Angiosperm phylogeny: 17 genes, 640 taxa.

PREMISE OF THE STUDY: Recent analyses employing up to five genes have provided numerous insights into angiosperm phylogeny, but many relationships have remained unresolved or poorly supported. In the hope of improving our understanding of angiosperm phylogeny, we expanded sampling of taxa and genes beyond previous analyses. METHODS: We conducted two primary analyses based on 640 species representing 330 families. The first included 25260 aligned base pairs (bp) from 17 genes (representing all three plant genomes, i.e., nucleus, plastid, and mitochondrion). The second included 19846 aligned bp from 13 genes (representing only the nucleus and plastid). KEY RESULTS: Many important questions of deep-level relationships in the nonmonocot angiosperms have now been resolved with strong support. Amborellaceae, Nymphaeales, and Austrobaileyales are successive sisters to the remaining angiosperms (Mesangiospermae), which are resolved into Chloranthales + Magnoliidae as sister to Monocotyledoneae + [Ceratophyllaceae + Eudicotyledoneae]. Eudicotyledoneae contains a basal grade subtending Gunneridae. Within Gunneridae, Gunnerales are sister to the remainder (Pentapetalae), which comprises (1) Superrosidae, consisting of Rosidae (including Vitaceae) and Saxifragales; and (2) Superasteridae, comprising Berberidopsidales, Santalales, Caryophyllales, Asteridae, and, based on this study, Dilleniaceae (although other recent analyses disagree with this placement). Within the major subclades of Pentapetalae, most deep-level relationships are resolved with strong support. CONCLUSIONS: Our analyses confirm that with large amounts of sequence data, most deep-level relationships within the angiosperms can be resolved. We anticipate that this well-resolved angiosperm tree will be of broad utility for many areas of biology, including physiology, ecology, paleobiology, and genomics.

Location, location, location: utilizing pipelines and services to more effectively georeference the world's biodiversity data.

BACKGROUND: Increasing the quantity and quality of data is a key goal of biodiversity informatics, leading to increased fitness for use in scientific research and beyond. This goal is impeded by a legacy of geographic locality descriptions associated with biodiversity records that are often heterogeneous and not in a map-ready format. The biodiversity informatics community has developed best practices and tools that provide the means to do retrospective georeferencing (e.g., the BioGeomancer toolkit), a process that converts heterogeneous descriptions into geographic coordinates and a measurement of spatial uncertainty. Even with these methods and tools, data publishers are faced with the immensely time-consuming task of vetting georeferenced localities. Furthermore, it is likely that overlap in georeferencing effort is occurring across data publishers. Solutions are needed that help publishers more effectively georeference their records, verify their quality, and eliminate the duplication of effort across publishers. RESULTS: We have developed a tool called BioGeoBIF, which incorporates the high throughput and standardized georeferencing methods of BioGeomancer into a beginning-to-end workflow. Custodians who publish their data to the Global Biodiversity Information Facility (GBIF) can use this system to improve the quantity and quality of their georeferences. BioGeoBIF harvests records directly from the publishers' access points, georeferences the records using the BioGeomancer web-service, and makes results available to data managers for inclusion at the source. Using a web-based, password-protected, group management system for each data publisher, we leave data ownership, management, and vetting responsibilities with the managers and collaborators of each data set. We also minimize the georeferencing task, by combining and storing unique textual localities from all registered data access points, and dynamically linking that information to the password protected record information for each publisher. CONCLUSION: We have developed one of the first examples of services that can help create higher quality data for publishers mediated through the Global Biodiversity Information Facility and its data portal. This service is one step towards solving many problems of data quality in the growing field of biodiversity informatics. We envision future improvements to our service that include faster results returns and inclusion of more georeferencing engines.

Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

Mass digitization of scientific collections: New opportunities to transform the use of biological specimens and underwrite biodiversity science.

New information technologies have enabled the scientific collections community and its stakeholders to adapt, adopt, and leverage novel approaches for a nearly 300 years old scientific discipline. Now, few can credibly question the transformational impact of technology on efforts to digitize scientific collections, as IT now reaches into almost every nook and cranny of society. Five to ten years ago this was not the case. Digitization is an activity that museums and academic institutions increasingly recognize, though many still do not embrace, as a means to boost the impact of collections to research and society through improved access. The acquisition and use of scientific collections is a global endeavor, and digitization enhances their value by improved access to core biodiversity information, increases use, relevance and potential downstream value, for example, in the management of natural resources, policy development, food security, and planetary and human health. This paper examines new opportunities to design and implement infrastructure that will support not just mass digitization efforts, but also a broad range of research on biological diversity and physical sciences in order to make scientific collections increasingly relevant to societal needs and interest.

TOLKIN--Tree of Life Knowledge and Information Network: filling a gap for collaborative research in biological systematics.

The development of biological informatics infrastructure capable of supporting growing data management and analysis environments is an increasing need within the systematics biology community. Although significant progress has been made in recent years on developing new algorithms and tools for analyzing and visualizing large phylogenetic data and trees, implementation of these resources is often carried out by bioinformatics experts, using one-off scripts. Therefore, a gap exists in providing data management support for a large set of non-technical users. The TOLKIN project (Tree of Life Knowledge and Information Network) addresses this need by supporting capabilities to manage, integrate, and provide public access to molecular, morphological, and biocollections data and research outcomes through a collaborative, web application. This data management framework allows aggregation and import of sequences, underlying documentation about their source, including vouchers, tissues, and DNA extraction. It combines features of LIMS and workflow environments by supporting management at the level of individual observations, sequences, and specimens, as well as assembly and versioning of data sets used in phylogenetic inference. As a web application, the system provides multi-user support that obviates current practices of sharing data sets as files or spreadsheets via email.