MEX Vocabulary: A Light-Weight Interchange Format for Machine Learning Experiments

MEX Vocabulary: A Light-Weight Interchange Format for Machine Learning Experiments

Issues Source Code Download

Over the last decades many machine learning experiments have been published, giving benefit to the scientific progress. In order to compare machine-learning experiment results with each other and collaborate positively, they need to be performed thoroughly on the same computing environment, using the same sample datasets and algorithm configurations. Besides this, practical experience shows that scientists and engineers tend to have large output data in their experiments, which is both difficult to analyze and archive properly without provenance metadata. However, the Linked Data community still misses a light-weight specification for interchanging machine-learning metadata over different architectures to achieve a higher level of interoperability. MEX provides a prompt method to describe experiments with a special focus on data provenance and fulfills the requirements for a long-term maintenance

Publications

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News

DBpedia Knowledge Engineering PhD Symposium ( 2022-05-02T16:59:37+02:00 by Julia Holze)

2022-05-02T16:59:37+02:00 by Julia Holze

Dear all,  We are excited to invite you to the 1st DBpedia Knowledge Engineering PhD Symposium, organized on July 6th, 2022 in Leipzig, Germany. Read more about "DBpedia Knowledge Engineering PhD Symposium"

Tutorial @ Knowledge Graph Conference 2022 ( 2022-04-25T12:24:06+02:00 by Julia Holze)

2022-04-25T12:24:06+02:00 by Julia Holze

On May 2, 2022 we will organize a tutorial 2.0 at the Knowledge Graph Conference (KGC) 2022. Read more about "Tutorial @ Knowledge Graph Conference 2022"

International Workshop on Data-driven Resilience Research 2022 ( 2022-04-21T14:43:27+02:00 by Julia Holze)

2022-04-21T14:43:27+02:00 by Julia Holze

In the face of continuously changing contextual conditions and ubiquitous disruptive crisis events, the concept of resilience refers to some of the most urgent, challenging, and interesting issues of nowadays society. Read more about "International Workshop on Data-driven Resilience Research 2022"

DBpedia @ Google Summer of Code Program 2022 ( 2022-03-23T14:26:48+01:00 by Julia Holze)

2022-03-23T14:26:48+01:00 by Julia Holze

DBpedia, one of InfAI’s community projects, will be part of the 11th Google Summer of Code (GSoC) program. The GSoC program has the goal to bring students from all over the globe into open source software development. Read more about "DBpedia @ Google Summer of Code Program 2022"

DBpedia Tutorial @ The Web Conference 2022 ( 2022-03-16T13:52:16+01:00 by Julia Holze)

2022-03-16T13:52:16+01:00 by Julia Holze

Dear all, We are proud to announce that we will organize an online tutorial at the Web Conference on 25th of April 2022. A particular focus will be put on the DBpedia Infrastructure, i.e. Read more about "DBpedia Tutorial @ The Web Conference 2022"