Quality assurance framework for the design, collection and curation of standard data products from a distributed ecology network

1. Ecological data are increasingly collected by networks of collaborators using replicated designs and methods, which can significantly improve the quality and quantity of data throughout the ecological niche and geographic range of species or communities. The coordinated generation and management of data is critical for producing datasets (Standard Data Products) across multiple sites that can be used by different researchers, over extended time periods and for multiple purposes.

2. We describe and use a Quality Assurance framework for the design, collection and production of reproducible Standard Data Products for distributed ecology projects. We identified six critical project elements of a Quality Assurance framework (QA1-6) to produce ecological Standard Data Products with high immediate and future value.

3. We applied the Quality Assurance framework to the Plantpopnet project as a case-study. Plantpopnet is a coordinated distributed system for population macroecology using the model species Plantago lanceolata. We mapped Plantpopnet activities to the Quality Assurance Framework as follows: (QA1) Measurable objectives: research project objectives with data requirements, (QA2) Process control: governance policies, (QA3) Project specific procedures: model organism selection and data collection protocol, (QA4) Supporting production of high quality data: recruitment, retention and engagement of participants, (QA5) Data management: data management plan and reproducible data cleaning workflow, (QA6) Production and management of outputs: Standard Data Products and papers.

4. Explicit use of Quality Assurance, project and data management tools together with standardised ecological methods facilitated the design, collection, maintenance and sustainability of high-quality data products. We provide a Quality Assurance framework together with governance documents, code and data for a reproducible Standard Data Product. This framework supports a distributed funding model which can be sustainably applied to facilitate future research and applications of coordinated distributed ecology projects.