Overview
While open access publishing broadens access to research products, making sense of volumes of new information is increasingly acute. We contend that open access to diverse sources of scientific sensemaking data is essential. We propose Open Science Sensemaking (OSSm)—an interoperable decentralized annotation network enabling researchers to share sensemaking data including annotations, tags, ratings, and behavioral traces.
OSSmOpen Science Sensemakingscientific sensemakingannotation networksopen accessdecentralizedinformation overload
Overview source: Curated paper metadata.
Methods and contributions
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Findings and contributions
- Contends that frictions in scientific sensemaking arise from deficiencies in open access to diverse sensemaking data such as annotations and usage traces.
- Proposes that sensemaking data be included in open science, published under FAIR principles, and embedded in stigmergic annotation networks.
- Argues that FAIR publishing alone is insufficient for sensemaking, which also needs personalizable algorithmic ranking and distribution.
- Observes that sensemaking data are being enclosed, noting that most scientific social bookmarking platforms and reference managers were bought by large publishers.
Methods
- Application of the FAIR data principles to scientific sensemaking data — Works through what Findable, Accessible, Interoperable and Re-usable would mean for annotations, ratings and bookmarks.
- Design of the Open Science Sensemaking Graph with three node types — Specifies a public knowledge graph of actors (SenseMakers), content (URLs) and stigmergic markers, starting from social bookmarking.
- Protocol-based, Murmurations-inspired four-module network architecture — Outlines decentralized storage (e.g. Solid pods, IPFS), indexing/querying, content discovery services and user-facing apps.
- Minimum viable implementation sketch: bookmarking app and rating aggregator — Proposes a reference bookmarking app and a Goodreads-like review/rating aggregator, with collaborative filtering for recommendation.
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Citation
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Tamari, Ronen; Friedman, Daniel. 2023. Open Access science needs Open Science Sensemaking (OSSm). MetaArXiv. DOI: 10.31222/osf.io/9nb3u. URL: https://doi.org/10.31222/osf.io/9nb3u.
Catalog details and resources
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