Crowdsourcing without a crowd : Reliable online species identification using Bayesian models to minimize crowd size

Acknowledgment This research is supported by an award made by the RCUK Digital Economy program to the University of Aberdeen’s dot.rural Digital Economy Hub (ref. EP/G066051/1).

Human Search for a Target on a Textured Background is Consistent with a Stochastic Model

This research was supported by the James S. McDonnell Foundation (ARH). Early version was supported by EPSRC grants EP/F02553X/1 and EP/D059364/1.

Digital Innovation Through Partnership Between Nature Conservation Organisations and Academia : A Qualitative Impact Assessment

We would like to thank all interviewees for sharing their experiences of working with academics, and the guest editor and three anonymous reviewers for valuable comments on earlier versions of the work. The research in this paper is supported by the RCUK dot.rural Digital economy Research Hub, University of Aberdeen (Grant reference: EP/G066051/1).

Interrogating Capabilities of IoT Devices

This research is supported by the UK Research Councils’ Digital Economy IT as a Utility Network+ (EP/K003569/1) and the dot.rural Digital Economy Hub (EP/G066051/1).

Digital Innovation Through Partnership Between Nature Conservation Organisations and Academia : A Qualitative Impact Assessment

We would like to thank all interviewees for sharing their experiences of working with academics, and the guest editor and three anonymous reviewers for valuable comments on earlier versions of the work. The research in this paper is supported by the RCUK dot.rural Digital economy Research Hub, University of Aberdeen (Grant reference: EP/G066051/1).

Interrogating Capabilities of IoT Devices

This research is supported by the UK Research Councils’ Digital Economy IT as a Utility Network+ (EP/K003569/1) and the dot.rural Digital Economy Hub (EP/G066051/1).

QUAL : A Provenance-Aware Quality Model

The research described here is supported by the award made by the RCUK Digital Economy program to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.

SC-PROV: A Provenance Vocabulary for Social Computation

The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.

Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data : A case study of reintroduced red kites

Acknowledgements We thank Andrew Spink (Noldus Information Technology) and the Blogging Birds team members Peter Kindness and Abdul Adeniyi for their valuable contributions to this paper. John Fryxell, Chris Thaxter and Arjun Amar provided valuable comments on an earlier version. The study was part of the Digital Conservation project of dot.rural, the University of Aberdeen’s Digital Economy Research Hub, funded by RCUK (grant reference EP/G066051/1).

High-resolution spatial modelling of greenhouse gas emissions from land-use change to energy crops in the United Kingdom

Funded by Energy Technologies Institute EPSRC-Supergen. Grant Number: EP/M013200/1

The role of automated feedback in training and retaining biological recorders for citizen science

© 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Acknowledgments The authors thank H. H. Nguyen for his early development work on the BeeWatch interface; E. O'Mahony, I. Pearce, and R. Comont for identifying numerous photographed bumblebees; B. Darvill, D. Ewing, and G. Perkins for enabling our partnership with the Bumblebee Conservation Trust; and S. Blake for his investments in developing the NLG feedback. The study was part of the Digital Conservation project of dot.rural, the University of Aberdeen's Digital Economy Research Hub, funded by RCUK (grant reference EP/G066051/1).

Smooth particle hydrodynamics study of surface defect machining for diamond turning of silicon

Acknowledgments The authors would like to thank EPSRC (EP/ K018345/1) and Royal Society-NSFC International Exchange Scheme for providing financial support to this research.

Tilted excitation implies odd periodic resonances

This work was supported by the Brazilian agencies FAPESP and CNPq. MSB also acknowledges the Engineering and Physical Sciences Research Council grant Ref. EP/I032606/1. GID thanks Felipe A. C. Pereira for fruitful discussions.

Pressure radiation from a perforated duct exit region

Acknowledgements The authors are grateful to the following bodies that provided financial support for the project: (i) China Scholarship Council, (ii) National Natural Science Foundation of China (Grant no. U1334201) and (iii) UK Engineering and Physical Sciences Research Council (Grant no. EP/G069441/1).