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Link to JuliaCon 2021 talk and simplify readme
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README.md

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[![Version](https://juliahub.com/docs/DataSets/version.svg)](https://juliahub.com/ui/Packages/DataSets/4adr3)
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[![docs latest](https://img.shields.io/badge/docs-latest-blue.svg)](https://juliahub.com/docs/DataSets)
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DataSets.jl exists to help manage data and reduce the amount of data wrangling
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code you need to write. It's annoying to write
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* Command line wrappers which deal with paths to data storage
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* Code to load and save from various *data storage systems* (eg, local
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filesystem data; local git data, downloaders for remote data over various
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protocols, etc)
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* Code to load the same data model from various serializations (eg, text:
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plain/compressed, property tree: toml/json/msgpack/bson/...
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tabular: csv/csv.gz/parquet/sqlite/...)
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* Code to deal with data lifecycle; versions, provenance, etc
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DataSets helps make data wrangling code more reusable.
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DataSets provides scaffolding to make this kind of code more reusable. We want
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to make it easy to *relocate* an algorithm between different data environments
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without code changes. For example from your laptop to the cloud, to another
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user's machine, or to an HPC system.
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* We want to make it easy to *relocate* an algorithm between different **data
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storage environments** without code changes. For example from your laptop to
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the cloud, to another user's machine, or to an HPC system.
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* We want to reduce coupling between data and code, by storing **rich type
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information** in metadata. Metadata bridges the gap between the ad hoc
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implicit type system of data outside your program and the Julia data
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structures within your program.
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Read [**the latest documentation**](https://juliahub.com/docs/DataSets) more information.
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Watch [**DataSets.jl talk**](https://www.youtube.com/watch?v=PJkf0CO5APs) from
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JuliaCon 2021, or read [**the latest documentation**](https://juliahub.com/docs/DataSets)
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more information.
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### Development
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