218
Bear observations that are made by moose hunters in the autumn are not reported
in Rovbase: the Swedish Hunters’ Association has its own routines and methods for
processing and publishing these data. Similarly, Rovbase is not used to store data
from carnivore research. Rovbase data can, however, be used for subsequent research.
The Wireless Remote Animal Monitoring Database
E-Infrastructure
Data from research projects and data from large carnivores that are acquired by
using biotelemetry sensors are not stored in Rovbase. The wealth of data that originates from these sources is handled in another e-infrastructure solution, the Wireless
Remote Animal Monitoring (WRAM), which is an instrument for automatic reception, long-time storage, sharing and analyzing of biotelemetry sensor data from animals (Dettki et al. 2014). It has been developed and operated as the national Swedish
e-infrastructure for biotelemetry data from both research and environmental monitoring programs by the Umeå Center for Wireless Remote Animal Monitoring
(UC-WRAM) at the Swedish University of Agricultural Sciences (SLU) in Umeå.
During the last 40 years, in Sweden and other countries, radio collars, fish tags,
and other telemetry equipment have been used to track fish and wildlife. The equipment used most often relied on traditional radio-telemetry techniques using
‘Very High Frequency’ (VHF) or ‘Ultra High Frequency’ (UHF) radio collars.
These techniques are labor intensive and result in a relatively low numbers of
positions per individual.
In recent years, Global Positioning System (GPS) telemetry collars and automated telemetry equipment have been used to an ever increasing extent. Due to the
automated fashion of data gathering and storage as well as improved battery lifetime of the equipment, the average cost per position is shrinking, resulting in large
datasets being collected per animal studied. Furthermore, additional biosensors can
be integrated in the same collar, measuring, for example, activity of the animal,
body temperature, heart beat or proximity to other sensors.
Due to the huge amount of data available, single research groups are often no
longer able to analyze their data in a timely fashion and they want to share their data
with similar research projects to obtain synergy effects and to open up for new fields
of research. Thus, the WRAM database e-infrastructure has been developed to
enable present and future national and international cooperation by connecting
together WRAMs own database with similar national and international data repositories for biotelemetry data, as e.g. German-US ‘Movebank’, Italian ‘EuroDeer’, or
Norwegian ‘Dyreposisjoner’. The objective is to provide an open database network
which is independent of location or the platform used, and which is used to store,
share, secure and analyze data from wireless remote animal monitoring. The database is accessible to all participating researchers and research groups and features
a web portal used to select, visualize, and access raw data, together with simple
spatial analysis tools and statistical tools. Currently (May 2017) the database
M. Schneider and H. Dettki
Bear observations that are made by moose hunters in the autumn are not reported
in Rovbase: the Swedish Hunters’ Association has its own routines and methods for
processing and publishing these data. Similarly, Rovbase is not used to store data
from carnivore research. Rovbase data can, however, be used for subsequent research.
The Wireless Remote Animal Monitoring Database
E-Infrastructure
Data from research projects and data from large carnivores that are acquired by
using biotelemetry sensors are not stored in Rovbase. The wealth of data that originates from these sources is handled in another e-infrastructure solution, the Wireless
Remote Animal Monitoring (WRAM), which is an instrument for automatic reception, long-time storage, sharing and analyzing of biotelemetry sensor data from animals (Dettki et al. 2014). It has been developed and operated as the national Swedish
e-infrastructure for biotelemetry data from both research and environmental monitoring programs by the Umeå Center for Wireless Remote Animal Monitoring
(UC-WRAM) at the Swedish University of Agricultural Sciences (SLU) in Umeå.
During the last 40 years, in Sweden and other countries, radio collars, fish tags,
and other telemetry equipment have been used to track fish and wildlife. The equipment used most often relied on traditional radio-telemetry techniques using
‘Very High Frequency’ (VHF) or ‘Ultra High Frequency’ (UHF) radio collars.
These techniques are labor intensive and result in a relatively low numbers of
positions per individual.
In recent years, Global Positioning System (GPS) telemetry collars and automated telemetry equipment have been used to an ever increasing extent. Due to the
automated fashion of data gathering and storage as well as improved battery lifetime of the equipment, the average cost per position is shrinking, resulting in large
datasets being collected per animal studied. Furthermore, additional biosensors can
be integrated in the same collar, measuring, for example, activity of the animal,
body temperature, heart beat or proximity to other sensors.
Due to the huge amount of data available, single research groups are often no
longer able to analyze their data in a timely fashion and they want to share their data
with similar research projects to obtain synergy effects and to open up for new fields
of research. Thus, the WRAM database e-infrastructure has been developed to
enable present and future national and international cooperation by connecting
together WRAMs own database with similar national and international data repositories for biotelemetry data, as e.g. German-US ‘Movebank’, Italian ‘EuroDeer’, or
Norwegian ‘Dyreposisjoner’. The objective is to provide an open database network
which is independent of location or the platform used, and which is used to store,
share, secure and analyze data from wireless remote animal monitoring. The database is accessible to all participating researchers and research groups and features
a web portal used to select, visualize, and access raw data, together with simple
spatial analysis tools and statistical tools. Currently (May 2017) the database
M. Schneider and H. Dettki