JOSS paper about Pooch (fatiando#116)

This is the paper we will submit to the Journal of Open Source Software. 
All authors have reviewed the paper and agreed to be listed on it.

Fixes fatiando#112

paper/paper.bib

@@ -0,0 +1,78 @@
+@article{scikit-learn,
+  title={Scikit-learn: Machine Learning in {P}ython},
+  author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V. and
+          Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P. and
+          Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
+          Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
+  journal={Journal of Machine Learning Research},
+  volume={12},
+  pages={2825--2830},
+  year={2011}
+}
+
+@article{scikit-image,
+  title={scikit-image: image processing in Python},
+  author={Van der Walt, Stefan and Sch{\"o}nberger, Johannes L and
+          Nunez-Iglesias, Juan and Boulogne, Fran{\c{c}}ois and Warner,
+          Joshua D and Yager, Neil and Gouillart, Emmanuelle and Yu, Tony},
+  journal={PeerJ},
+  volume={2},
+  pages={e453},
+  year={2014},
+  publisher={PeerJ Inc.},
+  doi={10.7717/peerj.453}
+}
+
+@software{metpy,
+  title={MetPy: A {Python} Package for Meteorological Data},
+  author={May, Ryan M. and Arms, Sean C. and Marsh, Patrick and Bruning, Eric and Leeman, John R.
+          and Goebbert, Kevin and Thielen, Jonathan E. and Bruck, Zachary},
+  organization={Unidata},
+  year={2008 - 2019},
+  version={0.11.1},
+  doi={10.5065/D6WW7G29},
+  url={https://github.com/Unidata/MetPy},
+  address={Boulder, Colorado}
+}
+
+@article{verde,
+  title={Verde: Processing and gridding spatial data using Green's functions},
+  doi={10.21105/joss.00957},
+  url={https://doi.org/10.21105/joss.00957},
+  year={2018},
+  month=oct,
+  publisher={The Open Journal},
+  volume={3},
+  number={30},
+  pages={957},
+  author={Leonardo Uieda},
+  journal={Journal of Open Source Software}
+}
+
+@misc{rockhound,
+  doi={10.5281/ZENODO.3086002},
+  url={https://zenodo.org/record/3086002},
+  author={Uieda,  Leonardo and Soler,  Santiago R.},
+  language={en},
+  title={Rockhound: Download geophysical models/datasets and load them in Python},
+  publisher={Zenodo},
+  year={2019}
+}
+
+@misc{icepack,
+  doi = {10.5281/ZENODO.3542092},
+  url = {https://zenodo.org/record/3542092},
+  author = {Shapero,  Daniel and Lilien,  David and Ham,  David A. and Hoffman,  Andrew},
+  title = {icepack/icepack: icepack: glacier flow modeling with the finite element method in Python},
+  publisher = {Zenodo},
+  year = {2019}
+}
+
+@misc{predictatops,
+  doi = {10.5281/ZENODO.1450596},
+  url = {https://zenodo.org/record/1450596},
+  author = {Gosses,  Justin},
+  title = {JustinGOSSES/predictatops: v0.0.4},
+  publisher = {Zenodo},
+  year = {2019}
+}

