John Deck

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.

Community next steps for making globally unique identifiers work for biocollections data

Abstract Biodiversity data is being digitized and made available online at a rapidly increasing rate but current practices typically do not preserve linkages between these data, which impedes interoperation, provenance tracking, and assembly of larger datasets. For data associated with biocollections, the biodiversity community has long recognized that an essential part of establishing and preserving linkages is to apply globally unique identifiers at the point when data are generated in the field and to persist these identifiers downstream, but this is seldom implemented in practice. There has neither been coalescence towards one single identifier solution (as in some other domains), nor even a set of recommended best practices and standards to support multiple identifier schemes sharing consistent responses. In order to further progress towards a broader community consensus, a group of biocollections and informatics experts assembled in Stockholm in October 2014 to discuss community next steps to overcome current roadblocks. The workshop participants divided into four groups focusing on: identifier practice in current field biocollections; identifier application for legacy biocollections; identifiers as applied to biodiversity data records as they are published and made available in semantically marked-up publications; and cross-cutting identifier solutions that bridge across these domains. The main outcome was consensus on key issues, including recognition of differences between legacy and new biocollections processes, the need for identifier metadata profiles that can report information on identifier persistence missions, and the unambiguous indication of the type of object associated with the identifier. Current identifier characteristics are also summarized, and an overview of available schemes and practices is provided.

A call for an international network of genomic observatories (GOs)

We are entering a new era in genomics–that of large-scale, place-based, highly contextualized genomic research. Here we review this emerging paradigm shift and suggest that sites of utmost scientific importance be expanded into ‘Genomic Observatories’ (GOs). Investment in GOs should focus on the digital characterization of whole ecosystems, from all-taxa biotic inventories to time-series ’omics studies. The foundational layer of biodiversity–genetic variation–would thus be mainstreamed into Earth Observation systems enabling predictive modelling of biodiversity dynamics and resultant impacts on ecosystem services.

The founding charter of the Genomic Observatories Network

The co-authors of this paper hereby state their intention to work together to launch the Genomic Observatories Network (GOs Network) for which this document will serve as its Founding Charter. We define a Genomic Observatory as an ecosystem and/or site subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms.An international group of 64 scientists first published the call for a global network of Genomic Observatories in January 2012. The vision for such a network was expanded in a subsequent paper and developed over a series of meetings in Bremen (Germany), Shenzhen (China), Moorea (French Polynesia), Oxford (UK), Pacific Grove (California, USA), Washington (DC, USA), and London (UK). While this community-building process continues, here we express our mutual intent to establish the GOs Network formally, and to describe our shared vision for its future. The views expressed here are ours alone as individual scientists, and do not necessarily represent those of the institutions with which we are affiliated.

Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

Clarifying Concepts and Terms in Biodiversity Informatics

“If names be not correct, language is not in accordance with the truth of things. If language be not in accordance with the truth of things, affairs cannot be carried on to success.” - Confucius, Analects, Book XIII, Chapter 3, verses 4-7, translated by James Legge Two workshops (hereafter described as “workshops”) were held in 2012, which brought together domain experts from genomic and biodiversity informatics, information modeling and biology, to clarify concepts and terms at the intersection of these domains. These workshops grew out of efforts sponsored by the NSF funded Resource Coordination Network (RCN) project for GSC [1] (RCN4GSC, hosted at UCSD, with John Wooley as PI) to reconcile terms from the Darwin Core (DwC) [2] vocabulary and with those in the MIxS family of checklists (Minimum Information about Any Type of Sequence) [3]. The original RCN4GSC meetings were able to align many terms between DwC and MIxS, finding both common and complementary terms. However, deciding exactly what constitutes the concept of a sample, a specimen, and an occurrence [4] to satisfy the needs of all use cases proved difficult, especially given the wide variety of sampling strategies employed within and between communities. Further, participants in the initial RCN4GSC workshops needed additional guidance on how to relate these entities to processes that act upon them and the environments in which organisms live. These issues provided the motivation for the workshops described below. The two workshops drew largely from experiences of the Basic Formal Ontology (BFO) [5] and were led by Barry Smith, State University of New York at Buffalo. We chose to interact with Smith based on his successful interactions with the GSC in developing the Environment Ontology (EnvO) [6] and also, on the ability of BFO to unite previously disconnected ontologies in the medical domain [7]. The first workshop addressed term definitions in biodiversity informatics, working within the BFO framework, while the second workshop developed a prototype Bio-Collections Ontology, dealing with samples and processes acting on samples. Concurrent with these workshops were two ongoing efforts involving data acquisition, visualization, and analysis that rely on a solid conceptual understanding of samples, specimens, and occurrences. These implementations are included in this report to show practical applications of term clarification. Finally, this report provides a discussion of some of the next steps discussed during the workshops.

