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Data Science AnalyticsTop 10 Best Metadata Editing Software of 2026
Top 10 metadata editing software ranked by metadata fields, batch editing, and export options, with comparisons for photo and file workflows.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
XnView MP is the best fit if local operators need reliable batch metadata fixes and renaming straight in image collections, whereas Capture One is the better choice for photography teams who want tight metadata control throughout capture-to-export processing.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
XnView MP
File renaming can be mapped directly to metadata fields during batch processing.
Built for fits when local operators need batch metadata fixes and renaming from tags..
Capture One
Editor pickMetadata templates combined with file renaming from metadata fields during batch operations.
Built for fits when photography teams need batch metadata control during capture-to-export workflows..
Metadata++
Editor pickFilename generation driven by metadata fields supports automated renaming workflows for large libraries.
Built for fits when teams need repeatable batch metadata edits and standardized mappings across folders..
Related reading
Comparison Table
XnView MP
SMBXnView MP browses, converts, and edits metadata in image collections.
File renaming can be mapped directly to metadata fields during batch processing.
XnView MP uses a single desktop workspace for browsing media, viewing tag fields, and applying edits to embedded metadata and XMP sidecar files. The tool handles batch tag editing with recursive folder scanning and can drive file renaming from metadata, which helps maintain consistent naming during catalog cleanups. It also supports metadata templates for repeatable fields and offers metadata import and export workflows for moving values between spreadsheets and files.
A tradeoff appears in governance and automation depth since XnView MP has no RBAC model, audit log, or server-side API surface for centrally managed editing. For large media libraries, the best fit is a local operator workflow that runs scripted-looking batches by folder patterns, then rechecks changes using the same viewer.
- +Batch tag editing across folders with recursive scanning and template reuse
- +File renaming driven by tag values for consistent library structure
- +Metadata import and export using CSV-style workflows for bulk operations
- +Works with embedded metadata and XMP sidecar files in one editor
- –No RBAC controls or audit log for multi-admin environments
- –Metadata validation is limited to basic consistency checks
- –Video container metadata support is narrower than specialized editors
- –Automation relies on local batch actions rather than an API
Media library managers
Normalize titles and artists in bulk
Clean library naming and ordering
Photo archivists
Repair EXIF and sidecar consistency
Reduced catalog mismatches
Show 2 more scenarios
Digital asset operations
Spreadsheet-driven tag updates
Faster bulk cataloging cycles
Import tabular metadata values then export changes back to files after review.
Creative teams
Standardize credits and dates
Consistent metadata across deliveries
Normalize repeated metadata fields across many files using batch templates.
Best for: Fits when local operators need batch metadata fixes and renaming from tags.
More related reading
Capture One
enterpriseCapture One manages and edits metadata during professional photo cataloging and processing.
Metadata templates combined with file renaming from metadata fields during batch operations.
Capture One enables batch tag editing across catalogs and collections, and it can also rename files from metadata fields while writing the updated values. Metadata templates let common presets apply repeatedly to consistent shooting scenarios, which reduces drift across sessions. It supports both embedded metadata workflows and XMP sidecar workflows, so teams can choose a write strategy that matches their storage and sharing model.
A tradeoff is that deeper metadata governance, like validating controlled vocabularies and enforcing strict schema constraints, relies more on disciplined template usage than on built-in validation rules. Capture One fits best when metadata changes are part of a capture-to-export process where catalogs, styles, and naming conventions need to stay aligned.
- +Batch edits across catalogs with consistent EXIF, IPTC, and XMP writing
- +Metadata templates keep repeated session tagging aligned
- +File renaming from metadata fields reduces manual cleanup
- +XMP sidecar workflow supports pipelines that avoid embedded changes
- –Strict metadata schema validation needs external process discipline
- –Metadata edits depend on catalog organization to scale across large libraries
- –Less suitable for lightweight, metadata-only batch jobs without catalog setup
Wedding photo editors
Normalize client deliverable metadata in batches
Cleaner deliveries with less manual editing
Studio production teams
Standardize capture notes across sessions
Reduced tagging inconsistency
Show 2 more scenarios
Media archive managers
Manage XMP sidecar-based metadata updates
Safer archive behavior
Write changes to XMP sidecars to keep embedded metadata stable for archival workflows.
