Pollen Trends Analysis with AeRobiology
The workflow "Pollen Trends Analysis with AeRobiology" leverages the AeRobiology library to manage and analyze time-series data of airborne pollen particles. Aimed at understanding the temporal dynamics of different pollen types, this workflow ensures data quality, profiles seasonal trends, and explores temporal variations. It integrates advanced features for analyzing pollen concentrations and their correlation with meteorological variables, offering comprehensive insights into pollen behavior over time. The workflow enhances data accessibility, facilitating broader research and public health applications.
Background
In the dynamic landscape of environmental research and public health, the AeRobiology library (https://cran.r-project.org/web/packages/AeRobiology/index.html) emerges as a potent instrument tailored for managing diverse airborne particle data. As the prevalence of airborne pollen-related challenges intensifies, understanding the nuanced temporal trends in different pollen types becomes imperative. AeRobiology not only addresses data quality concerns but also offers specialized tools for unraveling intricate insights into the temporal dynamics of various pollen types.
Introduction
Amidst the complexities of environmental research, particularly in the context of health studies, the meticulous analysis of airborne particles—specifically various pollen types—takes center stage. This workflow, harnessing the capabilities of AeRobiology, adopts a holistic approach to process and analyze time-series data. Focused on deciphering the temporal nuances of pollen seasons, this workflow aims to significantly contribute to our understanding of the temporal dynamics of different airborne particle types.
Aims
The primary objectives of this workflow are tailored to address specific challenges and goals inherent in the analysis of time series pollen samples:
- Holistic Data Quality Assurance: Conduct a detailed examination of time-series data for various pollen types, ensuring completeness and accuracy to establish a robust foundation for subsequent analysis.
- Pollen-Specific Seasonal Profiling: Leverage AeRobiology's advanced features to calculate and visually represent key parameters of the seasonal trends for different pollen types, offering a comprehensive profile of their temporal dynamics.
- Temporal Dynamics Exploration: Investigate the temporal trends in concentrations of various pollen types, providing valuable insights into their evolving nature over time.
- Enhanced Accessibility: Employ AeRobiology's interactive tools to democratize the exploration of time-series data, making complex information accessible to a broader audience of researchers and professionals.
Scientific Questions
This workflow addresses critical scientific questions related to pollen analysis:
- Distinct Temporal Signatures: What are the discernible patterns and trends in the temporal dynamics of different airborne pollen types, especially during peak seasons?
- Pollen-Specific Abundance Variability: How does the abundance of various pollen types vary throughout their respective seasons, and what environmental factors contribute to these fluctuations?
- Meteorological Correlations: Are there statistically significant correlations between the concentrations of different pollen types and specific meteorological variables, elucidating the influencing factors unique to each type?
- Cross-Annual Comparative Analysis: Through the lens of AeRobiology, how do the temporal trends of different pollen types compare across different years, and what contextual factors might explain observed variations?
Default
Identification
- Date ( Publication )
- 2023-12-31T00:00:00
- Status
- On going / operational
- Version
- 1.0
- Keywords
- Phytosociological Analysis
- Keywords
- Vegetation Inventories
- Keywords
- Statistical Analysis
- Keywords
- Data Preprocessing
- Keywords
- Interactive Graphs
- Keywords
- Species Dominance
- Keywords
- Altitudinal Distribution
- Keywords
- Species Coverage
- Keywords
- Similarity Dendrogram
- Keywords
- Species Interactions
- Keywords
- Fidelity Index
- Keywords
- Environmental Management
- Access constraints
- Copyright
- Other constraints
- Copyright 2023 Khaos Research Group
- Protocol
- DOI
- Service Name
- Import file from CSV
- Service Description
- Input CSV dataset
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/core/ImportFile/0.0.5
- Service Name
- iPot Pollen
- Service Description
- Interactive graph of the pollen data during one season
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/IPlotPollen/1.0.0
- Service Name
- iPot Year
- Service Description
- Interactive graph of the pollen data during several seasons
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/IPlotYear/1.0.0
- Service Name
- Quality Control
- Service Description
- Check the quality of several pollen types
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/QualityControl/1.0.0
- Service Name
- Calculate PS
- Service Description
- Calculate the main parameters of the pollen season regarding phenology and pollen intensify
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/CalculatePs/1.0.0
- Service Name
- Plot PS
- Service Description
- Plot the main pollen season from a single pollen type
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/PlotPs/1.0.0
- Service Name
- Pollen Calendar
- Service Description
- Calculate the pollen calendar from several pollen types
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/PollenCalendar/1.0.0
- Service Name
- Plot Abundance
- Service Description
- Bar plot based on the relative abundance in the air of pollen types with respect of the total amount
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/IplotAbundance/1.0.0
- Service Name
- Analyse Trend
- Service Description
- Graphical representation of the pollen trends
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/AnalyseTrend/1.0.0
- Service Name
- Plot Pheno
- Service Description
- Graphical representations of the phenological parameters
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/IPlotPheno/1.0.0
- Service Name
- Plot Trend
- Service Description
- Graphical representations of the trends in some main pollen season variables
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/PlotTrend/1.0.0
- Service Name
- Plot Summary
- Service Description
- Graphical representation of average, maximum and minimum pollen concentration by type
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/PlotSummary/1.0.0
- Service Name
- Plot Normsummary
- Service Description
- Graphical representation of pollen concentration by type and year
- Service Reference (id)
- https://gitlab.lifewatch.dev/lfw002-khaos/wrapper-library/-/tree/develop/data-sink/PlotNormsummary/1.0.0
- Workflow Helpdesk
- https://helpdesk.lifewatch.eu