Contextualization of topics - browsing through terms, authors, journals and cluster allocations

This paper builds on an innovative Information Retrieval tool, Ariadne. The tool has been developed as an interactive network visualization and browsing tool for large-scale bibliographic databases. It basically allows to gain insights into a topic by contextualizing a search query (Koopman et al., 2015). In this paper, we apply the Ariadne tool to a far smaller dataset of 111,616 documents in astronomy and astrophysics. Labeled as the Berlin dataset, this data have been used by several research teams to apply and later compare different clustering algorithms. The quest for this team effort is how to delineate topics. This paper contributes to this challenge in two different ways. First, we produce one of the different cluster solution and second, we use Ariadne (the method behind it, and the interface - called LittleAriadne) to display cluster solutions of the different group members. By providing a tool that allows the visual inspection of the similarity of article clusters produced by different algorithms, we present a complementary approach to other possible means of comparison. More particular, we discuss how we can - with LittleAriadne - browse through the network of topical terms, authors, journals and cluster solutions in the Berlin dataset and compare cluster solutions as well as see their context.Comment: proceedings of the ISSI 2015 conference (accepted

Coordinating visualizations of polysemous action: Values added for grounding proportion

We contribute to research on visualization as an epistemic learning tool by inquiring into the didactical potential of having students visualize one phenomenon in accord with two different partial meanings of the same concept. 22 Grade 4-6 students participated in a design study that investigated the emergence of proportional-equivalence notions from mediated perceptuomotor schemas. Working as individuals or pairs in tutorial clinical interviews, students solved non-symbolic interaction problems that utilized remote-sensing technology. Next, they used symbolic artifacts interpolated into the problem space as semiotic means to objectify in mathematical register a variety of both additive and multiplicative solution strategies. Finally, they reflected on tensions between these competing visualizations of the space. Micro-ethnographic analyses of episodes from three paradigmatic case studies suggest that students reconciled semiotic conflicts by generating heuristic logico-mathematical inferences that integrated competing meanings into cohesive conceptual networks. These inferences hinged on revisualizing additive elements multiplicatively. Implications are drawn for rethinking didactical design for proportions. © 2013 FIZ Karlsruhe

CacophonyViz: Visualisation of Birdsong Derived Ecological Health Indicators

The purpose of this work was to create an easy to interpret visualisation of a simple index that represents the quantity and quality of bird life in New Zealand. The index was calculated from an algorithm that assigned various weights to each species of bird. This work is important as it forms a part of the ongoing work by the Cacophony Project which aims to eradicate pests that currently destroy New Zealand native birds and their habitat. The map will be used to promote the Cacophony project to a wide public audience and encourage their participation by giving relevant feedback on the effects of intervention such as planting and trapping in their communities. The Design Science methodology guided this work through the creation of a series of prototypes that through their evaluation built on lessons learnt at each stage resulting in a final artifact that successfully displayed the index at various locations across a map of New Zealand. It is concluded that the artifact is ready and suitable for deployment once the availability of real data from the automatic analysis of audio recordings from multiple locations becomes available

Effects of labeling and consumer health trends on preferred ground beef color characteristics, fat content, and palatability in simulated retail display

Nutritional concerns and attempts to limit fat in the diet over the past decades have impacted the protein market, decreasing red meat consumption as well as prompting the advent of lean and extra lean ground beef. Such lean blends of ground beef may suffer in palatability, however, resulting in less satisfied consumers turning to other protein sources. While consumers are demanding lean ground beef, fatter blends may be more palatable. This study seeks to bridge the gap between perceived health and palatability by evaluating preferred fat content and instrumental color characteristics between labeled and unlabeled packages of ground beef in simulated retail display and comparing this data to preferred palatability characteristics in taste sampling. Participants were asked to identify the relative importance of characteristics commonly used in purchasing ground beef (color, label, fat content, company, and price) and select a preferred package of ground beef from labeled and unlabeled sections consisting of 4%, 10%, 20%, and 27% fat content. Instrumental color data (CIE L*, a*, b*, hue, and chroma) and their main drivers (oxymyoglobin proportion) were also collected. Participants then completed a blind taste sampling of ground beef with variable fat contents as previously described and were asked to evaluate samples for juiciness, bind, beef flavor, off flavor, and overall impression. Data were evaluated through the Mixed Model procedure of SAS, version 9.4. Color, fat, and price were found to be significantly more important (P \u3c 0.05) than label, which was significantly more important than company for package preference. No trend towards fatter or leaner blends was found between labeled and unlabeled selections, with 62.64% of participants selecting identical packages between the two sections. The 20% fat treatment was the most frequently selected product in both labeled and unlabeled sections, however the two leaner blends combined garnered more preferred selections than the two fatter blends (56.67% vs. 43.33%, respectively). Instrumental color data showed significant trends towards a lighter product and increasing L* value with increasing fat content as well as decreasing oxymyoglobin proportion with increasing fat content. No significant differences (P\u3e0.05) were found between the blends for any trait in sensory taste evaluation. These results suggest that while consumers have specific preferences when purchasing ground beef that can be replicated without a label using visual inspection alone, they are less discerning between cooked ground beef of different fat contents. This may explain the continued demand for lean ground beef, as consumers in this study found no significant differences in palatability between ground beef differing in fat content from 4% to 27%. Continued research comparing preferred fat content of ground beef in retail display with preferred fat content for palatability is encouraged to expand upon the findings of this study

Firewatch: Use of Sattelite Imagery by Remote\ud Communities in Northern Australia for Fire Risk\ud Communications.

This paper presents the contextual background and early findings from a new research project funded by the Australian Research Council titled Using community engagement and enhanced visual information to promote FireWatch satellite communications as a support for collaborative decision-making. FireWatch (provided by Landgate in Western Australia) is an internet-based public information service based on near real time satellite data showing timely information relevant to bushfire safety within Australia. However, it has been developed in a highly technical environment and is currently used chiefly by\ud experts. This project aims to redesign FireWatch for ordinary users and to engage a remote community in Northern Australia in this process, leading to improved decision making surrounding bushfire risk