This invitation-only workshop brought together members of the academic, publishing, and funder communities interested in exploring alternative contributorship and attribution models. Bibliographic conventions for representation of authorship lag behind the semantic capabilities of the web and tend to obfuscate the contributions of those involved in collaborative research and writing endeavors. As a result, publication credit is often misunderstood, and often misapportioned by traditional impact measures.
There is growing interest among researchers, funding agencies, academic institutions, editors, and publishers in increasing the transparency of research contributions, and in more granular tracking of attribution and associated credit. Many publishers now require contribution disclosures upon article submission - some in structured form, some in free-text form - at the same time that funders are developing more scientifically rigorous ways to track the outputs and impact of their research investments.
Our objectives as a group were to explore the pros and cons of alternative approaches, and to converge on a roadmap toward the creation of contributorship and attribution models and technologies that have the potential to:
- Facilitate authorship/contributorship disclosure processes and policies
- Identify good practices for tracking authorship in portions and versions of work
- Minimize authorship disputes
- Enable appropriate credit for contributions in multi-authored works – across all aspects of the research being reported (including data curation, statistical analysis, etc.)
- Improve automated tracking of funding outcomes and impact
- Support new forms of social and research networking
- Further developments in data management and nanopublication
- Inform the “science of science”, e.g. studies of productivity over a career trajectory
- Enable new metrics of credit and attribution