Content marketing teams
Rename assets from standardized fields
Faster search and retrieval
Generate filenames from metadata values during batch edits to maintain library ordering.
Best for: Fits when photography teams need batch metadata control during capture-to-export workflows.
Metadata++
SMBMetadata++ edits metadata across images, documents, audio, and video files.
Filename generation driven by metadata fields supports automated renaming workflows for large libraries.
Metadata++ is built around batch tag editing, recursive folder scanning, and filename generation from metadata for repeatable ingestion workflows. It supports import and export flows for metadata so structured updates can move between CSV-driven processes and bulk file edits. Tag mapping and metadata templates help normalize fields like dates and controlled values across mixed libraries.
A tradeoff appears in workflow complexity for advanced normalization, because controlled vocabularies and mappings require upfront setup to avoid propagating incorrect values. It fits best when recurring metadata cleanup or synchronization is needed across many files and the team wants repeatable templates rather than one-off edits.
- +Batch operations with recursive folder scanning for large collections
- +Metadata templates and tag mapping support consistent field standards
- +Import and export workflows fit structured CSV-driven updates
- +Filename generation from metadata supports repeatable renaming
- –Advanced normalization needs careful template and mapping setup
- –Complex multi-format edits can require staged workflows to verify output
- –Governance-style controls like RBAC and detailed audit logs are not emphasized
Media operations teams
Standardize tags across incoming batches
Consistent library metadata
Digital asset coordinators
Rename files from embedded metadata
Fewer naming collisions
Show 2 more scenarios
Cataloging teams
Update metadata from CSV workflows
Faster batch corrections
Exported and imported metadata enables structured edits and rapid bulk corrections.
Photo archivists
Normalize date values at scale
Cleaner chronological sorting
Bulk date normalization reduces inconsistencies across files in folder trees.
Best for: Fits when teams need repeatable batch metadata edits and standardized mappings across folders.
digiKam
SMBdigiKam organizes photographs and edits IPTC, XMP, and EXIF metadata.
digiKam’s metadata tools connect to its media library and batch jobs, keeping changes consistent across recursive scans.
digiKam is a desktop photo manager that also performs ID3 tag editing and EXIF editing inside a media library workflow. Metadata edits integrate with browsing, batch operations, and structured tag management across folders and collections.
It supports import and export of metadata, which enables CSV metadata workflows and file-to-library synchronization. The tool is most effective when metadata changes stay tied to how assets are curated, searched, and organized rather than treated as isolated per-file edits.
- +Batch metadata editing tied to library views and selections
- +Supports cover art embedding and lyric embedding workflows
- +Recursive folder scanning and metadata sync for large archives
- +Built-in CSV metadata import and export workflows
- –Workflow requires GUI navigation across multiple metadata modules
- –Complex rules for filename changes from metadata can cause collisions
- –Deep customization needs more configuration discipline than simple tag editors
Best for: Fits when large photo collections need batch metadata edits tied to a library workflow.
Photo Mechanic
vertical specialistPhoto Mechanic adds captions, keywords, copyright data, and other IPTC metadata to photographs.
Camera-aware, batch-first metadata editing that tightly couples preview workflow with metadata template application.
Photo Mechanic edits embedded and sidecar metadata for large photo and media libraries with a fast, preview-first workflow. It supports batch tag editing and camera-aware EXIF and IPTC workflows that keep filenames and metadata in sync during organization.
The program’s metadata templates and mapping let teams standardize common fields while processing thousands of files. Its emphasis is on throughput, metadata preservation during import, and repeatable batch operations rather than a web-based management layer.
- +Very fast ingest and preview that supports high-throughput metadata edits
- +Batch editing works across embedded metadata and XMP sidecars
- +Metadata templates and mappings reduce repetitive field entry
- +Folder-based organization can drive consistent tag and rename workflows
- –Automation depends on workflow design inside the desktop editor rather than centralized APIs
- –Metadata validation and schema enforcement for controlled vocabularies is limited
- –Collisions during metadata-driven renaming require careful rule planning
- –Enterprise governance features like RBAC and audit logs are not its focus
Best for: Fits when photographers and studios need rapid batch metadata fixes without building custom automation systems.
