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UID:pretalx-sips2026-dc-7KLYDF@pretalx.com
DTSTART;TZID=EST:20260608T093000
DTEND;TZID=EST:20260608T110000
DESCRIPTION:In the 2025 In-person SIPS\, we introduced the concept of "Radi
 cal Transparency" (RT)\, a practice consisting of making public the whole 
 process of developing a research process\, instead of just its outcomes.\n
 To carry out research in this manner\, we may leverage existing technologi
 es (e.g.\, version control systems).\n\nHowever\, there are still many unk
 nowns yet to be uncovered.\nIn this hackathon\, we will focus on trying to
  make progress towards the following objectives:\n\n-   To define the scop
 e and constraints of the RT approach.\n\n-   To determine the ability of e
 xisting technologies to meet the requirements of RT.\n\n-   To uncover the
  risks and unintended consequences of RT\, and propose safeguards to mitig
 ate them.\n\nWe will split into groups to draft ideas on these objectives.
 \nAt the end of the session\, we will gather the results\, discuss them\, 
 and decide on the next steps towards a publication.
DTSTAMP:20260524T183855Z
LOCATION:AUDITORIUM
SUMMARY:Towards an academic definition of Radical Transparency in Science -
  Daniel Morillo\, Cristina Rodríguez Prada\, Priya Silverstein
URL:https://pretalx.com/sips2026-dc/talk/7KLYDF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-sips2026-dc-JGXREE@pretalx.com
DTSTART;TZID=EST:20260608T160000
DTEND;TZID=EST:20260608T170000
DESCRIPTION:The movement toward open science is driven by the idea of radic
 al transparency. Frameworks such as the OSF enable researchers to share da
 ta\, materials\, and ideas openly\, fostering collaboration\, efficiency\,
  and reproducibility. At the same time\, the rapid rise of AI presents bot
 h opportunities and challenges for this vision. Open datasets can accelera
 te discovery\, support new forms of analysis\, and power AI-driven tools f
 or scientific progress. However\, these same resources may be used to trai
 n models without researchers’ knowledge or consent\, while preprint repo
 sitories may increasingly host rapidly generated and unevenly vetted work.
 \n\nThese developments prompt an important conversation about the future o
 f open science. How can we preserve openness while addressing emerging ris
 ks? What norms\, infrastructures\, or safeguards can ensure transparency s
 upports responsible research? Should we rethink openness or adapt it to a 
 changing technological landscape? This raises a key question: what is the 
 future of open science in an AI-enabled world?
DTSTAMP:20260524T183855Z
LOCATION:AUDITORIUM
SUMMARY:Keynote Day 1: Open Science and the Impact of AI - Crystal N. Stelt
 enpohl\, Daniel Morillo\, Kailey Lawson
URL:https://pretalx.com/sips2026-dc/talk/JGXREE/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-sips2026-dc-CLGXVT@pretalx.com
DTSTART;TZID=EST:20260609T110000
DTEND;TZID=EST:20260609T123000
DESCRIPTION:Registered Reports were created to improve openness and replica
 bility in research. While they have gained in popularity over the past dec
 ade\, they remain difficult to systematically identify and discover\, hind
 ering meta-science efforts to evaluate them at scale. To address this gap\
 , we are developing a comprehensive living database of published Registere
 d Reports. Since our 2025 hackathon\, initial work focused on building a Z
 otero database\, developing machine learning mechanisms for identifying an
 d collecting Registered Reports\, and defining processing terms/informatio
 n to include in the database. Our hackathon will build directly on this fo
 undation. Participants will collaborate to improve data collection pipelin
 es\, improve tagging and metadata standards\, expand database coverage acr
 oss journals and disciplines\, and address sustainability\, versioning\, a
 nd long-term maintenance. The goal is to develop a robust\, scalable\, com
 munity-driven resource that enables reliable discovery and reuse of Regist
 ered Reports for researchers\, meta-researchers\, and the broader scientif
 ic community.
DTSTAMP:20260524T183855Z
LOCATION:AUDITORIUM
SUMMARY:Making Registered Reports Discoverable: A Collaborative Database In
 itiative - William L. D. Krenzer\, Lillian King\, Erin Buchanan\, Daniel M
 orillo
URL:https://pretalx.com/sips2026-dc/talk/CLGXVT/
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