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University of Arizona ResBaz Features Talk on Data Publication in ReDATA

By: Sumana Nandipati, West Hub High School Intern


Earlier this year, the University of Arizona (UA) hosted its annual Research Bazaar, or ResBaz, a festival that focuses on digital literacy among multiple disciplines. Included in this year’s ResBaz was a talk about FAIR (findable, accessible, interoperable, and reusable) principles by Fernando Rios of UA’s Library Research Data Management team.

Rios specifically spoke about data publication in ReDATA. He went into detail about why and how to publish datasets under the FAIR principles, which ensures that published data is Findable, Accessible, Interoperable, and Reusable.


Rios also explained the facets of ReData — a long-term public archive. He explained how to best prepare datasets for reproducible research, and how to upload the data to the ReDATA platform.


“Preparing and uploading data to ReDATA is quite straight-forward,” Rios said. “Depositors organize and document their data according to our deposit guidelines document. They then drag and drop their files into the web browser, which automatically creates a metadata record. After completing the record and submitting the item, it undergoes review to help depositors ensure all the i’s are dotted and t’s crossed. After the review is completed, the item is published (or embargoed if the depositor requires it) .”

ResBaz is sponsored each year by several university’s affiliates — including UA’s Data Science Institute (DSI), which is an institution for research and education in the field of data science. Comprising experts from diverse fields such as computer science, statistics, mathematics, engineering and social sciences, the DSI is dedicated to promoting interdisciplinary collaboration to advance the field of data science.

The institute offers a range of services and resources to support research and education in data science, including data analytics consulting, data visualization, and data management services. In addition, the DSI provides training and education programs for undergraduate and graduate students in data science and related fields. The institute also offers workshops and short courses for professionals and researchers who want to stay up-to-date with the latest developments in data science.

One of the key focuses of the DSI is to promote interdisciplinary research that addresses real-world problems. The institute's researchers have tackled a wide range of challenges across industries, from healthcare and environmental conservation to finance and social justice. The DSI's interdisciplinary approach enables its researchers to provide unique insights and solutions to complex problems.

The DSI is also committed to engaging with the broader community. The institute hosts events and workshops to promote public awareness of data science and its applications. They partner with industry and government organizations to provide expertise and support in data-driven decision-making. The institute also collaborates with other institutions to advance the field of data science through research and education.

The DSI's research activities cover a broad range of topics, from machine learning and data mining to natural language processing and computer vision. The institute's researchers work on developing new algorithms and tools for data analysis, as well as applying these tools to real-world problems. The DSI's research has been published in top-tier journals and presented at leading conferences in the field of data science.

In addition to its research and education programs, the DSI also promotes diversity and inclusion in data science. The institute offers scholarships and fellowships to students from underrepresented groups in STEM fields, as well as initiatives to promote diversity and inclusion in data science education and research. They also offer various educational programs, including a Bachelor of Science in Data Science, a Master of Science in Data Science, and a PhD in Computer Science with a focus on Data Science.

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