Strategies for successful aggregation and integration of ecological data – lessons from other research domains

Background/Question/Methods

Global environmental change will inevitably lead to changes in the composition of ecological communities and concomitant changes in ecosystem functioning. To address these global challenges, ecologists require not only extensive ecological trait data, but also the ability to integrate these data with many additional datasets, such as species occurrences, community or plot data, and environmental data. As ecologists move towards this world of ‘Big Data,’ the ecological research community, and funding agencies, may choose how to approach these challenges. 

Results/Conclusions

Aggregation and integration of trait data can potentially occur at many scales, ranging from small ad-hoc collaborations with one-time integration, to global, professionally curated databases with fully developed solutions for integration with geospatial data from other domains such as climatology. Here I review data aggregation and integration efforts from various fields outside of ecology, some of which began the move towards ‘Big Data’ long ago. By carefully examining the successes and failures of these related efforts, ecologists can make informed decisions regarding prospects for the success of our own aggregation and integration efforts, and perhaps avoid potential pitfalls.