A Better Finder Attributes
SMBA Better Finder Attributes edits file dates, Finder attributes, and selected media metadata on macOS.
Rules-style selection inside the file browser drives targeted batch metadata updates across extended attributes.
A Better Finder Attributes is a macOS metadata editor focused on editing Finder-visible attributes like labels, comments, and other file properties, with workflows built around directory browsing. Batch editing is supported by selecting files in Finder-like views and applying changes across many items at once.
The tool also supports writing metadata into extended attributes and offers rules-style selection so edits can be targeted by current attribute values. It is best suited for people who want visual, filesystem-first metadata management rather than external metadata mapping pipelines.
- +Finder-like browser workflow supports fast selection and attribute edits
- +Batch changes apply to multiple items with consistent attribute updates
- +Rules-based filtering targets subsets without exporting to spreadsheets
- +Extended attribute handling enables metadata storage beyond basic fields
- –Limited coverage for embedded media metadata formats like ID3 and EXIF
- –No documented API surface for automation across non-macOS environments
- –Filename collision handling is manual when edits also affect names
- –Large recursive scans can feel slower than dedicated ingestion tools
Best for: Fits when macOS users need batch edits for Finder-visible and extended attributes without code.
GeoSetter
vertical specialistGeoSetter edits GPS, IPTC, and EXIF metadata for geotagged photographs.
GeoSetter’s metadata-to-filename mapping lets bulk runs generate new names from tag values while keeping edits aligned to the same folder selection.
GeoSetter focuses on turning metadata edits into repeatable batch operations with a visual workflow for common file types. It supports editing embedded metadata and writing it back to media files, including photo and audio tags.
The tool also provides mappings for renaming from metadata and for applying consistent template-like settings across folders. For teams that maintain media libraries, GeoSetter’s workflow favors file-based import and export patterns over server-based governance features.
- +Batch editing of embedded tags across folder trees
- +Visual tag mapping for consistent edits during bulk runs
- +Metadata-driven filename generation with collision handling
- +Supports export and import workflows for metadata sets
- –Limited coverage of video container metadata compared with media managers
- –No native API surface for automation or external pipelines
- –Metadata validation rules are shallow for complex tag schemas
- –Recursive scanning performance can lag on very large libraries
Best for: Fits when desktop teams need batch tag editing with predictable file-based workflows for photos and audio.
Kid3
vertical specialistKid3 edits tags in audio files and supports batch conversion between tag formats.
Field-to-tag mapping plus batch templates that apply transformations across folders and keep edits consistent.
Kid3 targets desktop users who need repeatable metadata edits across many files.
Its batch workflow uses mapping rules and import and export so metadata can be edited in bulk and applied back to files.
- +Batch editing with rule-based mapping from external fields to tags
- +Batch import and export workflows for offline CSV and spreadsheet editing
- +Recursive folder scanning to apply changes across deep library structures
- +Supports cover art embedding into media containers
- –Tag support coverage varies by media format and container
- –Advanced mapping workflows require careful setup to avoid unintended changes
- –Media conversion and metadata preservation depend on external tools
Best for: Fits when large media libraries need repeated batch tag mapping without a cloud workflow.
Exif Pilot
vertical specialistExif Pilot views and edits EXIF, IPTC, and XMP data in digital images.
Metadata templates combined with tag mapping lets repeatable batch updates translate between external field names and embedded metadata tags.
Exif Pilot edits embedded image and media metadata fields such as EXIF, IPTC, and XMP and writes updates back to the same files.
Exif Pilot supports batch processing with recursive folder scanning, metadata templates, and tag mapping to keep tagging consistent across large sets.
Exif Pilot enables metadata import and export workflows to translate between file metadata and external lists for repeatable tag operations.
Exif Pilot concentrates on desktop batch editing rather than multi-user administration features like RBAC or audit logs.
