Biodiversity data supports research on human infectious diseases: Global trends, challenges, and opportunities.

The unprecedented generation of large volumes of biodiversity data is consistently contributing to a wide range of disciplines, including disease ecology. Emerging infectious diseases are usually zoonoses caused by multi-host pathogens. Therefore, their understanding may require the access to biodiversity data related to the ecology and the occurrence of the species involved. Nevertheless, despite several data-mobilization initiatives, the usage of biodiversity data for research into disease dynamics has not yet been fully leveraged. To explore current contribution, trends, and to identify limitations, we characterized biodiversity data usage in scientific publications related to human health, contrasting patterns of studies citing the Global Biodiversity Information Facility (GBIF) with those obtaining data from other sources. We found that the studies mainly obtained data from scientific literature and other not aggregated or standardized sources. Most of the studies explored pathogen species and, particularly those with GBIF-mediated data, tended to explore and reuse data of multiple species (>2). Data sources varied according to the taxa and epidemiological roles of the species involved. Biodiversity data repositories were mainly used for species related to hosts, reservoirs, and vectors, and barely used as a source of pathogens data, which was usually obtained from human and animal-health related institutions. While both GBIF- and not GBIF-mediated data studies explored similar diseases and topics, they presented discipline biases and different analytical approaches. Research on emerging infectious diseases may require the access to geographical and ecological data of multiple species. The One Health challenge requires interdisciplinary collaboration and data sharing, which is facilitated by aggregated repositories and platforms. The contribution of biodiversity data to understand infectious disease dynamics should be acknowledged, strengthened, and promoted.

Publishing data to support the fight against human vector-borne diseases.

Vector-borne diseases are responsible for more than 17% of human cases of infectious diseases. In most situations, effective control of debilitating and deadly vector-bone diseases (VBDs), such as malaria, dengue, chikungunya, yellow fever, Zika and Chagas requires up-to-date, robust and comprehensive information on the presence, diversity, ecology, bionomics and geographic spread of the organisms that carry and transmit the infectious agents. Huge gaps exist in the information related to these vectors, creating an essential need for campaigns to mobilise and share data. The publication of data papers is an effective tool for overcoming this challenge. These peer-reviewed articles provide scholarly credit for researchers whose vital work of assembling and publishing well-described, properly-formatted datasets often fails to receive appropriate recognition. To address this, GigaScience's sister journal GigaByte partnered with the Global Biodiversity Information Facility (GBIF) to publish a series of data papers, with support from the Special Programme for Research and Training in Tropical Diseases (TDR), hosted by the World Health Organisation (WHO). Here we outline the initial results of this targeted approach to sharing data and describe its importance for controlling VBDs and improving public health.

Country Compendium of the Global Register of Introduced and Invasive Species.

The Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS) is a collation of data across 196 individual country checklists of alien species, along with a designation of those species with evidence of impact at a country level. The Compendium provides a baseline for monitoring the distribution and invasion status of all major taxonomic groups, and can be used for the purpose of global analyses of introduced (alien, non-native, exotic) and invasive species (invasive alien species), including regional, single and multi-species taxon assessments and comparisons. It enables exploration of gaps and inferred absences of species across countries, and also provides one means for updating individual GRIIS Checklists. The Country Compendium is, for example, instrumental, along with data on first records of introduction, for assessing and reporting on invasive alien species targets, including for the Convention on Biological Diversity and Sustainable Development Goals. The GRIIS Country Compendium provides a baseline and mechanism for tracking the spread of introduced and invasive alien species across countries globally. Design Type(s) Data integration objective ● Observation design Measurement Type(s) Alien species occurrence ● Evidence of impact invasive alien species assessment objective Technology Type(s) Agent expert ● Data collation Factor Type(s) Geographic location ● Origin / provenance ● Habitat Sample Characteristics - Organism Animalia ● Bacteria ● Chromista ● Fungi ● Plantae ● Protista (Protozoa) ● Viruses Sample Characteristics - Location Global countries.

A mid-term analysis of progress toward international biodiversity targets.

In 2010, the international community, under the auspices of the Convention on Biological Diversity, agreed on 20 biodiversity-related "Aichi Targets" to be achieved within a decade. We provide a comprehensive mid-term assessment of progress toward these global targets using 55 indicator data sets. We projected indicator trends to 2020 using an adaptive statistical framework that incorporated the specific properties of individual time series. On current trajectories, results suggest that despite accelerating policy and management responses to the biodiversity crisis, the impacts of these efforts are unlikely to be reflected in improved trends in the state of biodiversity by 2020. We highlight areas of societal endeavor requiring additional efforts to achieve the Aichi Targets, and provide a baseline against which to assess future progress.

A specialist's audit of aggregated occurrence records: An 'aggregator's' perspective.

A recent ZooKeys' paper (Mesibov, 2013: http://www.pensoft.net/journal_home_page.php?journal_id=1&page=article&SESID=df7bcb35b02603283dcb83ee0e0af0c9&type=show&article_id=5111) has highlighted data quality issues in aggregated data sets, but did not provide a realistic way to address these issues. This paper provides an aggregator's perspective including ways that the whole community can help to address data quality issues. The establishment of GBIF and national nodes (national aggregators) such as the Atlas of Living Australia (ALA) have integrated and exposed a huge diversity of biological observations along with many associated issues. Much of the admirable work by Mesibov (2013) was enabled by having the data exposed. Data quality, one of the highest priorities for GBIF, the national nodes and other aggregators, depends on both automatic methods and community experts to detect and correct data issues. Not all issues can however be automatically detected or corrected, so community assistance is needed to help improve the quality of exposed biological data. We do need to improve the infrastructure and associated processes to more easily identify data issues and document all changes to ensure a full record is permanently and publicly available.