IncluSet: A Data Surfacing Repository for Accessibility Datasets.

Hernisa Kacorri, Utkarsh Dwivedi, Sravya Amancherla, Mayanka K Jha, Riya Chanduka
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引用次数: 15

Abstract

Datasets and data sharing play an important role for innovation, benchmarking, mitigating bias, and understanding the complexity of real world AI-infused applications. However, there is a scarcity of available data generated by people with disabilities with the potential for training or evaluating machine learning models. This is partially due to smaller populations, disparate characteristics, lack of expertise for data annotation, as well as privacy concerns. Even when data are collected and are publicly available, it is often difficult to locate them. We present a novel data surfacing repository, called IncluSet, that allows researchers and the disability community to discover and link accessibility datasets. The repository is pre-populated with information about 139 existing datasets: 65 made publicly available, 25 available upon request, and 49 not shared by the authors but described in their manuscripts. More importantly, IncluSet is designed to expose existing and new dataset contributions so they may be discoverable through Google Dataset Search.

IncluSet:可访问性数据集的数据表面存储库。
数据集和数据共享在创新、基准测试、减轻偏见和理解现实世界人工智能应用程序的复杂性方面发挥着重要作用。然而,残疾人产生的可用数据缺乏,这些数据具有训练或评估机器学习模型的潜力。这部分是由于人口较少、特征不同、缺乏数据注释方面的专业知识以及隐私问题。即使收集了数据并公开提供,通常也很难找到它们。我们提出了一个新的数据表面存储库,称为IncluSet,它允许研究人员和残疾人社区发现和链接可访问性数据集。存储库预先填充了139个现有数据集的信息:65个公开可用,25个应要求提供,49个不为作者共享,但在其手稿中有描述。更重要的是,IncluSet旨在公开现有的和新的数据集贡献,以便可以通过Google数据集搜索发现它们。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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