| 1. |
- Kissling, W. Daniel, et al.
(författare)
-
Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale
- 2018
-
Ingår i: Biological Reviews. - : Wiley. - 1464-7931 .- 1469-185X. ; 93:1, s. 600-625
-
Tidskriftsartikel (refereegranskat)abstract
- © 2017 Cambridge Philosophical Society. Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a 'Big Data' approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence-absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals.
|
|
| 2. |
- Koureas, Dimitrios, et al.
(författare)
-
Unifying European Biodiversity Informatics (Bio Unify)
- 2016
-
Ingår i: Research Ideas and Outcomes. - : Pensoft Publishers. - 2367-7163. ; 2:e7787, s. 1-23
-
Tidskriftsartikel (refereegranskat)abstract
- In order to preserve the variety of life on Earth, we must understand it better. Biodiversity research is at a pivotal point with research projects generating data at an ever increasing rate. Structuring, aggregating, linking and processing these data in a meaningful way is a major challenge. The systematic application of information management and engineering technologies in the study of biodiversity (biodiversity informatics) help transform data to knowledge. However, concerted action is required to be taken by existing e-infrastructures to develop and adopt common standards, provisions for interoperability and avoid overlapping in functionality. This would result in the unification of the currently fragmented landscape that restricts European biodiversity research from reaching its full potential. The overarching goal of this COST Action is to coordinate existing research and capacity building efforts, through a bottom-up trans-disciplinary approach, by unifying biodiversity informatics communities across Europe in order to support the long-term vision of modelling biodiversity on earth. BioUnify will: 1. specify technical requirements, evaluate and improve models for efficient data and workflow storage, sharing and re-use, within and between different biodiversity communities; 2. mobilise taxonomic, ecological, genomic and biomonitoring data generated and curated by natural history collections, research networks and remote sensing sources in Europe; 3. leverage results of ongoing biodiversity informatics projects by identifying and developing functional synergies on individual, group and project level; 4. raise technical awareness and transfer skills between biodiversity researchers and information technologists; 5. formulate a viable roadmap for achieving the long-term goals for European biodiversity informatics, which ensures alignment with global activities and translates into efficient biodiversity policy.
|
|
| 3. |
- Ronquist, Fredrik, 1962-, et al.
(författare)
-
EU-BON Deliverable 1.3. Systems for mobilizing and managing collection-based data (specimen + DNA-data) fully integrated
- 2016
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Introduction. A large portion of the biodiversity data in natural history collections is still not available digitally. Increasingly, innovative high-throughput methods are being applied to digitize this backlog in bulk, generating large amounts of data. In parallel, natural history museums are becoming increasingly involved in the generation of large amounts of molecular biodiversity data using new massively parallel sequencing platforms. Against this backdrop, the goal of EU BON Task 1.4 has been to support data mobilization efforts targeting collection-based and molecular data, mainly through the development and integration of innovative open-source tools and services.Progress towards objectives. The activities have involved work within the context of three major projects: i) DINA, an open-source, modular, web-based collection management system for natural history specimen data. ii) JACQ an open-access system for botanical (herbarium) data. iii) PlutoF, a web platform for working with traditional and molecular biodiversity research data. The task has also involved work on a number of other EU BON partner systems and services, as well as integration across internal EU BON and external biodiversity informatics resources. Finally, these systems have been used for targeted data mobilization efforts.Achievements and current status. Within DINA, the focus has been on supporting the engineering of sophisticated biodiversity information systems through the exploration of tools supporting distributed development and a modular plug-and-play design based on services-oriented architectures. This has involved the testing and adoption of tools like Apiary for the design of Application Programming Interfaces (APIs) and Docker for systems integration and deployment tasks. A Python library for data migration to DINA was also developed and tested. Within JACQ, a number of tools were developed to facilitate deployment and data migration to the system, and the AnnoSys tool for annotation of data has been integrated. Within PlutoF, EU BON efforts focused on the development of a citizen-science module and improved functionality for the mobilization of collection (living) specimen data. A number of innovative tools were developed by Pensoft to help mobilize biodiversity data published in the scientific literature, including semantic mark-up of species conservation papers, direct import of data from a range of biodiversity platforms into manuscripts, and a mechanism for providing stable links from publications to global biodiversity repositories. Plazi implemented an automated workflow mining published scientific papers for taxonomic data, currently mobilizing 25 % of all published new names as they become available. GlueCad developed apps allowing citizen scientists reporting spontaneous observations or systematic inventory data to select target taxa and preferred data mobilization platform. IBSAS and UCPH have focused on national data mobilization efforts targeting Slovakia and Denmark, respectively.Future developments. Although the development is clearly towards increased integration of biodiversity informatics tools into larger and more sophisticated systems, it is clear that there is no one size that fits all. Nevertheless, the increasingly widespread adoption of community standards, open-source development practises and service-oriented architectures are pushing the capability of current systems forward and facilitating tighter integration across systems. This trend is supported by the appearance of sophisticated tools enabling the design and deployment of complex modular systems. The adoption of the Docker approach is one example of how the biodiversity informatics community may benefit from this.
|
|
