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- Dettki, Holger
(författare)
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A plea for standards in reporting data collected by animal‑borne electronic devices
- 2016
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Ingår i: Animal Biotelemetry. - : Springer Science and Business Media LLC. - 2050-3385. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, there has been significant investment in collaborative e-infrastructures to support biotelemetry research. Whilst these e-infrastructures are rapidly growing in size and sophistication, the current lack of standards for reporting and documenting the data collected by animal-borne telemetry devices is hampering their effectiveness. Here, we demonstrate why the current lack of standards is severely complicating the process for those developing and maintaining biotelemetry-related e-infrastructures, and provide suggestions as to how the current issue may be resolved. We hope this article will stimulate discussion across the community and facilitate the first steps towards the creation and adoption of industry standards for data collected by animal-borne telemetry devices.
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- Dettki, Holger
(författare)
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A standardisation framework for bio-logging data to advance ecological research and conservation
- 2021
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Ingår i: Methods in Ecology and Evolution. - 2041-210X. ; 12, s. 996-1007
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Tidskriftsartikel (refereegranskat)abstract
- Bio-logging data obtained by tagging animals are key to addressing global conservation challenges. However, the many thousands of existing bio-logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms, slowing down ecological research and effective management. A set of universal standards is needed to ensure discoverability, interoperability and effective translation of bio-logging data into research and management recommendations.We propose a standardisation framework adhering to existing data principles (FAIR: Findable, Accessible, Interoperable and Reusable; and TRUST: Transparency, Responsibility, User focus, Sustainability and Technology) and involving the use of simple templates to create a data flow from manufacturers and researchers to compliant repositories, where automated procedures should be in place to prepare data availability into four standardised levels: (a) decoded raw data, (b) curated data, (c) interpolated data and (d) gridded data. Our framework allows for integration of simple tabular arrays (e.g. csv files) and creation of sharable and interoperable network Common Data Form (netCDF) files containing all the needed information for accuracy-of-use, rightful attribution (ensuring data providers keep ownership through the entire process) and data preservation security.We show the standardisation benefits for all stakeholders involved, and illustrate the application of our framework by focusing on marine animals and by providing examples of the workflow across all data levels, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing.Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and inter-governmental assessments (e.g. the World Ocean Assessment), and will provide a starting point for broader efforts to establish interoperable bio-logging data formats across all fields in animal ecology.
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- Dettki, Holger
(författare)
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A Toolbox for Remotely Monitoring Large Carnivores in Sweden. In: The Roles of Remote Sensing in Nature Conservation
- 2017
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Ingår i: The Roles of Remote Sensing in Nature Conservation A Practical Guide and Case Studies. - Cham : Springer International Publishing. - 9783319643304 ; , s. 203-222
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Bokkapitel (refereegranskat)abstract
- Five species of large carnivore are the main focus of interest in Sweden when it comes to the conservation of biological diversity, ecosystem completeness, and the traditional herding of reindeer (Rangifer tarandus) by indigenous Sámi people. Successful work with the wolf (Canis lupus), brown bear (Ursus arctos), lynx (Lynx lynx), wolverine (Gulo gulo) and golden eagle (Aquila chrysaetos) necessitates good knowledge of their numbers, distribution and population dynamics as well as their effects on prey species and the reindeer herding economy. However, large carnivores are relatively few, elusive, wide ranging and secretive, and therefore notoriously hard to observe. Hence, collecting standardized data of sufficient quality and quantity is a challenge for both research and management. In this chapter, we describe how this challenge is being met in Sweden. We define remote sensing as observing and measuring from a distance, and different approaches for remote sensing of carnivores are used in Sweden. These include non-invasive methods such as DNA-sampling and snow tracking, partly invasive methods such as automatic cameras, and highly invasive methods such as tagging with biotelemetry sensors. Attitude surveys are used to monitor public opinions about carnivores and their management. We also present infrastructure solutions (Rovbase, UC-WRAM) for handling the wealth of data that are acquired through remote sensing of carnivores in Sweden.
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- Dettki, Holger
(författare)
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Wildlife tracking data management: a new vision
- 2010
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Ingår i: Philosophical Transactions B: Biological Sciences. - : The Royal Society. - 0962-8436 .- 1471-2970. ; 365, s. 2177-2185
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Tidskriftsartikel (refereegranskat)abstract
- To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.
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