paper/paper.md

@@ -0,0 +1,158 @@
+---
+title: "Pooch: A friend to fetch your data files"
+tags:
+  - python
+authors:
+  - name: Leonardo Uieda
+    orcid: 0000-0001-6123-9515
+    affiliation: 1
+  - name: Santiago Rubén Soler
+    orcid: 0000-0001-9202-5317
+    affiliation: "2,3"
+  - name: Rémi Rampin
+    orcid: 0000-0002-0524-2282
+    affiliation: 4
+  - name: Hugo van Kemenade
+    orcid: 0000-0001-5715-8632
+    affiliation: 5
+  - name: Matthew Turk
+    orcid: 0000-0002-5294-0198
+    affiliation: 6
+  - name: Daniel Shapero
+    orcid: 0000-0002-3651-0649
+    affiliation: 7
+  - name: Anderson Banihirwe
+    orcid: 0000-0001-6583-571X
+    affiliation: 8
+  - name: John Leeman
+    orcid: 0000-0002-3624-1821
+    affiliation: 9
+affiliations:
+ - name: Department of Earth, Ocean and Ecological Sciences, School of Environmental Sciences, University of Liverpool, UK
+   index: 1
+ - name: Instituto Geofísico Sismológico Volponi, Universidad Nacional de San Juan, Argentina
+   index: 2
+ - name: CONICET, Argentina
+   index: 3
+ - name: New York University, USA
+   index: 4
+ - name: Independent (Non-affiliated)
+   index: 5
+ - name: University of Illinois at Urbana-Champaign, USA
+   index: 6
+ - name: Polar Science Center, University of Washington Applied Physics Lab, USA
+   index: 7
+ - name: The US National Center for Atmospheric Research, USA
+   index: 8
+ - name: Leeman Geophysical, USA
+   index: 9
+date: 02 December 2019
+bibliography: paper.bib
+---
+
+# Summary
+
+Scientific software is usually created to analyze, model, and visualize data.
+As such, many software libraries include sample datasets in their distributions
+for use in documentation, tests, benchmarks, and workshops.
+The usual approach is to include smaller datasets in the GitHub repository
+directly and package them with the source and binary distributions
+(e.g., scikit-learn [@scikit-learn] and scikit-image [@scikit-image] do this).
+Larger datasets require writing code to download the files from a remote server
+to the user's computer.
+The same problem is faced by scientists using version control to manage their
+research projects.
+As data files increase in size, it becomes unfeasible to store them in GitHub
+repositories.
+While downloading a data file over HTTP can be done easily with modern Python
+libraries, it is not trivial to manage a set of files, keep them updated, and
+check for corruption.
+Instead of scientists and library authors recreating the same code, it would be
+best to have a minimalistic and easy to set up tool for fetching and maintaining
+data files.
+
+Pooch is a Python library that fills this gap.
+It manages a data *registry* by downloading files from one or more remote
+servers and storing them in a local data cache.
+Pooch is written in pure Python and has minimal dependencies.
+The integrity of downloads is verified by comparing the file's SHA256 hash with
+the one stored in the data registry.
+This is also the mechanism used to detect if a file needs to be re-downloaded
+due to an update in the registry.
+Pooch is meant to be a drop-in replacement for the custom download code that
+users have already written (or are planning to write).
+In the ideal scenario, the end-user of a software package should not need to know that
+Pooch is being used.
+Setup is as easy as calling a single function (`pooch.create`), including
+setting up an environment variable for overwriting the data cache path and
+versioning the downloads so that multiple versions of the same package can
+coexist in the same machine.
+For example, this is the code required to set up a module
+`datasets.py` that uses Pooch to manage data downloads:
+
+```python
+import pooch
+
+# Get the version string from the project
+from . import version
+
+# Create a new instance of pooch.Pooch
+GOODBOY = pooch.create(
+    # Cache path using the default for the operating system
+    path=pooch.os_cache("myproject"),
+    # Base URL of the remote data server (for example, on GitHub)
+    base_url="https://github.com/me/myproject/raw/{version}/data/",
+    # PEP 440 compliant version number (added to path and base_url)
+    version=version,
+    # An environment variable that overwrites the path
+    env="MYPROJECT_DATA_DIR",
+)
+# Load the registry from a simple text file.
+# Each line has: file_name sha256 [url]
+GOODBOY.load_registry("registry.txt")
+
+def fetch_some_data():
+    # Get the path to the data file in the local cache
+    # If it's not there or needs updating, download it
+    fname = GOODBOY.fetch("some-data.csv")
+    # Load it with NumPy/pandas/xarray/etc.
+    data = pandas.read_csv(fname)
+    return data
+```
+
+Pooch is designed to be extended: users can plug in custom download functions
+and post-download processing functions.
+For example, a custom download function could fetch files from a
+password-protected FTP server (the default is HTTP/HTTPS or anonymous FTP) and
+a processing function could decrypt a file using a user-defined password once
+the download is completed.
+We include ready-made download functions for HTTP and FTP (including basic
+authentication) as well as processing functions for unpacking archives (zip or
+tar) and decompressing files (gzip, lzma, and bzip2).
+
+To the best of the authors' awareness, the only other Python software with some
+overlapping functionality is [Intake](https://github.com/intake/intake).
+While Intake is powerful and can be used to manage large data archives,
+we argue that Pooch has a simpler setup and meets the
+specific needs of scientific software authors and individual scientists.
+For example, Pooch does not require users to change their data loading code to
+fit into a plug-in structure, instead only providing the file path for the
+user.
+
+The Pooch API is stable and has been field-tested by other projects:
+MetPy [@metpy], Verde [@verde], RockHound [@rockhound], predictatops
+[@predictatops], and icepack [@icepack].
+Pooch is also being implemented as the download manager for scikit-image
+([GitHub pull request number 3945](https://github.com/scikit-image/scikit-image/pull/3945)).
+
+
+# Acknowledgements
+
+We would like to thank all of the volunteers who have dedicated their time and
+energy to build the open-source ecosystem on which our work relies.
+The order of authors is based on number of commits to the GitHub repository.
+A full list of all contributors to the project can be found on the
+[GitHub repository](https://github.com/fatiando/pooch/graphs/contributors).
+
+
+# References