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We present a new system for online publication, sharing and analysis of images and metadata, named SuAVE (Survey Analysis via Visual Exploration), and demonstrate its applications to coral reef surveys and related data collections. SuAVE supports easy access to thousands of images organized in a single browser screen, exploration and comparison of subsets based on faceted search over image metadata, analysis of distributions, drilling down to individual cases, and identifying site-related tagged datasets. The system enables collaborative analysis of collections, as users can annotate patterns and individual images, then share these annotations with others in a way that supports continued analysis from any annotation point.
SuAVE has been applied in several domains, from analysis of questionnaire surveys in sociology to exploration of digital collections in geo- and biosciences and humanities. It has been particularly useful in enabling researchers to formulate and address science questions through integrated analysis of large multi-modal multi-variable collections, as it combines visual, statistical and cartographic views of data, and links out to additional information sources. Such capabilities are typically needed in the analysis of coral bleaching, as investigation of coral reef ecosystems requires integration of diverse multi-scale surveys including remote sensing, high resolution 3D reef mapping, underwater video transects, assessments of physiological responses to stressors, and genomic studies. We demonstrate SuAVE using surveys from the Moorea LTER and Kaneohe Bay, Hawaii. The project web site and a gallery of sample surveys are at


Zaslavsky, I., UCSD, USA,

Meier, O. W., University of Hawaii, USA,

Li, S., UCSD, USA,

Gates, R. D., University of Hawaii, USA,

Gastil-Buhl, G., UCSB, USA,


Oral presentation

Session #:024
Date: 03/02/2017
Time: 10:45
Location: 306 B

Presentation is given by student: No