Problem
Research questions and friction points this paper is trying to address.
credit attribution
biocuration
academic assessment
APICURON: a reactive infrastructure for credit attribution across distributed research data ecosystems
🤖 AI Summary
为解决生物数据管理中贡献未被充分认可的问题，APICURON平台通过实时记录和转换策展事件为可验证的工作单元，提供了一种信用归属机制。
📝 Abstract
Data-driven biology relies on structured knowledge generated by expert biocurators, yet this work remains largely unrecognized in traditional academic assessments. To bridge this gap, we present the updated APICURON platform, a credit-attribution infrastructure that formally acknowledges these scientific contributions. Rather than relying on delayed batch reporting, the system captures curation events as they happen and transforms them into verifiable units of work. This design allows independent resources to define and update their own recognition models while preserving the historical record of each contribution. For researchers, APICURON highlights recent activity alongside lifetime achievements and connects verified activities to persistent academic profiles via ORCID. APICURON has been successfully integrated across biological knowledgebases and data resources, demonstrating its application to diverse workflows. Extending beyond biodata resources, it also supports recognition of non-traditional research artefacts, including training materials and research software, without imposing a rigid definition of contribution.
Innovation
Methods, ideas, or system contributions that make the work stand out.
real-time curation event capture
verifiable units of work
independent recognition models
non-traditional research artefacts
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