KGA "XAIR principles" WG - M10 deliverable: Synopsis of core concepts for explainable-AI-ready data and models

Reliable AI technology necessitates the development of robust validation infrastructures and data documentation schemas to ensure that AI systems become trustworthy and transparent. The International Workshop on Designing the Conceptual Landscape for a XAIR Validation Infrastructure (DCLXVI 2024), held on 11th December 2024 in Kaiserslautern, Germany, surveyed the conceptual landscape of explainable-AI-ready (XAIR) models and data. The definition of concepts relevant to data integrity, algorithmic transparency, and user interpretability were explored, resulting in a synopsis of core concepts for "XAIR".

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-31
DOI
https://doi.org/10.5281/zenodo.14582690
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

KGA "XAIR principles" WG - M10 deliverable: Synopsis of core concepts for explainable-AI-ready data and models

Zenodo (CERN European Organization for Nuclear Research)
Explainable Artificial Intelligence (XAI)
article

KGA "XAIR principles" WG - M10 deliverable: Synopsis of core concepts for explainable-AI-ready data and models

article en

Abstract

Reliable AI technology necessitates the development of robust validation infrastructures and data documentation schemas to ensure that AI systems become trustworthy and transparent. The International Workshop on Designing the Conceptual Landscape for a XAIR Validation Infrastructure (DCLXVI 2024), held on 11th December 2024 in Kaiserslautern, Germany, surveyed the conceptual landscape of explainable-AI-ready (XAIR) models and data. The definition of concepts relevant to data integrity, algorithmic transparency, and user interpretability were explored, resulting in a synopsis of core concepts for "XAIR".

Zenodo (CERN European Organization for Nuclear Research)
Institute for Applied Systems Technology Bremen (DE), Norwegian University of Life Sciences (NO)
Industry, innovation and infrastructure
Openalex Percentile: Top 57%
Explainable Artificial Intelligence (XAI)
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

KGA "XAIR principles" WG - M10 deliverable: Synopsis of core concepts for explainable-AI-ready data and models · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS