Overview | Installation | Installing the rclone binary | Configuring a remote | Amazon S3 | MinIO / S3-compatible | Listing configured remotes | Listing objects | Local paths (no credentials needed) | Remote paths | Copying and syncing files | Copy | Copy to/from the cloud | Sync | Move | Other file operations | Using the low-level rclone() wrapper | Migrating from minioclient

Introduction | Creating an RDF Store | Loading RDF Data | Turtle | N-Triples | From Files | SPARQL Queries | SELECT Queries | Filtering and Sorting | ASK Queries | Aggregation | Modifying Data | SPARQL Update | Direct Triple Manipulation | Serialization | Best Practices | Further Reading

arkdb | Package rationale | Installation | Tutorial | Creating an archive of an existing database | Unarchive | Pluggable text formats | A note on compression | Distributing data

Overview of the EML hierarchy | Our example: (re)-creating hf205.xml | Our strategy | Attribute Metadata | Data file format | Assembling the dataTable | Coverage metadata | Creating methods | Creating parties | Creating a keywordSet

Earth Data Authentication

Earth Data Authentication | Search via STAC | Building a Data Cube | Comparison

It's all about the triples | Subject URIs | Predicate URIs | Datatype URIs | Triples in rdflib | Dialing back the ugly | Prefixes for URIs | URI vs URL | Blank nodes | Triple notation: nquads rdfxml, turtle, and nquads | JSON-LD | From tables to Graphs | SPARQL: A Graph Query Language | SPARQL: Getting back to Tidy Tables!

Basic tree and metadata queries | Replicating results | Meta-Analysis

Why piggyback? | Authentication | Download Files | Download URLs | Reading data for R usage | Reading files | Reading from URLs | Uploading data | Write R object directly to release | Deleting Files | Listing Files | Caching | Valid file names | A Note on GitHub Releases vs Data Archiving | What will GitHub think of this?

piggyback vs the alternatives | Git LFS | Amazon S3 | Scientific repositories with private storage | datastorr | Sharding on GitHub

Data Too Big To Fit In Memory | nflverse play by play | DuckDB | duckdbfs

netcdf, 1 GB file | Zarr, 31 TB

Earthdata

Getting started | Finches Examples | Anoles example | Citation

contentid | Quick start | Overview | How this works | Acknowledgements

Data Schema | Hierarchy Terms | Synonyms | Common names | Linked Data formats | Conventions | Data Processing | Data Versioning

Installation | Getting Started | Remote data access | Local data

Overview | Add a custom unit to EML | Reading EML: parsing unit information, including custom unit types

codemetar: generate codemeta metadata for R packages | Why create a codemeta.json for your package? | Installation and usage requirements | Create a codemeta.json in one function call | Keep codemeta.json up-to-date | A brief intro to common terms we'll use: | How to improve your package's codemeta.json? | Going further

RSQLite | MonetDBLite & duckdb | in-memory | Manual control of the backend engine | Local storage | Other backends

knitcitations | Installation | Quick start: rmarkdown (pandoc) mode | Cite by DOI | Cite by URL | Cite bibtex and bibentry objects directly | Re-using Keys | Displaying the final bibliography | Example file for RStudio / rmarkdown | References

emld | Installation | Motivation | Reading EML | Writing EML | Working with EML as JSON-LD | As JSON: Query with JQ | As semantic data: SPARQL queries

Advanced annotation | Taxonomic identifiers | Working with character data | Extracting character data

Extending the NeXML standard through metadata annotation.

SPARQL Queries

Writing NeXML metadata | Taxonomic identifiers | Custom metadata extensions | Reading NeXML metadata | Merging metadata tables

Understanding the nexml S4 object

Installation | Configuration | Server management

Vignette Info | Styles | Figures | More Examples