Part 2: Sensemaking Networks Project Plan - Cosmik Labs

Sensemaking Networks: Project Introduction - Cosmik Labs

Incorporating science social media into the scientific process

Sensemaking Networks: Transforming Social Media into a Sensemaking Layer for Science | Ronen Tamari

Sensemaking Networks is a project aiming to address three interrelated limitations of the current science publishing and communication infrastructure: (1) poor reach and feedback, (2) knowledge fragmentation, and (3) rigid formats. To address these issues, Sensemaking Networks combine two promising trends in science publishing and communication: science social media and semantic nanopublishing. While science social media significantly impacts scientific processes and public engagement, it lacks formal recognition and accessibility. On the other hand, nanopublications offer the benefits of formal scientific publishing and machine-readable knowledge representation. Their integration represents a promising direction that could serve as a transformative sensemaking layer for science, enhancing the collective synthesis, dissemination, and evaluation of research.

Sensemaking Networks Part 3: building partnerships and prototypes - Cosmik Labs

Semantic cross-posters for re-integrating science social media

Sensemaking and Science Publishing | Ronen Tamari

Sensemaking as a new framework for understanding why science publishing/peer review is broken, and how to fix it

Cosmik

Tools and networks for collective sensemaking

SenseNets alpha launch retrospective - Cosmik Labs

Experiments at the bleeding edge scientific publishing

Science Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation

Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue that we need a new program of science communication as collective intelligence—a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be informed by (a) a wider base of aggregated knowledge, (b) contributions from a diverse scientific community, (c) participatory input from stakeholders, and (d) better responsiveness to ongoing changes in the state of knowledge.

Semantic Scholar Academic Graph API | Semantic Scholar

Build projects that accelerate scientific progress with the Semantic Scholar Academic Graph API

Semantic Scholar | AI-Powered Research Tool

Semantic Scholar uses groundbreaking AI and engineering to understand the semantics of scientific literature to help Scholars discover relevant research.

Sensemaking AI | Jigsaw

Sensemaking is a suite of AI-powered tools designed to help public leaders understand public opinion quickly. By combining AI interviewing with automated reporting, we bridge the gap between individual voices and actionable policy insights.