Biodiversity research needs a digital library on multi-source data. Biodiversity digital library, based on the virtual community, has similar features as digital libraries in data types, storage requirement and sharing methods. On the other hand, it has distinct features in terms of data mining and application. Based on an investigation of related digital library projects and cooperation with the Biodiversity Heritage Library and Internet Archive, we summarize the types of literature data in some kinds of digital libraries and briefly introduce Dublin Core and TaxonX standards which will be applied in the construction of the biodiversity digital library. Then, the present architecture of the biodiversity digital library, composed of data aggregation models and data processes, conversion and translation models and service models, is proposed in order to integrate multi-source data, construct the virtual community and provide specific data service to external web sites. Part of the implemented information system is demonstrated, and then some problems like copyright, OCR (optical character recognition) and the extension of massive data sets are discussed.
Considering analyses of the development of biodiversity informatics techniques, the introduction of related international biodiversity e-Science infrastructure and previous similar achievements, we suggest and describe a biodiversity e-Science infrastructure of China based on SOA and ISO 19119 Standards. Moreover, the major steps in construction of the biodiversity e-Science infrastructure are also introduced, including strong coordination and organization, data standardization and extension, data storage and computation, ontology and semantic web development, thematic analysis and modeling, and service standardization. This architecture can provide references for future construction of biodiversity e-Science infrastructure in China.
Herein, we have proposed and implemented a predictive species distribution system (PSDS) based on GIS (Geographic Information Systems) and using multiple models, according to the situation in the field of species habitat modeling. The new system (PSDS 2.0) was developed from PSDS1.0, originally initiated by our research group. We introduced three models into PSDS 2.0, including a mahalanobis distance model (MD), an environmental envelope plus limiting factor model (EELF), and a support vector machine (SVM) model. In this paper, we describe the implementation of the system and introduce the main functions in detail. In order to compare and evaluate results from different algorithms, an iterative cross-validation technique has been implemented in PSDS 2.0, which also facilitates the selection of suitable algorithms for different sample data. A function for flexibly dealing with pseudo-absences has been incorporated into presence-absence models. A GIS interfaces with the software for data preparation and further analysis of the model results. We also present a case study using the Reeve’s pheasant, Syrmaticus reevesii, as a practical application to introduce the entire modeling process. The performance of all model types is compared within this unified system.
Crop germplasm resources are a key component of biodiversity, and can serve as a material basis for crop breeding and agroproduction. For a long time, ununified standards, widely-scattered germplasm storage, and weak information network infrastructure have restricted the sharing and utilization of crop germplasm resources in China. In order to overcome these problems, the concept and architecture of a program called the National Crop Germplasm Resources Infrastructure (NCGRI) were proposed. The NCGRI is a virtual organization which brings together crop germplasm resources from the national long-term genebank, the national duplicate genebank, the national medium-term genebank, the national field genebank, and the national germplasm information center. The principles and methods for establishing a technical standard system were elaborated. Complete with descriptor lists, a data dictionary, and data quality control standards, the group established a technical standard system for 110 crops. A protocol for sample sharing that is driven by information sharing was put forward. The national crop germplasm resources database with 390,000 accessions and the Chinese Crop Germplasm Resources Information Network (http://www.cgris.net/) were established as repositories. Finally five service-modes including routine service, field display services, targeted services, demand for services, and guide services were created.
Biodiversity Informatics is a young and rapidly growing field that brings information science and technologies to bear on the data and information generated by the study of biodiversity and related subjects. Recent years, biodiversity informatics community has made an extraordinary effort to digitize primary biodiversity data, and develop modelling tools, data integration, and county/regional/global biodiversity networks. In doing so, the community is creating an unprecedented global sharing of information and data produced by biodiversity science, and encouraging people to consider, survey and monitor natural biodiversity. Due to success of several international biodiversity informatics projects, such as Species 2000, Global Biodiversity Information Facility, Barcoding of Life and Encyclopedia of Life, digitized information on species inventories, herbarium specimens, multimedia and literature is available through internet. These projects not only make great contributions to sharing digitized biodiversity data, but also in prompting the implementation of important biodiversity information standards, such as Darwin Core, and in the establishment of regional and national biodiversity networks. These efforts will facilitate the future establishment of a strong information infrastructure for data sharing and exchange at a global scale. Besides focusing on browsing and searching digitized data, scientists should also work on building data mining and modeling, such as MAXENT for Ecological Niche Modelling and LifeDesk for taxonomist’s knowledge management. At the same time, the idea of citizen sciences gains popularity showing us the benefit of the public working closely with the scientific community in completing internet-based biodiversity informatics activities. Therefore, biodiversity informatics has broad prospects, and is helping to build strong facilities that will aid in implementing the goals set by Global Plant Conservation Strategy and related international treaties, resolving biodiversity crises and the management of biodiversity resources in global climate change scenarios.
The integration of Taiwan’s biodiversity databases started in 2001, the same year that both the Digital Archives Program (later renamed Taiwan e-Learning and Digital Archives Program; TELDAP) and Biodiversity Action Plan were launched and Taiwan joined the Global Biodiversity Information Facility (GBIF) as an Associate Participant. In 2002, Academia Sinica began the creation of the “Catalog of Life in Taiwan” database (TaiBNET). Taiwan’s node of GBIF, TaiBIF, established in 2004, integrates Taiwan’s biodiversity data and shares it with the global community. Both TaiBNET and TaiBIF have broken through the barrier of Intellectual Property Rights and can collect and integrate data accumulated by TELDAP’s various sub-projects. However, raw data, especially those on ecological distribution, generated by different agencies or non-TELDAP projects are still dispersed due to parochialism. A cross-agency committee was thus established in Academia Sinica in 2008 to formulate policies on data collection and integration, as well as mechanisms to increase public availability of data. Any commissioned project will hereafter include these policy requirements in the contract. The results of TaiBIF’s efforts over the past six years, though not perfect, can provide some information and insights for others to reference or replicate.
Biodiversity Committee, CAS
Botanical Society of China
Institute of Botany, CAS
Institute of Zoology, CAS
Institute of Microbiology, CAS
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