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.

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.

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.