@inproceedings{21872,
author       = {Beauxis-Aussalet, E. M. A. L. and Arslanova, E. and Hardman, L. and van Ossenbruggen, J. R.},
title        = {A {Case} {Study} {Of} {Trust} {Issues} {In} {Scientific} {Video} {Collections}},
booktitle    = {Proceedings of the Workshop on Multimedia Analysis for Ecological Data (MAED, 2013)},
conferencetitle    = {Workshop on Multimedia Analysis for Ecological Data},
conferencedate     = {2013},
series       = {ACM Digital Library},
pages        = { - },
year         = {2013},
month        = {October},
publisher    = {ACM},
refereed     = {y},
size         = {1p.},
keywords     = {Data Provenance; Video Analysis; Information Design},
group        = {INS2},
scndgroup    = {A&C},
language     = {en},
abstract     = {In-situ video recording of underwater ecosystems is able to provide valuable information for biology research
 and natural resources management, e.g. changes in species abundance. Searching the videos manually, however, requires costly
 human effort. Our video analysis tool supports the key task of counting different species of fish, allowing marine biologists
 to query the video collection without watching the videos. To be suitable for scientific research on changes in species
 abundance, the video data must include data provenance information that reflects the potential biases introduced through
 the video processing.In order to trust the analyses made by the system, we need to provide expert users with sufficient
 information to allow them to interpret these potential biases. We conducted two user studies to design a user interface
 that includes data provenance information. Our qualitative analysis discusses the support for understanding the reliability
 of video analysis, and trusting the results it produces. Our main finding is that disclosing details about the video processing
 and provenance data allows biologists to compare the results with their traditional statistical methods, thus increasing
 their trust in the results.},
url          = {http://dx.doi.org/10.1145/2509896.2509907},
}

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R.},\ntitle = {A {Case} {Study} {Of} {Trust} {Issues} {In} {Scientific} {Video} {Collections}},\nbooktitle = {Proceedings of the Workshop on Multimedia Analysis for Ecological Data (MAED, 2013)},\nconferencetitle = {Workshop on Multimedia Analysis for Ecological Data},\nconferencedate = {2013},\nseries = {ACM Digital Library},\npages = { - },\nyear = {2013},\nmonth = {October},\npublisher = {ACM},\nrefereed = {y},\nsize = {1p.},\nkeywords = {Data Provenance; Video Analysis; Information Design},\ngroup = {INS2},\nscndgroup = {A&C},\nlanguage = {en},\nabstract = {In-situ video recording of underwater ecosystems is able to provide valuable information for biology research\n and natural resources management, e.g. changes in species abundance. Searching the videos manually, however, requires costly\n human effort. Our video analysis tool supports the key task of counting different species of fish, allowing marine biologists\n to query the video collection without watching the videos. 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