Visualize Fungal Diversity with MycView — Case Studies & Workflows

Getting Started with MycView — Features, Tips, and Best Practices

What is MycView

MycView is a visualization and analysis tool designed for mycology datasets, combining specimen records, imagery, and analytical layers to help researchers, citizen scientists, and educators explore fungal diversity. It organizes specimen metadata, supports geospatial mapping, and provides image-centric workflows for identification and quality control.

Key Features

• Specimen & Metadata Management: Import CSV, Excel, or Darwin Core formatted records; map fields to standardized metadata (collector, date, locality, taxon, voucher ID).
• Image Handling: Bulk upload, thumbnail gallery, zoomable viewers, and side-by-side comparison.
• Interactive Mapping: Display specimen occurrences on base maps, filter by date, taxon, or custom attributes, and export shapefiles/KML.
• Filtering & Querying: Faceted filters, saved queries, and advanced search (range queries for dates, numeric fields).
• Annotation & Notes: Attach curator notes, flag records for review, and track curation history.
• Integrations & Export: Export datasets in common formats (CSV, GeoJSON) and connect to GBIF or institutional databases via API.
• Dashboard & Visualizations: Charts for taxonomic breakdowns, temporal trends, and collector activity; customizable dashboards.
• User Roles & Permissions: Role-based access for collaborators, with read/write/curation tiers.

Quick Start — Setup in 6 Steps

1. Prepare your data: Clean up a spreadsheet with columns: specimen ID, scientific name, date (ISO YYYY-MM-DD), latitude, longitude, locality, collector, image filenames.
2. Create a project: Start a new project/workspace in MycView and choose a base map (satellite or topographic).
3. Import records: Upload your file and map each column to MycView fields. Validate required fields and resolve any parsing errors.
4. Upload images: Bulk-upload associated images and link them to specimen IDs (or let MycView auto-match by filename).
5. Explore the map & gallery: Use the map to inspect geographic coverage and the gallery to review specimen images.
6. Save & share: Save a snapshot of filters and export a subset for downstream analysis or sharing.

Best Practices for Data Quality

• Use standardized names: Resolve scientific names against a taxonomic backbone (e.g., Index Fungorum, MycoBank) to avoid synonyms and misspellings.
• Standardize dates and coordinates: Use ISO date format and decimal degrees for coordinates; include coordinate uncertainty when possible.
• Include provenance metadata: Keep collector, collection date, and voucher repository to enable reproducibility.
• Image standards: Capture scale bars, multiple angles, and metadata (camera, focal length) in EXIF when possible.
• Flag uncertain IDs: Use a confidence field or annotation system rather than overwriting original identifications.

Tips for Efficient Workflows

• Bulk edits: Use bulk-edit features for namespace changes or georeferencing batches.
• Saved filters & views: Create saved queries for commonly used subsets (e.g., region-specific or taxon-specific).
• Automate taxon updates: Schedule regular name reconciliation with authoritative taxonomic sources to keep names current.
• Use curated checklists: For regional projects, load a curated checklist to help constrain identifications and speed validation.
• Leverage API: Script uploads or downloads using the MycView API for reproducible pipelines.

Collaboration & Curation

• Role assignment: Assign curators to specific taxonomic groups or geographic regions to distribute workload.
• Curation logs: Maintain audit trails for changes and provide brief rationale notes for taxonomic or locality edits.
• Peer review: Use a two-step curation flow where initial identifications are reviewed before finalizing records.

Common Pitfalls & How to Avoid Them

• Mismatched image links: Ensure filenames match specimen IDs; use automated matching tools and review unmatched files.
• Coordinate errors: Spot-check outliers on the map; implement bounds checks (e.g., lat between -90 and 90).
• Inconsistent taxon ranks: Normalize ranks (species, genus, family) and avoid mixing rank annotations in name fields.
• Overwriting original data: Keep raw imports immutable; record curated values in separate fields to preserve provenance.

Exporting & Downstream Use

• Export filtered datasets as CSV or GeoJSON for GIS and statistical analysis.
• Use the API to feed cleaned occurrence data into GBIF, institutional repositories, or analytical notebooks (R/Python).
• Generate printable specimen reports or specimen labels with standardized templates for physical collections.

Example Workflow (Field-to-Repository)

1. Field notes and photos → standardized CSV + images.
2. Import into MycView → automated georeferencing and name reconciliation.
3. Curator review → annotations and confidence scores added.
4. Export curated dataset → deposit to institutional repository and GBIF.

Troubleshooting & Support

• Check import logs for parsing errors.
• Use map filters to locate suspicious records (e.g., wrong country).
• Reconcile names against taxonomic databases when IDs look stale.
• For persistent issues, consult MycView documentation or contact your system administrator.

Final Recommendations

• Establish a standard import template for your team.
• Implement periodic audits (quarterly) of taxonomy, georeferencing, and image links.
• Train collaborators on role-based curation workflows to maintain consistent data quality.