- +Batch folder scanning with recursive operations
- +Metadata templates and tag mapping for consistent fields
- +Import and export workflows for moving tag sets
- +Controls for filename changes derived from metadata fields
- –Limited multi-user governance such as RBAC and audit logs
- –Thin automation surface compared with API-driven metadata pipelines
- –Lower coverage for non-image container metadata edits
- –Filename collision handling can require manual checks in dense sets
Best for: Fits when local teams need repeatable batch metadata edits across large photo folders.
TagScanner
vertical specialistTagScanner edits and organizes tags in digital music collections.
Filename renaming directly driven by tag values with collision handling during batch runs.
TagScanner is a Windows tag editing tool that focuses on fast batch workflows and metadata editing across large media folders. It provides ID3 tag editing, EXIF editing for image files, and XMP sidecar handling so edits can stay consistent across common media ecosystems.
The software pairs preview and filename updates from tags with mapping controls for repeatable batch operations. TagScanner also supports recurring scans and export-style workflows for CSV based metadata processing.
- +Batch tag editing with recursive folder scanning for large libraries
- +Preview-first edits reduce accidental overwrites during bulk changes
- +Filename renaming from tag values with collision handling tools
- +CSV metadata workflow supports repeatable offline corrections
- –No documented API for automation or external integrations
- –Governance controls like RBAC and audit logs are not available
- –Limited automation for cross-format normalization beyond built-in mappings
- –Workflow depends on accurate tag mapping setup per file type
Best for: Fits when teams need Windows-based batch tag editing with filename updates and CSV-driven corrections.
Conclusion
After evaluating 10 data science analytics, XnView MP stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right metadata editing software
This buyer's guide covers metadata editing software used to write and normalize embedded and sidecar metadata at scale across images, audio, and video files. It focuses on how tools like XnView MP, Capture One, Metadata++, and digiKam handle batch edits, recursive folder workflows, and metadata-driven filename changes.
Coverage includes local file editors such as Exif Pilot and Kid3, macOS attribute workflows with A Better Finder Attributes, geotag batch operations via GeoSetter, and Windows batch tag editing with TagScanner. The guide translates the observed capabilities and constraints of all ten tools into selection criteria that match real cataloging workflows.
Evaluation criteria for metadata editors: template control, batch coverage, and workflow scaling
Metadata editing projects fail when field mapping, batch scope, or rename rules are unclear, because bulk updates can spread errors across entire libraries. The evaluation criteria below center on how each tool updates metadata formats and how it scales to recursive folder processing and repeatable templates.
XnView MP, Capture One, Metadata++, and Photo Mechanic each show different strengths around metadata-driven renaming and template-based assignment, while A Better Finder Attributes and Kid3 highlight workflow differences driven by OS focus and media type coverage.
Metadata-driven filename generation with collision controls
Filename generation mapped to metadata fields drives consistent library structure during bulk runs in tools like XnView MP and Metadata++. TagScanner and GeoSetter also generate names from tag values, and digiKam warns that complex filename rules can create collisions that need careful planning.
Recursive folder batch editing across embedded fields and sidecars
Recursive folder scanning for batch updates is a core strength in XnView MP, Metadata++, and Kid3, which apply metadata changes across deep library structures. digiKam and Photo Mechanic also pair batch operations with their media workflows so updates remain consistent across repeated scans.
Template-based field mapping for repeatable tagging standards
Metadata templates and tag mapping keep repeated edits aligned to the same field standards in Capture One and Exif Pilot. Metadata++ and Photo Mechanic use templates and mappings to reduce manual entry during high-volume caption, rights, and IPTC-style updates.
Import and export workflows for offline CSV-based metadata operations
CSV-style metadata import and export workflows support structured bulk updates in XnView MP and Metadata++. digiKam also includes built-in CSV import and export, and Kid3 supports import and export workflows for mapping filenames, folders, and tag values from external lists.
Preview-first editing workflow for throughput and safer bulk changes
Photo Mechanic emphasizes camera-aware, preview-first batch metadata editing that tightly couples templates with a fast ingest-and-review loop. Kid3 also supports consistent batch mapping workflows and cover art embedding, and A Better Finder Attributes prioritizes filesystem-first selection to reduce accidental overwrites.
