Cynthia Sims Parr

Task taxonomy for graph visualization

Our goal is to define a list of tasks for graph visualization that has enough detail and specificity to be useful to: 1) designers who want to improve their system and 2) to evaluators who want to compare graph visualization systems. In this paper, we suggest a list of tasks we believe are commonly encountered while analyzing graph data. We define graph specific objects and demonstrate how all complex tasks could be seen as a series of low-level tasks performed on those objects. We believe that our taxonomy, associated with benchmark datasets and specific tasks, would help evaluators generalize results collected through a series of controlled experiments.

Dynamic changes in motivation in collaborative citizen-science projects

Online citizen science projects engage volunteers in collecting, analyzing, and curating scientific data. Existing projects have demonstrated the value of using volunteers to collect data, but few projects have reached the full collaborative potential of scientists and volunteers. Understanding the shared and unique motivations of these two groups can help designers establish the technical and social infrastructures needed to promote effective partnerships. We present findings from a study of the motivational factors affecting participation in ecological citizen science projects. We show that volunteers are motivated by a complex framework of factors that dynamically change throughout their cycle of work on scientific projects; this motivational framework is strongly affected by personal interests as well as external factors such as attribution and acknowledgment. Identifying the pivotal points of motivational shift and addressing them in the design of citizen-science systems will facilitate improved collaboration between scientists and volunteers.

A Large-Scale, Higher-Level, Molecular Phylogenetic Study of the Insect Order Lepidoptera (Moths and Butterflies)

Background Higher-level relationships within the Lepidoptera, and particularly within the species-rich subclade Ditrysia, are generally not well understood, although recent studies have yielded progress. We present the most comprehensive molecular analysis of lepidopteran phylogeny to date, focusing on relationships among superfamilies. Methodology / Principal Findings 483 taxa spanning 115 of 124 families were sampled for 19 protein-coding nuclear genes, from which maximum likelihood tree estimates and bootstrap percentages were obtained using GARLI. Assessment of heuristic search effectiveness showed that better trees and higher bootstrap percentages probably remain to be discovered even after 1000 or more search replicates, but further search proved impractical even with grid computing. Other analyses explored the effects of sampling nonsynonymous change only versus partitioned and unpartitioned total nucleotide change; deletion of rogue taxa; and compositional heterogeneity. Relationships among the non-ditrysian lineages previously inferred from morphology were largely confirmed, plus some new ones, with strong support. Robust support was also found for divergences among non-apoditrysian lineages of Ditrysia, but only rarely so within Apoditrysia. Paraphyly for Tineoidea is strongly supported by analysis of nonsynonymous-only signal; conflicting, strong support for tineoid monophyly when synonymous signal was added back is shown to result from compositional heterogeneity. Conclusions / Significance Support for among-superfamily relationships outside the Apoditrysia is now generally strong. Comparable support is mostly lacking within Apoditrysia, but dramatically increased bootstrap percentages for some nodes after rogue taxon removal, and concordance with other evidence, strongly suggest that our picture of apoditrysian phylogeny is approximately correct. This study highlights the challenge of finding optimal topologies when analyzing hundreds of taxa. It also shows that some nodes get strong support only when analysis is restricted to nonsynonymous change, while total change is necessary for strong support of others. Thus, multiple types of analyses will be necessary to fully resolve lepidopteran phylogeny.

RDF123: From Spreadsheets to RDF

We describe RDF123, a highly flexible open-source tool for translating spreadsheet data to RDF. Existing spreadsheet-to-rdf tools typically map only to star-shaped RDF graphs, i.e. each spreadsheet row is an instance, with each column representing a property. RDF123, on the other hand, allows users to define mappings to arbitrary graphs, thus allowing much richer spreadsheet semantics to be expressed. Further, each row in the spreadsheet can be mapped with a fairly different RDF scheme. Two interfaces are available. The first is a graphical application that allows users to create their mapping in an intuitive manner. The second is a Web service that takes as input a URL to a Google spreadsheet or CSV file and an RDF123 map, and provides RDF as output.

Evolutionary informatics: unifying knowledge about the diversity of life

The accelerating growth of data and knowledge in evolutionary biology is indisputable. Despite this rapid progress, information remains scattered, poorly documented and in formats that impede discovery and integration. A grand challenge is the creation of a linked system of all evolutionary data, information and knowledge organized around Darwins ever-growing Tree of Life. Such a system, accommodating topological disagreement where necessary, would consolidate taxon names, phenotypic and geographical distributional data across clades, and serve as an integrated community resource. The field of evolutionary informatics, reviewed here for the first time, has matured into a robust discipline that is developing the conceptual, infrastructure and community frameworks for meeting this grand challenge.

Can Deliberately Incomplete Gene Sample Augmentation Improve a Phylogeny Estimate for the Advanced Moths and Butterflies (Hexapoda: Lepidoptera)?

Abstract This paper addresses the question of whether one can economically improve the robustness of a molecular phylogeny estimate by increasing gene sampling in only a subset of taxa, without having the analysis invalidated by artifacts arising from large blocks of missing data. Our case study stems from an ongoing effort to resolve poorly understood deeper relationships in the large clade Ditrysia ( > 150,000 species) of the insect order Lepidoptera (butterflies and moths). Seeking to remedy the overall weak support for deeper divergences in an initial study based on five nuclear genes (6.6 kb) in 123 exemplars, we nearly tripled the total gene sample (to 26 genes, 18.4 kb) but only in a third (41) of the taxa. The resulting partially augmented data matrix (45% intentionally missing data) consistently increased bootstrap support for groupings previously identified in the five-gene (nearly) complete matrix, while introducing no contradictory groupings of the kind that missing data have been predicted to produce. Our results add to growing evidence that data sets differing substantially in gene and taxon sampling can often be safely and profitably combined. The strongest overall support for nodes above the family level came from including all nucleotide changes, while partitioning sites into sets undergoing mostly nonsynonymous versus mostly synonymous change. In contrast, support for the deepest node for which any persuasive molecular evidence has yet emerged (78–85% bootstrap) was weak or nonexistent unless synonymous change was entirely excluded, a result plausibly attributed to compositional heterogeneity. This node (Gelechioidea + Apoditrysia), tentatively proposed by previous authors on the basis of four morphological synapomorphies, is the first major subset of ditrysian superfamilies to receive strong statistical support in any phylogenetic study. A “more-genes-only” data set (41 taxa×26 genes) also gave strong signal for a second deep grouping (Macrolepidoptera) that was obscured, but not strongly contradicted, in more taxon-rich analyses.

