A knowledge environment for the biodiversity and ecological sciences (original) (raw)

Creating and providing data management services for the biological and ecological sciences: science environment for ecological knowledge

2005

The Science Environment for Ecological Knowledge (SEEK) [1] is an information technology project designed to address the many challenges associated with data accessibility and integration of large-scale biocomplexity data in the ecological sciences. The SEEK project is creating cyberinfrastructure encompassing three integrated systems: EcoGrid, a Semantic Mediation System (SMS) and an Analysis and Modeling System (AMS). SEEK enables ecologists to efficiently capture, organize and search for data and analytical processes (i.e., scientific workflows) from their desktop in a user friendly interface --ultimately providing access to global data and analytical resources typically out of reach for many ecologists. The prototype application is ecological niche modeling.

Semantic Management of Data from Biodiversity and Ecosystem Studies: Toward an Integrated Workflow from Collection to Publication. Application to Plankton Data from Lake Geneva

2021

Biodiversity is a key player in ecosystem characteristics and dynamics. Acting as a driver, it also results from ecosystem functioning. Understanding this complex interplay between biological and physical components is one of the main current challenges in the context of land use changes and climate warming. The acquisition of knowledge on biodiversity requires multidisciplinary approaches and mobilises numerous research teams. Data are collected or computed in large quantity but are most often poorly standardised and therefore heterogeneous. In this context the development of semantic interoperability is a major challenge for the sharing and reuse of these data. This objective is implemented within the framework of the AnaEE (Analysis and Experimentation on Ecosystems) Research Infrastructure dedicated to experimentation on ecosystems and biodiversity. A distributed Information System (IS) is developed, based on the semantic interoperability of its components using common vocabular...

The Open Biodiversity Knowledge Management (eco-)System: Tools and Services for Extraction, Mobilization, Handling and Re-use of Data from the Published Literature

Biodiversity Information Science and Standards

The Open Biodiversity Knowledge Management System (OBKMS) is an end-to-end, eXtensible Markup Language (XML)- and Linked Open Data (LOD)-based ecosystem of tools and services that encompasses the entire process of authoring, submission, review, publication, dissemination, and archiving of biodiversity literature, as well as the text mining of published biodiversity literature (Fig. 1). These capabilities lead to the creation of interoperable, computable, and reusable biodiversity data with provenance linking facts to publications. OBKMS is the result of a joint endeavour by Plazi and Pensoft lasting many years. The system was developed with the support of several biodiversity informatics projects - initially (Virtual Biodiversity Research and Access Network for Taxonomy) ViBRANT, and then followed by pro-iBiosphere, European Biodiversity Observation Network (EU BON), and Biosystematics, informatics and genomics of the big 4 insect groups (BIG4). The system includes the following key...

BiGe-Onto: An ontology-based system for managing biodiversity and biogeography data1

Applied Ontology, 2020

Great progress to digitize the world's available Biodiversity and Biogeography data have been made recently, but managing data from many different providers and research domains still remains a challenge. A review of the current landscape of metadata standards and ontologies in Biodiversity sciences suggests that existing standards, such as the Darwin Core terminology, are inadequate for describing Biodiversity data in a semantically meaningful and computationally useful way. As a contribution to fill this gap, we present an ontology-based system, called BiGe-Onto, designed to manage data together from Biodiversity and Biogeography. As data sources, we use two internationally recognized repositories: the Global Biodiversity Information Facility (GBIF) and the Ocean Biogeographic Information System (OBIS). BiGe-Onto system is composed of (i) BiGe-Onto Architecture (ii) a conceptual model called BiGe-Onto specified in OntoUML, (iii) an operational version of BiGe-Onto encoded in OWL 2, and (iv) an integrated dataset for its exploitation through a SPARQL endpoint. We will show use cases that allow researchers to answer questions that manage information from both domains.

Semantic Bridges for Biodiversity Sciences

The Semantic Web - ISWC 2015, 2015

Understanding the impact of climate change and humans on biodiversity requires the retrieval and integration of heterogeneous data sets for the generation of models that provide insights not possible with a single model. Scientists invest a significant amount of time collecting and manually preprocessing data for the generation of such models. The Earth Life and Semantic Web (ELSEWeb) project aims to create a semantic-based, open-source cyberinfrastructure to automate the ingestion of data by models. This paper describes the ontologies at the backbone of ELSEWeb that provide semantic bridges between environmental data sources and species distribution models.

Model Framework for Development of Biodiversity Information Systems

Journal of Physics: Conference Series, 2019

The aim of the study was to design a framework for developing bioinformatics resource information systems using the Model-View-Controller (MVC) design pattern. Research contributions generate a framework as an approach model for the development of Biodiversity Information Systems which aims to improve computational capabilities and management of biodiversity data resources for the use of public information clusters. This product combines component capabilities (View Controller Model (MCV), Object Relational Mapping (ORM) and ICBN Nomenclature Taxonomy) with reusable resources. The results of the study have produced a special prototype in the form of a Framework in the Development of Bioinformatics resource information systems that can be accessed online in the site: http://borneodiversity.org/index.

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

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.

Advancing ecological research with ontologies

2008

Ecology is inherently cross-disciplinary, drawing together many types of information to address questions about the natural world. Finding and integrating relevant data to assist in these analyses is crucial, but is difficult owing to ambiguous terminology and the lack of sufficient information about datasets. Ontologies provide a formal mechanism for defining terms and their relationships, and can improve the location, interpretation and integration of data based on its inherent meaning. Ontologies have assisted other disciplines (e.g. molecular biology) in unifying and enriching descriptions of data, and ecology can benefit from similar approaches. We review ontology efforts in ecology, and describe how these can benefit research by enhancing the location and interpretation of relevant data for confronting crucial ecological questions.

Open Biodiversity Knowledge Management System, PhD Project

Background This is a Research Presentation paper, one of the novel article formats developed for the Research Ideas and Outcomes (RIO) journal and aimed at representing brief research outcomes. In this paper we publish and discuss our webinar presentation for the Integrated Digitized Biocollections (iDigBio) audience on two novel publishing workflows for biodiversity data: (1) automatic import of specimen records into manuscripts, and (2) automatic generation of data paper manuscripts from Ecological Metadata Language (EML) metadata. New information Information on occurrences of species and information on the specimens that are evidence for these occurrences (specimen records) is stored in different biodiversity databases. These databases expose the information via public REST API's. We focused on the Global Biodiversity Information Facility (GBIF), Barcode of Life Data Systems (BOLD), iDigBio, ‡ § ‡

Biodiversity knowledge organization system: Proposed architecture

2012

Summary This document provides a proposed architecture for the new Knowledge Organization System (KOS) for biodiversity information resources to be hosted by GBIF. The proposed KOS architecture includes the following key components:“Vocabulary of Terms”(1),“Term Browser”(2),“Extensions and Code lists for the Darwin Core Archives”(3), domain Ontologies (4), and a “Resources Repository”(5). This document presents the overall architecture and how these conceptual building blocks are linked together.