A comprehensive record of research data provenance is essential for the successful curation, management, and reuse of data over time. However, creating such detailed metadata can be onerous, and there are few structured methods for doing so. In this case study of data curation in support of geobiology research conducted at Yellowstone National Park, we describe a method of “Research Process Modeling” for documenting noncomputational data provenance in a structured yet flexible way. The method combines systems analysis techniques to model research activities, the World Wide Web Consortium Provenance (PROV) ontology to illustrate relationships between data products, and simple inventory methods to account for research processes and data products. It also supports collaborative data curation between information professionals and researchers, and is therefore a significant step toward producing more useable and interpretable research data. We demonstrate how this method describes data provenance more robustly than “flat” metadata alone and fills a critical gap in the documentation of provenance for field‐based and noncomputational workflows. We discuss potential applications of this approach to other research domains.

We report on an in-progress project to design a new field instrument used to link data collection and preservation practices across the gaps separating groups of oceanographic scientists engaged in interdisciplinary collaborations. Oceanographic cruises provide an important means for collecting data as an input for specific scientific investigations and for longer term efforts to make a wide range of environmental field data available for future scientific investigators. For both of these tasks, there is the need to perform the invisible work of identifying and resolving potential gaps and consistency issues in the data in order to make the data usable. The event logger system was designed to address these issues by associating every measurement on two organization's scientific cruises with a latitude, longitude, and time stamp. It is the finding of this ethnographic analysis that the event logger system has been successful to the extent that the design process has been able to incorporate a diverse range of voices into an open and collaborative activity.

This paper addresses the collaborative development of information infrastructure for supporting data-rich scientific collaboration. Studying infrastructure development empirically not only in terms of spatial issues but also, and equally importantly, temporal ones, we illustrate how the long-term matters. Our case is about the collaborative development of a metadata standard for an ecological research domain. It is a complex example where standards are recognized as one element of infrastructure and standard-making efforts include integration of semantic work and software tools development. With a focus on the temporal scales of short-term and long-term, we analyze the practices and views of the main parties involved in the development of the standard. Our contributions are three-fold: 1) extension of the notion of infrastructure to more explicitly include the temporal dimension; 2) identification of two distinct temporal orientations in information infrastructure development work, namely ‘project time’ and ‘infrastructure time’, and 3) association of related development orientations, particularly ‘continuing design’ as a development orientation that recognizes ‘infrastructure time’. We conclude by highlighting the need to enrich understandings of temporality in CSCW, particularly towards longer time scales and more diversified temporal hybrids in collaborative infrastructure development. This work draws attention to the manifold ramifications that ‘infrastructure time’, as an example of more extended temporal scales, suggests for CSCW and e-Research infrastructures.