Understanding continental- to global-scale ecological patterns requires developing skills in ecoinformatics approaches and deploying them systematically. Building the multi-faceted datasets required to address questions of such scope is uniquely complex for a variety of reasons. Data resolution typically represents a variety of temporal and spatial domains that need to be synchronized. Some data may be sourced directly from individuals who may have different cultural backgrounds, expectations, and needs with respect to collaboration and attribution. Engagement with these data contributors is necessary to retain traceability, and their knowledge of local conditions can be valuable for interpreting outliers. Thus, challenges exist not only in terms of the database compilation, but also with respect to integrating data contributors into an overall project structure and process for which the scientific questions may already be defined and developed. Various best practices have been proposed for different components (e.g. data sharing policies), but overall ecoinformatics remains complicated due to the large variety of idiosyncrasies encountered in this type of collaborative project. We expand on the technosocial aspects of ecoinformatics, as well as providing perspectives from data contributors who were surveyed for their feedback after a large collaborative project to learn more about how aspects of the project and process were perceived by them and what they valued.
Results/Conclusions
A full incorporation of technosocial aspects of ecoinformatics is necessary to achieve a fully successful multi-faceted project. Analyses of such a disparate set of data can gain substantially when the data contributors, who collectively represent the diverse set of systems, are engaged, ultimately leading to stronger results and interpretations. Inclusive, flexible collaborations that provide mechanisms for attribution and engagement build a cohesive network of people that can pursue longer-term research in productive pathways. Developing project policies early on facilitates trust and community-building. Regular communication throughout the project was important, as was the nature and means of information communicated. Our experiences, as well as the perspectives from data contributors, illustrate the value of developing the social network, an under-appreciated aspect of ecoinformatics. Thus, we encourage researchers to think about building datasets in terms of developing both the data and the community of contributors.