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UC Love Data Week (UC LDW), the annual festival for data lovers, was held February 13-17, 2023, and attracted over 1100 registered attendees across 12 UC communities, a 3% increase from last year. Committed to providing various types of workshops ranging from demonstrations to seminars and from hands-on to discussions, the UC LDW committee once again brought together almost 30 unique data-centric workshops for participants of diverse backgrounds. In addition to the UC campuses and organizations that participated last year, UC LDW welcomed the UC Division of Agriculture and Natural Resources (UC ANR) as part of the team.
Unlike other traditional events, UC LDW offers demos and discussions that focus on various programming tools and presents workshops on data access, management, security, sharing and preservation. The events incorporate qualitative and quantitative data and provide specialized topics in mapping and GIS, reproducibility in machine learning and more.
This year, Leigh Phan from UCLA’s Data Science Center and Kat Koziar from UC Riverside co-led innovative workshops on Wikidata. Wikidata(opens in a new tab) is an open access knowledge base that provides structured and linked data for Wikipedia and third-party applications and researchers. The duo planned a three-day series with an introductory seminar, a hands-on workshop on retrieving Wikidata with SPARQL, and a Wikidata edit-a-thon for more practice. Leigh said UC LDW organizers “found this event to be a great opportunity to introduce topics that are more specialized and unique,” which inspired her to pursue the topic suggested by her collaborator. They wanted the UC community to become more aware of Wikidata. Its interlinked data structure enables easier semantic queries of open-access data, making it a powerful resource across disciplines.
Another workshop led by UCLA was “Exploring Digital Archives,” hosted by Wendy Kurtz and Anthony Caldwell from the Digital Humanities Program. During this workshop, Wendy and Anthony introduced various tools and techniques that enable researchers to capture, search, and synthesize information stored in digital archives. Wendy stated that “the need to gather, structure and analyze data” is a crucial commonality while working with data from various disciplines. Therefore, the team designed the workshop to showcase a workflow incorporating numerous tools, “highlighting multiple applications that could be useful at different points of the research process.”
Nitika Sharma, a postdoctoral researcher at the Center for Impact at UCLA Anderson School of Management who uses data analysis daily, attended the Web Archiving as Data workshop hosted by Tori Maches and Stephanie Labou from UCSD. Nitika said the workshop was the most memorable part of her UC LDW experience because she was surprised to learn how web scraping and text mining techniques can be applied to a very different domain from her own - in corporate environmental, social and governance (ESG) disclosures. In addition, she said it was highly enlightening for her to meet experts in different data science tools across UC who “were very approachable and enthusiastic to answer [her] queries.”
Recordings and materials from UC LDW are now available on the official event site, and we encourage you to check them out. We are happy to see the event grow in the diversity of offerings each year, enabling attendees to “apply skills they have learned in previous, more introductory workshops on more intermediate and advanced topics,” as Leigh mentioned.
While this year’s UC LDW has ended, the UC LDW organizing committee looks forward to making the event even better for the years to come. As we receive positive feedback on the diversity of topics, UC LDW aims to offer various topics that haven't been covered in the past during the event, such as text analysis and potentially increase involvement from other campus departments. As for future UC LDW events, Nitika hopes to see a networking component to the week “to encourage collaborations and develop a circle of data scientists to overcome the silos of our respective workspaces.”