Governance and multi-admin safety controls
Multi-admin governance is limited in many local editors, so RBAC and audit logs are absent in XnView MP, Photo Mechanic, TagScanner, and Exif Pilot. When governance-style controls matter, the practical implication is to rely on local operator discipline and controlled batch pipelines rather than built-in approval trails.
Decision framework for choosing a metadata editor that matches the target workflow
Selection should start from the target workflow shape, not the file format list. Tools like Capture One and digiKam scale inside a catalog or media-library workflow, while XnView MP and Metadata++ treat edits as file-centric batch operations using templates and import-export steps.
Once workflow shape is chosen, the next decision is metadata write strategy and rename behavior. Tools such as Photo Mechanic, TagScanner, and XnView MP each tie batch edits to filename updates, so collision handling and validation expectations should be evaluated together.
Match the tool to the workflow owner: catalog pipeline vs local file batch jobs
Capture One fits when metadata edits must stay consistent through its catalog processing and export path, with EXIF, IPTC, and XMP writing aligned to batch sessions. XnView MP and Metadata++ fit when local operators need file-based bulk metadata fixes across folders without building an external synchronization pipeline.
Choose the metadata write mode: embedded changes vs XMP sidecar pipelines
Capture One supports an XMP sidecar workflow so teams can keep changes aligned with XMP-driven pipelines without forcing embedded edits. XnView MP, Metadata++, and Exif Pilot both support embedded metadata edits and XMP sidecar handling in the same editor, which fits mixed libraries but still keeps scope local to files.
Validate how filename generation works and what happens on collisions
XnView MP can map file renaming directly to metadata fields during batch processing, which suits structured renaming jobs. TagScanner and GeoSetter also drive renaming from tag values and include collision-handling tools, while digiKam notes that complex filename-change rules can cause collisions that require careful rule design.
Decide the mapping inputs: templates only vs template-plus-import pipelines
If repeatable tagging standards must be applied inside a consistent template set, Capture One and Photo Mechanic use metadata templates combined with renaming rules during batch operations. If batch updates originate from an external spreadsheet workflow, XnView MP and Metadata++ provide CSV-style import and export workflows that fit structured cataloging jobs.
Assess governance depth based on multi-admin requirements
Local batch editors such as XnView MP, Photo Mechanic, TagScanner, and Exif Pilot do not emphasize RBAC controls or audit-log safety, which means change tracking must be handled operationally. If the team cannot rely on operator discipline, reduce batch scope and stage edits using templates and export files rather than expecting built-in approvals.
Confirm coverage for the media types that matter most to the library
Kid3 focuses on audio tags and supports batch tag editing, cover art embedding, and file-to-tag mapping workflows across media folders. GeoSetter and Exif Pilot focus on photo-oriented metadata like EXIF and IPTC with batch folder operations, while DigiKam adds image-library tooling plus workflows like lyric embedding.
Which organizations and operators benefit from metadata editing tools
Metadata editing tools fit teams that need consistent tagging and repeated cleanup across large collections, where manual edits do not scale. The best-fit tool depends on whether edits must stay tied to a media library workflow, remain file-centric, or focus on specific metadata domains.
The audience segments below map to the stated best-for situations for XnView MP, Capture One, Metadata++, digiKam, Photo Mechanic, A Better Finder Attributes, GeoSetter, Kid3, Exif Pilot, and TagScanner.
Local operators doing batch metadata fixes and metadata-driven renaming
XnView MP is a strong match because it performs batch tag editing across folders with recursive scanning and can map file renaming directly to metadata fields. TagScanner also fits Windows-based bulk renaming from tag values and supports CSV-driven corrections.
Photography teams normalizing capture outputs through a catalog-to-export workflow
Capture One fits teams that need consistent EXIF, IPTC, and XMP handling aligned to catalog processing and batch sessions. Photo Mechanic fits studios that need camera-aware, preview-first throughput while applying IPTC-style templates and keeping filenames and metadata in sync.
Teams standardizing metadata mappings across folder collections using templates and structured workflows
Metadata++ fits organizations that want batch operations with metadata templates and tag mapping for standardized field standards, backed by CSV-driven import and export workflows. Exif Pilot also fits local teams that need metadata templates plus tag mapping to translate external field names into embedded metadata tags.
