cambridge used CK to help the community reproduce results of their publication in the International Symposium on Code Generation and Optimization (CGO'17) during Artifact Evaluation^[11]
• General Motors (USA) uses CK to crowd-benchmarkconvolutional neural network optimizations^[12][13]
• TheRaspberry Pi Foundation and thecTuning foundation released a CK workflow with a reproducible "live" paper to enable collaborative research into multi-objective autotuning and machine learning techniques^[4]
• IBM uses CK to reproducequantum results from nature^[14]
• CK is used to automate MLPerf benchmark^[15][16]

CK has an integrated cross-platform package manager withPython scripts,JSON API andJSON meta-description to automatically rebuild software environment on a user machine required to run a given research workflow.^[17]

CK enables reproducibility of experimental results via community involvement similar toWikipedia andphysics. Whenever a new workflow with all components is shared via GitHub, anyone can try it on a different machine, with different environment and using slightly different choices (compilers, libraries, data sets). Whenever an unexpected or wrong behavior is encountered, the community explains it, fixes components and shares them back as described in.^[4]

• Development site:[1]
• Documentation:[2]
• Public repository with crowdsourced experiments:[3]
• International Workshop on Adaptive Self-tuning Computing System (ADAPT) uses CK to enable public reviewing of publications and artifacts viaReddit:[4]

• Workflow applications
• Build automation

• Articles with short description
• Short description is different from Wikidata