BioBricks.ai: A Versioned Data Registry for Life Sciences Data Assets
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arXiv
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| Autores principales: | , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866909301498445824 |
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| author | Gao, Yifan Mughal, Zakariyya Jaramillo-Villegas, Jose A. Corradi, Marie Borrel, Alexandre Lieberman, Ben Sharif, Suliman Shaffer, John Fecho, Karamarie Chatrath, Ajay Maertens, Alexandra Teunis, Marc A. T. Kleinstreuer, Nicole Hartung, Thomas Luechtefeld, Thomas |
| author_facet | Gao, Yifan Mughal, Zakariyya Jaramillo-Villegas, Jose A. Corradi, Marie Borrel, Alexandre Lieberman, Ben Sharif, Suliman Shaffer, John Fecho, Karamarie Chatrath, Ajay Maertens, Alexandra Teunis, Marc A. T. Kleinstreuer, Nicole Hartung, Thomas Luechtefeld, Thomas |
| contents | Researchers in biomedical research, public health, and the life sciences often spend weeks or months discovering, accessing, curating, and integrating data from disparate sources, significantly delaying the onset of actual analysis and innovation. Instead of countless developers creating redundant and inconsistent data pipelines, BioBricks.ai offers a centralized data repository and a suite of developer-friendly tools to simplify access to scientific data. Currently, BioBricks.ai delivers over ninety biological and chemical datasets. It provides a package manager-like system for installing and managing dependencies on data sources. Each 'brick' is a Data Version Control git repository that supports an updateable pipeline for extraction, transformation, and loading data into the BioBricks.ai backend at https://biobricks.ai. Use cases include accelerating data science workflows and facilitating the creation of novel data assets by integrating multiple datasets into unified, harmonized resources. In conclusion, BioBricks.ai offers an opportunity to accelerate access and use of public data through a single open platform. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_17320 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | BioBricks.ai: A Versioned Data Registry for Life Sciences Data Assets Gao, Yifan Mughal, Zakariyya Jaramillo-Villegas, Jose A. Corradi, Marie Borrel, Alexandre Lieberman, Ben Sharif, Suliman Shaffer, John Fecho, Karamarie Chatrath, Ajay Maertens, Alexandra Teunis, Marc A. T. Kleinstreuer, Nicole Hartung, Thomas Luechtefeld, Thomas Databases Quantitative Methods Researchers in biomedical research, public health, and the life sciences often spend weeks or months discovering, accessing, curating, and integrating data from disparate sources, significantly delaying the onset of actual analysis and innovation. Instead of countless developers creating redundant and inconsistent data pipelines, BioBricks.ai offers a centralized data repository and a suite of developer-friendly tools to simplify access to scientific data. Currently, BioBricks.ai delivers over ninety biological and chemical datasets. It provides a package manager-like system for installing and managing dependencies on data sources. Each 'brick' is a Data Version Control git repository that supports an updateable pipeline for extraction, transformation, and loading data into the BioBricks.ai backend at https://biobricks.ai. Use cases include accelerating data science workflows and facilitating the creation of novel data assets by integrating multiple datasets into unified, harmonized resources. In conclusion, BioBricks.ai offers an opportunity to accelerate access and use of public data through a single open platform. |
| title | BioBricks.ai: A Versioned Data Registry for Life Sciences Data Assets |
| topic | Databases Quantitative Methods |
| url | https://arxiv.org/abs/2408.17320 |