The need for sound ecological science has escalated alongside the rise of the information age and “big data” across all sectors of society. Big data generally refer to massive volumes of data not readily handled by the usual data tools and practices and present unprecedented opportunities for advancing science and informing resource management through data‐intensive approaches. The era of big data need not be propelled only by “big science” – the term used to describe large‐scale efforts that have had mixed success in the individual‐driven culture of ecology. Collectively, ecologists already have big data to bolster the scientific effort – a large volume of distributed, high‐value information – but many simply fail to contribute. We encourage ecologists to join the larger scientific community in global initiatives to address major scientific and societal problems by bringing their distributed data to the table and harnessing its collective power. The scientists who contribute such information will be at the forefront of socially relevant science – but will they be ecologists?

When scientists from two or more disciplines work together on related problems, they often face what we call 'science friction'. As science becomes more data-driven, collaborative, and interdisciplinary, demand increases for interoperability among data, tools, and services. Metadata -usually viewed simply as 'data about data', describing objects such as books, journal articles, or datasets -serve key roles in interoperability. Yet we find that metadata may be a source of friction between scientific collaborators, impeding data sharing. We propose an alternative view of metadata, focusing on its role in an ephemeral process of scientific communication, rather than as an enduring outcome or product. We report examples of highly useful, yet ad hoc, incomplete, loosely structured, and mutable, descriptions of data found in our ethnographic studies of several large projects in the environmental sciences. Based on this (5) evidence, we argue that while metadata products can be powerful resources, usually they must be supplemented with metadata processes. Metadata-as-process suggests the very large role of the ad hoc, the incomplete, and the unfinished in everyday scientific work.

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