Large photo archives where metadata edits must stay tied to library browsing and sync
digiKam fits large photo collections because its metadata tools connect to media-library views and batch jobs during recursive scans. It also supports workflows like cover art embedding and lyric embedding that are harder to replicate in general-purpose metadata editors.
macOS users managing Finder-visible and extended attributes in bulk
A Better Finder Attributes fits macOS workflows because it edits Finder-visible labels and comments and writes metadata into extended attributes. It avoids deep embedded media metadata editing like ID3 and EXIF, so it is best for filesystem-first metadata management.
Common failure modes when rolling out metadata editing in real libraries
Common mistakes come from treating bulk metadata editing as a single format problem. Many failures instead happen when rename rules, mapping inputs, and governance expectations are misaligned with the tool’s actual workflow shape.
These pitfalls show up across XnView MP, Capture One, Metadata++, digiKam, Photo Mechanic, Exif Pilot, A Better Finder Attributes, GeoSetter, Kid3, and TagScanner.
Assuming built-in governance exists for multi-admin batch changes
XnView MP, Photo Mechanic, TagScanner, and Exif Pilot do not provide RBAC controls or audit logs for multi-admin environments. The corrective action is to restrict batch runs to controlled operator workflows and stage changes with exports and template-based batches.
Overconfidence in filename-change rules without testing collision scenarios
digiKam warns that complex rules for filename changes can cause collisions, and GeoSetter requires collision handling during metadata-driven renaming. The corrective action is to run a limited subset batch first and validate rename outcomes before applying recursive scans across the entire folder tree.
Treating metadata validation as comprehensive normalization across formats
Capture One and Metadata++ both rely on template and mapping setup, and Capture One’s strict metadata schema validation needs external process discipline for normalization. The corrective action is to pre-define field mapping standards and validate outputs using staged batches before wide recursive runs.
Expecting the tool to cover all media containers uniformly
GeoSetter and Exif Pilot have limited coverage for video container metadata compared with specialized media editors, and Kid3 tag support varies by media format and container. The corrective action is to confirm the specific target formats first and use separate tools for container classes that fall outside the editor’s supported coverage.
Using a lightweight OS-focused editor for embedded media metadata workloads
A Better Finder Attributes targets Finder-visible and extended attributes and has limited coverage for embedded media formats like ID3 and EXIF. The corrective action is to choose XnView MP, Exif Pilot, or Kid3 for embedded and sidecar metadata editing rather than trying to force Finder-only workflows.
How We Selected and Ranked These Tools
We evaluated XnView MP, Capture One, Metadata++, digiKam, Photo Mechanic, A Better Finder Attributes, GeoSetter, Kid3, Exif Pilot, and TagScanner using features, ease of use, and value, and the overall rating weighted features most heavily at forty percent. Ease of use and value were each scored next at thirty percent, which means high-scoring metadata capabilities still lose ground when batch workflows become cumbersome.
This ranking is editorial research that scores only what the provided tool records describe, including named batch behaviors like recursive folder scanning, CSV-style import-export workflows, metadata-driven filename mapping, and the presence or absence of governance controls such as RBAC and audit logs. XnView MP separated from lower-ranked tools because it combines recursive batch tag editing with file renaming mapped directly to metadata fields and it also supports CSV-style metadata import and export, which lifted both the features score and the practical throughput story.
Frequently Asked Questions About metadata editing software
How does batch metadata editing differ between XnView MP and Metadata++?
Which tools support filename generation from tag values with collision handling?
How can teams normalize date and time fields at scale across EXIF, IPTC, and XMP?
When should a team use a library-based workflow like digiKam instead of local file-only editing like XnView MP?
Which tool is better for preview-first metadata fixes, Photo Mechanic or GeoSetter?
What breaks if metadata templates and field mapping are inconsistent across a folder run?
How do teams handle cover art embedding during batch tagging?
Which tools support metadata import and export workflows for CSV-driven corrections?
How does security and access control differ between Capture One’s workflow and local editors like Exif Pilot or XnView MP?
Where does metadata preservation during conversion matter most, and which tools address it directly?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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