Amsterdam Actors/Stakeholders and End-users (biologists, ecologists, field researchers) their roles and Data analysts, data archive managers, e-Science Infrastructure responsibilities managers, EU states national representatives Goals Research and monitor different ecosystems, biological species, their dynamics and migration. Use Case Description LifeWatch project and initiative intends to provide integrated access to a variety of data, analytical and modeling tools as served by a variety of collaborating initiatives. Another service is offered with data and tools in selected workflows for specific scientific communities. In addition, LifeWatch will provide opportunities to construct personalized ‘virtual labs', also allowing to enter new data and analytical tools. New data will be shared with the data facilities cooperating with LifeWatch. Particular case studies: Monitoring alien species, monitoring migrating birds, wetlands LifeWatch operates Global Biodiversity Information facility and Biodiversity Catalogue that is Biodiversity Science Web Services Catalogue Current Compute(System) Field facilities TBD Solutions Datacenter: General Grid and cloud based resources provided by national e-Science centers Storage Distributed, historical and trends data archiving Networking May require special dedicated or overlay sensor network. Software Web Services based, Grid based services, relational databases Big Data Data Source Ecological information from numerous observation Characteristics (distributed/centralized) and monitoring facilities and sensor network, satellite images/information, climate and weather, all recorded information. Information from field researchers Volume (size) Involves many existing data sets/sources Collected amount of data TBD Velocity Data analysed incrementally, processes dynamics (e.g. real time) corresponds to dynamics of biological and ecological processes. However may require real time processing and analysis in case of the natural or industrial disaster. May require data streaming processing. Variety Variety and number of involved databases and (multiple datasets, observation data is currently limited by available mashup) tools; in principle, unlimited with the growing ability to process data for identifying ecological changes, factors/reasons, species evolution and trends. See below in additional information. Variability (rate of Structure of the datasets and models may change change) depending on the data processing stage and tasks Big Data Science Veracity (Robustness In normal monitoring mode are data are statistically (collection, Issues) processed to achieve robustness. curation, Some biodiversity research are critical to data analysis, veracity (reliability/trustworthiness). action) In case of natural and technogenic disasters data veracity is critical.
Amsterdam Actors/Stakeholders and their roles and responsibilities End-users (biologists, ecologists, field researchers) Data analysts, data archive managers, e-Science Infrastructure managers, EU states national representatives Goals Research and monitor different ecosystems, biological species, their dynamics and migration. Use Case Description LifeWatch project and initiative intends to provide integrated access to a variety of data, analytical and modeling tools as served by a variety of collaborating initiatives. Another service is offered with data and tools in selected workflows for specific scientific communities. In addition, LifeWatch will provide opportunities to construct personalized ‘virtual labs', also allowing to enter new data and analytical tools. New data will be shared with the data facilities cooperating with LifeWatch. Particular case studies: Monitoring alien species, monitoring migrating birds, wetlands LifeWatch operates Global Biodiversity Information facility and Biodiversity Catalogue that is Biodiversity Science Web Services Catalogue Current Solutions Compute(System) Field facilities TBD Datacenter: General Grid and cloud based resources provided by national e-Science centers Storage Distributed, historical and trends data archiving Networking May require special dedicated or overlay sensor network. Software Web Services based, Grid based services, relational databases Big Data Characteristics Data Source (distributed/centralized) Ecological information from numerous observation and monitoring facilities and sensor network, satellite images/information, climate and weather, all recorded information. Information from field researchers Volume (size) Involves many existing data sets/sources Collected amount of data TBD Velocity (e.g. real time) Data analysed incrementally, processes dynamics corresponds to dynamics of biological and ecological processes. However may require real time processing and analysis in case of the natural or industrial disaster. May require data streaming processing. Variety (multiple datasets, mashup) Variety and number of involved databases and observation data is currently limited by available tools; in principle, unlimited with the growing ability to process data for identifying ecological changes, factors/reasons, species evolution and trends. See below in additional information. Variability (rate of change) Structure of the datasets and models may change depending on the data processing stage and tasks Big Data Science (collection, curation, analysis, action) Veracity (Robustness Issues) In normal monitoring mode are data are statistically processed to achieve robustness. Some biodiversity research are critical to data veracity (reliability/trustworthiness). In case of natural and technogenic disasters data veracity is critical.