Giving credit where credit is due: How to make more meaningful connections between people and their roles, work, and impact

Talk and poster at Rocky Bioinformatics Conference, Dec 06, 2019.

Abstract:
Traditional metrics for scholarship typically measure publication records and grants received. However scholarly contributions can extend well beyond these traditional contributions to include things such as algorithm or tool development, biocuration and data analysis. In order to properly give attribution, we need improved mechanisms for recognizing and quantifying these efforts. We aim to develop a computable system to better attribute scholars for the work they do.

The Contributor Role Ontology (CRO) is a structured representation of scholarly roles and contributions. The CRO can be used in combination with research object types to develop infrastructure to understand the scholarly ecosystem, so we can better understand, leverage, and credit a diverse workforce and community.

The Contributor Attribution Model (CAM) provides a simple and tightly scoped data model for representing information about contributions made to research-related artifacts - for example when, why, and how a curator contributed to a gene annotation record. This core model is intended to be used as a modular component of broader data models that support data collection and curation systems, to facilitate reliable and consistent exchange of computable contribution metadata. Additional components of the CAM specification support implementation of the model, data collection, and ontology-based query and analysis of contribution metadata.

Beyond this technical approach, we need to address this challenge from a cultural perspective and we welcome community involvement. We encourage stakeholders from various
communities and roles to get involved, provide perspective, make feature requests, and help shape the future of academic credit and incentives.

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CC BY 4.0