The Encyclopedia of Life v2: Providing Global Access to Knowledge About Life on Earth

Abstract The Encyclopedia of Life (EOL, http://eol.org) aims to provide unprecedented global access to a broad range of information about life on Earth. It currently contains 3.5 million distinct pages for taxa and provides content for 1.3 million of those pages. The content is primarily contributed by EOL content partners (providers) that have a more limited geographic, taxonomic or topical scope. EOL aggregates these data and automatically integrates them based on associated scientific names and other classification information. EOL also provides interfaces for curation and direct content addition. All materials in EOL are either in the public domain or licensed under a Creative Commons license. In addition to the web interface, EOL is also accessible through an Application Programming Interface. In this paper, we review recent developments added for Version 2 of the web site and subsequent releases through Version 2.2, which have made EOL more engaging, personal, accessible and internationalizable. We outline the core features and technical architecture of the system. We summarize milestones achieved so far by EOL to present results of the current system implementation and establish benchmarks upon which to judge future improvements. We have shown that it is possible to successfully integrate large amounts of descriptive biodiversity data from diverse sources into a robust, standards-based, dynamic, and scalable infrastructure. Increasing global participation and the emergence of EOL-powered applications demonstrate that EOL is becoming a significant resource for anyone interested in biological diversity.

Supporting content curation communities: The case of the Encyclopedia of Life

This article explores the opportunities and challenges of creating and sustaining large-scale “content curation communities” through an in-depth case study of the Encyclopedia of Life (EOL). Content curation communities are large-scale crowdsourcing endeavors that aim to curate existing content into a single repository, making these communities different from content creation communities such as Wikipedia. In this article, we define content curation communities and provide examples of this increasingly important genre. We then follow by presenting EOL, a compelling example of a content curation community, and describe a case study of EOL based on analysis of interviews, online discussions, and survey data. Our findings are characterized into two broad categories: information integration and social integration. Information integration challenges at EOL include the need to (a) accommodate and validate multiple sources and (b) integrate traditional peer reviewed sources with user-generated, nonpeer-reviewed content. Social integration challenges at EOL include the need to (a) establish the credibility of open-access resources within the scientific community and (b) facilitate collaboration between experts and novices. After identifying the challenges, we discuss the potential strategies EOL and other content curation communities can use to address them, and provide technical, content, and social design recommendations for overcoming them.

Visualizations for taxonomic and phylogenetic trees

MOTIVATION Despite substantial efforts to develop and populate the back-ends of biological databases, front-ends to these systems often rely on taxonomic expertise. This research applies techniques from human-computer interaction research to the biodiversity domain. RESULTS We developed an interactive node-link tool, TaxonTree, illustrating the value of a carefully designed interaction model, animation, and integrated searching and browsing towards retrieval of biological names and other information. Users tested the tool using a new, large integrated dataset of animal names with phylogenetic-based and classification-based tree structures. These techniques also translated well for a tool, DoubleTree, to allow comparison of trees using coupled interaction. Our approaches will be useful not only for biological data but as general portal interfaces.

Phylogeny of magpies (genus Pica) inferred from mtDNA data

We investigated the phylogenetic relationships of species and subspecies of the cosmopolitan genus Pica using 813 bp of the mitochondrial genome (including portions of 16s rDNA, tRNA-Leu, and ND1). The phylogenetic relationships within the genus Pica revealed in our molecular analyses can be summarized as follows: (1). the Korean magpie (Pica pica sericea) appears basal within the genus Pica; (2). the European magpie (Pica pica pica) shows a close relationship to the Kamchatkan magpie (Pica pica camtschatica); (3). two North American species (Pica hudsonia and Pica nuttalli) shows a sister-group relationship; (4). most importantly, the European+Kamchatkan clade appears more closely related to the North American clade than to Korean magpies. Based on these results and genetic distance data, it is possible that members of an ancestral magpie lineage in East Asia initially moved north to form Kamchatkan magpies and then crossed the Bering land bridge to found North American taxa. At a later date, a group might have split off from Kamchatkan magpies and migrated west to form the Eurasian subspecies. The divergence between the two North American taxa appears to have happened no later than the divergence of Eurasian subspecies and both processes appear to have been relatively rapid. Rather than the formation of P. hudsonia by re-colonization from an Asian magpie ancestor, as suggested by, our data suggest a shared ancestry between P. hudsonia and P. nuttalli. Based on the above findings, including phylogenetic placement of P. hudsonia and P. nuttalli as nested within the larger Pica pica clade, and the lack of evidence suggesting reproductive isolation within the genus Pica, we believe that the current classification may be inaccurate. A more conservative classification would recognize one monophyletic species (i.e., P. pica) and treat P. nuttalli and P. hudsonia as subspecies (i.e., P. p. nuttalli and P. p. hudsonia). More extensive studies on the population genetics and biogeography of magpies should be conducted to better inform any taxonomic decisions.