We cordially invite you to join us at the Data Stewardship Co nversations to discuss your feedback on the Data Curation Guide and decide next steps.
\nThe Data Curation Guide was developed as part of our current thematic focus to serve as an interactive map for researchers at t he University of Basel to provide them with easy access to general and sub ject-specific information on data curation throughout the research data li fecycle.
\nAt the event\, we would like to discuss in particular the following questions:
\nFinally\, we would like to discuss with you the b est way to deploy the tool at the university.
\nYour feedback is esp ecially important to us so that we can benefit from your knowledge of the conditions and needs in your field before the roll out of the tool.
\n< p>To test the tool and provide feedback\, please see the RDM Wiki for more information: https:/ /wiki.biozentrum.unibas.ch/x/XaboJw\nWe look forward to hearing your insights and having a fruitful discussion. It is greatly appreciated .
\nAs usual\, we will end the event with an informal chat over drin ks and snacks.
\nData stewards and other members of the university's RDM Network will be invited to this event by email. Other people who are interested in attending the event are asked to contact the coordinators of the Data Stewardship Program (researchdata@unibas.ch).
DTEND;TZID=Europe/Zurich:20261027T153000 END:VEVENT BEGIN:VEVENT UID:news239@researchdata.unibas.ch DTSTAMP;TZID=Europe/Zurich:20260902T143646 DTSTART;TZID=Europe/Zurich:20261201T140000 SUMMARY:Agentic AI in Research: Concepts\, Workflows\, and Critical Use DESCRIPTION:Agentic artificial intelligence (AI) shows great potential for automating data processing in research contexts and is developing quickly. \\r\\nUnlike standard chatbots\, which respond to single prompts\, agentic AI systems can plan tasks\, use tools\, retrieve information\, organize d ata\, and carry out multi-step workflows with varying degrees of autonomy. \\r\\nIn terms of research data management (RDM)\, agentic AI systems can perform tasks such as renaming and organizing files\, completing metadata\ , identifying gaps and inconsistencies in datasets\, converting formats\, and drafting documentation\, rather than having these tasks done manually. \\r\\nThis introductory workshop is designed for data stewards\, network m embers\, and researchers who wish to learn how agentic AI can support rese arch projects\, RDM and data curation. The workshop will explain the pract ical meaning of “agentic”\, where these systems may be useful in resea rch\, and the risks they introduce.\\r\\nThe session will include a live d emonstration of agentic AI\, followed by the opportunity for hands-on expe rimentation in a sandbox environment. Participants will learn how to form ulate tasks\, evaluate outputs\, document AI-assisted processes\, and dete rmine when not to use agentic AI.\\r\\nBy the end of the session\, partici pants will be able to:\\r\\nidentify suitable use cases for agentic AI in research projectsdistinguish between helpful automation and unreliable del egationdesign simple workflows with agentic AIassess security risks in res earch projects when using agentic AI.\\r\\nThe workshop concludes with a d iscussion of how agentic AI and other AI tools can be used effectively and securely for research projects at the university and the steps needed to achieve this.\\r\\nLecturer\\r\\nDr. Olga Serbaeva (Open Science\, Univers ity Library\, University of Basel)\\r\\nCourse Language: English\\r\\nData stewards and other members of the university's RDM Network will be invite d to this course by email. Other people who are interested in attending th e course are asked to contact the coordinators of the Data Stewardship Pro gram (researchdata@unibas.ch [mailto:researchdata@unibas.ch]). X-ALT-DESC:Agentic artificial intelligence (AI) shows great potential fo r automating data processing in research contexts and is developing quickl y.
\nUnlike standard chatbots\, which respond to single prompts\, ag entic AI systems can plan tasks\, use tools\, retrieve information\, organ ize data\, and carry out multi-step workflows with varying degrees of auto nomy.
\nIn terms of research data management (RDM)\, agentic AI syst ems can perform tasks such as renaming and organizing files\, completing m etadata\, identifying gaps and inconsistencies in datasets\, converting fo rmats\, and drafting documentation\, rather than having these tasks done m anually.
\nThis introductory workshop is designed for data stewards\ , network members\, and researchers who wish to learn how agentic AI can s upport research projects\, RDM and data curation. The workshop will explai n the practical meaning of “agentic”\, where these systems may be usef ul in research\, and the risks they introduce.
\nThe session will in clude a live demonstration of agentic AI\, followed by the opportunity for hands-on experimentation in a sandbox environment. Participants will lear n \;how to formulate tasks\, evaluate outputs\, document AI-assisted p rocesses\, and determine when not to use agentic AI.
\nBy the end of the session\, participants will be able to:
\nThe workshop concludes with a discussion of how agentic AI an d other AI tools can be used effectively and securely for research project s at the university and the steps needed to achieve this.
\nLecturer
\nCourse Language: English
\nData stewards and other members of the university's RDM Network will be invited to this course by email. Other people who are interested in atten ding the course are asked to contact the coordinators of the Data Stewards hip Program (researchdata@unibas.ch).
DTEND;TZID=Europe/Zurich:20261201T170000 END:VEVENT END:VCALENDAR