B-HIT - A Tool for Harvesting and Indexing Biodiversity Data.

With the rapidly growing number of data publishers, the process of harvesting and indexing information to offer advanced search and discovery becomes a critical bottleneck in globally distributed primary biodiversity data infrastructures. The Global Biodiversity Information Facility (GBIF) implemented a Harvesting and Indexing Toolkit (HIT), which largely automates data harvesting activities for hundreds of collection and observational data providers. The team of the Botanic Garden and Botanical Museum Berlin-Dahlem has extended this well-established system with a range of additional functions, including improved processing of multiple taxon identifications, the ability to represent associations between specimen and observation units, new data quality control and new reporting capabilities. The open source software B-HIT can be freely installed and used for setting up thematic networks serving the demands of particular user groups.

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.

Sharing and re-use of phylogenetic trees (and associated data) to facilitate synthesis.

BACKGROUND: Recently, various evolution-related journals adopted policies to encourage or require archiving of phylogenetic trees and associated data. Such attention to practices that promote sharing of data reflects rapidly improving information technology, and rapidly expanding potential to use this technology to aggregate and link data from previously published research. Nevertheless, little is known about current practices, or best practices, for publishing trees and associated data so as to promote re-use. FINDINGS: Here we summarize results of an ongoing analysis of current practices for archiving phylogenetic trees and associated data, current practices of re-use, and current barriers to re-use. We find that the technical infrastructure is available to support rudimentary archiving, but the frequency of archiving is low. Currently, most phylogenetic knowledge is not easily re-used due to a lack of archiving, lack of awareness of best practices, and lack of community-wide standards for formatting data, naming entities, and annotating data. Most attempts at data re-use seem to end in disappointment. Nevertheless, we find many positive examples of data re-use, particularly those that involve customized species trees generated by grafting to, and pruning from, a much larger tree. CONCLUSIONS: The technologies and practices that facilitate data re-use can catalyze synthetic and integrative research. However, success will require engagement from various stakeholders including individual scientists who produce or consume shareable data, publishers, policy-makers, technology developers and resource-providers. The critical challenges for facilitating re-use of phylogenetic trees and associated data, we suggest, include: a broader commitment to public archiving; more extensive use of globally meaningful identifiers; development of user-friendly technology for annotating, submitting, searching, and retrieving data and their metadata; and development of a minimum reporting standard (MIAPA) indicating which kinds of data and metadata are most important for a re-useable phylogenetic record.