The distributed work of local action: interaction amongst virtually collocated research teams

Existing research on synchronous remote working in CSCW has highlighted the troubles that can arise because actions at one site are (partially) unavailable to remote colleagues. Such ‘local action’ is routinely characterised as a nuisance, a distraction, subordinate and the like. This paper explores interconnections between ‘local action’ and ‘distributed work’ in the case of a research team virtually collocated through ‘MiMeG’. MiMeG is an e-Social Science tool that facilitates ‘distributed data sessions’ in which social scientists are able to remotely collaborate on the real-time analysis of video data. The data are visible and controllable in a shared workspace and participants are additionally connected via audio conferencing. The findings reveal that whilst the (partial) unavailability of local action is at times problematic, it is also used as a resource for coordinating work. The paper considers how local action is interactionally managed in distributed data sessions and concludes by outlining implications of the analysis for the design and study of technologies to support group-to-group collaboration.

Interaction among non-toxic phytoplankton, toxic phytoplankton and zooplankton: inferences from field observations

We explore the mutual dependencies and interactions among different groups of species of the plankton population, based on an analysis of the long-term field observations carried out by our group in the North–West coast of the Bay of Bengal. The plankton community is structured into three groups of species, namely, non-toxic phytoplankton (NTP), toxic phytoplankton (TPP) and zooplankton. To find the pair-wise dependencies among the three groups of plankton, Pearson and partial correlation coefficients are calculated. To explore the simultaneous interaction among all the three groups, a time series analysis is performed. Following an Expectation Maximization (E-M) algorithm, those data points which are missing due to irregularities in sampling are estimated, and with the completed data set a Vector Auto-Regressive (VAR) model is analyzed. The overall analysis demonstrates that toxin-producing phytoplankton play two distinct roles: the inhibition on consumption of toxic substances reduces the abundance of zooplankton, and the toxic materials released by TPP significantly compensate for the competitive disadvantages among phytoplankton species. Our study suggests that the presence of TPP might be a possible cause for the generation of a complex interaction among the large number of phytoplankton and zooplankton species that might be responsible for the prolonged coexistence of the plankton species in a fluctuating biomass.