‘openDS’ – A New Standard for Digital Specimens and Other Natural Science Digital Object Types

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Abstract

With projected lifespans of many decades, infrastructure initiatives such as Europe’s Distributed System of Scientiﬁc Collections (DiSSCo), USA’s Integrated Digitized Biocollections (iDigBio), National Specimen Information Infrastructure (NSII) of China and Australia’s digitisation of national research collections (NRCA Digital) aim at transforming today’s slow, ineﬃcient and limited practices of working with natural science collections. The need to borrow specimens (plants, animals, fossils or rocks) or physically visit collections, and absence of linkages to other relevant information represent signiﬁcant impediments to answering today’s scientiﬁc and societal questions. A logical extension of the Internet, Digital Object Architecture (Kahn and Wilensky 2006) oﬀers a way of grouping, managing and processing fragments of information relating to a natural science specimen. A ‘digital specimen’ acts as a surrogate in cyberspace for a speciﬁc physical specimen, identifying its actual location and authoritatively saying something about its collection event (who, when, where) and taxonomy, as well as providing links to high-resolution images. A digital specimen exposes supplementary information about related literature, traits, tissue samples and DNA sequences, chemical analyses, environmental information, etc. stored elsewhere than in the natural science collection itself. By presenting digital specimens as a new layer between data infrastructure of natural science collections and user applications for processing and interacting with information about specimens and collections, it’s possible to seamlessly organise global access spanning multiple collection-holding institutions and sources. Virtual collections of digital specimens with unique identiﬁers oﬀer possibilities for wider, more ﬂexible, and ‘FAIR’ (Findable, Accessible, Interoperable, Reusable) access for varied research and policy uses: recognising curatorial work, annotating with latest taxonomic treatments, understanding variations, working with DNA sequences or chemical analyses, supporting regulatory processes for health, food, security, sustainability and environmental change, inventions/products critical to the bio-economy, and educational uses. Adopting a digital specimen approach is expected to lead to faster insights for lower cost on many fronts. We propose that realising this vision requires a new TDWG standard. OpenDS is a speciﬁcation of digital specimen and other object types essential to mass digitisation of natural science collections and their digital use. For ﬁve principal digital object types corresponding to major categories of collections and specimens’ information, OpenDS deﬁnes structure and content, and behaviours that can act upon them: Digital specimen: Representing a digitised physical specimen, contains information about a single specimen with links to related supplementary information; Storage container: Representing groups of specimens stored within a single container, such as insect tray, drawer or sample jar; Collection: Information about characteristics of a collection; Organisation: Information about the legal-entity owning the specimen and collection to which it belongs; and, Interpretation: Assertion(s) made on or about the specimen such as determination of species and comments. Secondary classes gather presentation/preservation characteristics (e.g., herbarium sheets, pinned insects, specimens in glass jars, etc.), the general classiﬁcation of a specimen (i.e., plant, animal, fossil, rock, etc.) and history of actions on the object (provenance). Equivalencing concepts in ABCD 3.0 and EFG extension for geo-sciences, OpenDS is also an ontology extending OBO Foundry’s Biological Collection Ontology (BCO) (Walls et al. 2014) from bco:MaterialSample, which has preferred label dwc:specimen from Darwin Core, thus linking it also with that standard. OpenDS object content can be serialized to speciﬁc formats/representations (e.g. JSON) for diﬀerent exchange and processing purposes.

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Is Open Access

Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies

Ramona L. Walls, John Deck, Robert Guralnick … (2014)

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.