Importing and serving open-data medical images to support Artificial Intelligence research

Author(s):  
Sébastien Jodogne
2021 ◽  
Vol 13 (5) ◽  
pp. 124
Author(s):  
Jiseong Son ◽  
Chul-Su Lim ◽  
Hyoung-Seop Shim ◽  
Ji-Sun Kang

Despite the development of various technologies and systems using artificial intelligence (AI) to solve problems related to disasters, difficult challenges are still being encountered. Data are the foundation to solving diverse disaster problems using AI, big data analysis, and so on. Therefore, we must focus on these various data. Disaster data depend on the domain by disaster type and include heterogeneous data and lack interoperability. In particular, in the case of open data related to disasters, there are several issues, where the source and format of data are different because various data are collected by different organizations. Moreover, the vocabularies used for each domain are inconsistent. This study proposes a knowledge graph to resolve the heterogeneity among various disaster data and provide interoperability among domains. Among disaster domains, we describe the knowledge graph for flooding disasters using Korean open datasets and cross-domain knowledge graphs. Furthermore, the proposed knowledge graph is used to assist, solve, and manage disaster problems.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Elin Trägårdh ◽  
Pablo Borrelli ◽  
Reza Kaboteh ◽  
Tony Gillberg ◽  
Johannes Ulén ◽  
...  

Author(s):  
Денис Валерьевич Сикулер

В статье выполнен обзор 10 ресурсов сети Интернет, позволяющих подобрать данные для разнообразных задач, связанных с машинным обучением и искусственным интеллектом. Рассмотрены как широко известные сайты (например, Kaggle, Registry of Open Data on AWS), так и менее популярные или узкоспециализированные ресурсы (к примеру, The Big Bad NLP Database, Common Crawl). Все ресурсы предоставляют бесплатный доступ к данным, в большинстве случаев для этого даже не требуется регистрация. Для каждого ресурса указаны характеристики и особенности, касающиеся поиска и получения наборов данных. В работе представлены следующие сайты: Kaggle, Google Research, Microsoft Research Open Data, Registry of Open Data on AWS, Harvard Dataverse Repository, Zenodo, Портал открытых данных Российской Федерации, World Bank, The Big Bad NLP Database, Common Crawl. The work presents review of 10 Internet resources that can be used to find data for different tasks related to machine learning and artificial intelligence. There were examined some popular sites (like Kaggle, Registry of Open Data on AWS) and some less known and specific ones (like The Big Bad NLP Database, Common Crawl). All included resources provide free access to data. Moreover in most cases registration is not needed for data access. Main features are specified for every examined resource, including regarding data search and access. The following sites are included in the review: Kaggle, Google Research, Microsoft Research Open Data, Registry of Open Data on AWS, Harvard Dataverse Repository, Zenodo, Open Data portal of the Russian Federation, World Bank, The Big Bad NLP Database, Common Crawl.


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