The Global Genome Biodiversity Network (GGBN) Data Standard specification

Genomic samples of non-model organisms are becoming increasingly important in a broad range of studies from developmental biology, biodiversity analyses, to conservation. Genomic sample definition, description, quality, voucher information and metadata all need to be digitized and disseminated across scientific communities. This information needs to be concise and consistent in today’s ever-increasing bioinformatic era, for complementary data aggregators to easily map databases to one another. In order to facilitate exchange of information on genomic samples and their derived data, the Global Genome Biodiversity Network (GGBN) Data Standard is intended to provide a platform based on a documented agreement to promote the efficient sharing and usage of genomic sample material and associated specimen information in a consistent way. The new data standard presented here build upon existing standards commonly used within the community extending them with the capability to exchange data on tissue, environmental and DNA sample as well as sequences. The GGBN Data Standard will reveal and democratize the hidden contents of biodiversity biobanks, for the convenience of everyone in the wider biobanking community. Technical tools exist for data providers to easily map their databases to the standard. Database URL: http://terms.tdwg.org/wiki/GGBN_Data_Standard

The trouble with triplets in biodiversity informatics: a data-driven case against current identifier practices.

The biodiversity informatics community has discussed aspirations and approaches for assigning globally unique identifiers (GUIDs) to biocollections for nearly a decade. During that time, and despite misgivings, the de facto standard identifier has become the “Darwin Core Triplet”, which is a concatenation of values for institution code, collection code, and catalog number associated with biocollections material. Our aim is not to rehash the challenging discussions regarding which GUID system in theory best supports the biodiversity informatics use case of discovering and linking digital data across the Internet, but how well we can link those data together at this moment, utilizing the current identifier schemes that have already been deployed. We gathered Darwin Core Triplets from a subset of VertNet records, along with vertebrate records from GenBank and the Barcode of Life Data System, in order to determine how Darwin Core Triplets are deployed “in the wild”. We asked if those triplets follow the recommended structure and whether they provide an easy and unambiguous means to track from specimen records to genetic sequence records. We show that Darwin Core Triplets are often riddled with semantic and syntactic errors when deployed and curated in practice, despite specifications about how to construct them. Our results strongly suggest that Darwin Core Triplets that have not been carefully curated are not currently serving a useful role for relinking data. We briefly consider needed next steps to overcome current limitations.

Meeting report: advancing practical applications of biodiversity ontologies

We describe the outcomes of three recent workshops aimed at advancing development of the Biological Collections Ontology (BCO), the Population and Community Ontology (PCO), and tools to annotate data using those and other ontologies. The first workshop gathered use cases to help grow the PCO, agreed upon a format for modeling challenging concepts such as ecological niche, and developed ontology design patterns for defining collections of organisms and population-level phenotypes. The second focused on mapping datasets to ontology terms and converting them to Resource Description Framework (RDF), using the BCO. To follow-up, a BCO hackathon was held concurrently with the 16th Genomics Standards Consortium Meeting, during which we converted additional datasets to RDF, developed a Material Sample Core for the Global Biodiversity Information Framework, created a Web Ontology Language (OWL) file for importing Darwin Core classes and properties into BCO, and developed a workflow for converting biodiversity data among formats.

The Genomic Observatories Metadatabase (GeOMe): a new repository for field and sampling event metadata associated with genetic samples

The Genomic Observatories Metadatabase (GeOMe, http://www.geome-db.org/) is an open access repository for geographic and ecological metadata associated with biosamples and genetic data. Whereas public databases have served as vital repositories for nucleotide sequences, they do not accession all the metadata required for ecological or evolutionary analyses. GeOMe fills this need, providing a user-friendly, web-based interface for both data contributors and data recipients. The interface allows data contributors to create a customized yet standard-compliant spreadsheet that captures the temporal and geospatial context of each biosample. These metadata are then validated and permanently linked to archived genetic data stored in the National Center for Biotechnology Information’s (NCBI’s) Sequence Read Archive (SRA) via unique persistent identifiers. By linking ecologically and evolutionarily relevant metadata with publicly archived sequence data in a structured manner, GeOMe sets a gold standard for data management in biodiversity science.