/52things

52 Things You Should Know About Geocomputing

52things

52 Things You Should Know About Geocomputing

This is a second attempt at collecting 52 essays about geocomputing. Here's the original call for papers, from a little over 2 years ago. This time we can do it!

Authors, please see Submitting an essay.

Reviewers, please see Reviewing submissions.

Submissions for review

Thing Author Working title Reviewed by
1 Martin Bentley In praise of small tools
2 Martin Bentley Best Practices are not the best...
3 Austin Bingham Domain-driven design in geocomputing
4 Ben Bougher Am = d: a linear algebra approach...
5 Bert Bril Putting colours on data
6 Caumon & Levy Is geology Cartesian?
7 Jesper Dramsch General purpose GPU programming
8 Chris Ennen Software, software everywhere
9 Sergey Fomel Reproducible research
10 GRAM Seismic data encryption
11 Gosses Standing on the shoulders...
12 Dave Hale My favourite 10 line program
13 Matt Hall What's so special about geoscience?
14 Eirik Larsen Crossplots on the boardroom table
15 John Leeman Hardware is hard: teaching geotech
16 Neil McNaughton 'Digitalization,' from Harry Nyquist...
17 Bill Menger The steady advance of Linux
18 Bill Menger Software challenges in oil & gas
19 Matteo Niccoli A fault colourmap prototype
20 Jan Niederau Teaching geoscience students to code
21 Didi Ooi Simple machine learning
22 Steve Purves Learn JavaScript!
23 Michael Pyrcz Open source geostatistical geomodeling
24 Michael Pyrcz Machine learning for geological modeling
25 Alan Richardson Use standard file & problem formats
26 Alberto Rusic I hate computers 1
27 Alberto Rusic I hate computers 2
28 Hassan Sabirin Quality checking spatial data
29 James Selvage Serverless computing
30 Andrew D. Steen Teaching geoscientists to code
31 Martin Storey De profundis: of well depth
32 John Thurmond The tyranny of formats
33 Miguel de la Varga Geological modeling in Python
34 Florian Wellmann A Geological Model is a Hypothesis
35 Adam Cawood et al. Why use virtual outcrop?
36 Dewey Dunnington R, RStudio, and the tidyverse for Geocomputing
37 Andrew Pethick The obsolete geoscientist
38 Matt Hall What is geocomputing? (Blog post)
39 Matteo Niccoli Keep on improving your geocomputing projects
40 Jesse Pisel Arm-wavers Anonymous
41 Robert Leckenby My name is bot, geobot
42 Dewey Dunnington Grammar of graphics
43 Matteo Niccoli Some advice on reproducing figures
44 George Bisbas Getting started in HPC in 3 easy steps
45 Evan Saltman Speeding things up
46 Darren Kondrat Getting started in Geocomputing can seem daunting...
47 Ágoston Sasvári The Phoenix
48 John Howell & Brian Burnham The Virtual Geoscience Revolution Pt. 1
49 John Howell & Brian Burnham The Virtual Geoscience Revolution Pt. 2
50 Tyler Newton Human neural networks in geocomputing
51 Rowan Cockett Building Technical Communication Tools
52 Steve Rogers Advice from a fractured reservoir modeler
53 Chris Dinneen SEGY: Judging books by their covers

Wish list

If you have a topic you wish someone would write about, please add it here:

  • Three ways to get started in geocomputing.
  • Drop everything and learn X (Julia? Clojure? vim?).
  • Only a quantum computer can do geology.
  • Geocomputing at enterprise scale.
  • Open sourcing a corporate software project.
  • Data standards, lol.
  • Geocomputing in the years 2010, 2020, 2030, and 2040.
  • Who are/were the pioneers of digital science?
  • (How) can machines learn physical (or conceptual?) models?
  • Teaching geoscientists to code: Everything Drew Steen said is wrong
  • Thank you for the state-of-the-art processing, I will now proceed to interpret it incorrectly.
  • Units -sigh- let's start using pint (like metpy), astropy, or something.
  • How tech ubiquity is changing geoscientific observation.
  • 5 math concepts for digital geoscientists: probability, linear algebra, machine learning, graph theory, set theory
  • 5 libraries for geophysicists: obspy, madagascar, simpeg, vispy, etc.
  • 5 libraries for geologists: pynoddy, qgis, pygmt, pandas/welly/striplog, etc.
  • Is the subsurface a Graph? (ask the author of noddy/pynoddy)
  • 5 libraries for geobiologists: dplyr, magrittr (maybe), tidyr, vegan, ggplot2
  • Innovative geo-solutions: Your organization fears change, so now what?

Promises, promises

If you want to tell others what you're writing on, or find a co-author!, please add your topic here:

Author Topic or working title
Evan Bianco The art of visualization
Paige Bailey Machine learning opportunities in the geosciences
Brian Burnham A history of virtual outcrops
Matt Hall Upgrade your human technology
Matt Hall Learn some one-liners
Lindsey Heagy Sprint and refactor
Steve Purves Not the floating point
Tom Creech The analog(ue) scientist's best frenemy
Tom Creech + any takers? Geocomputing at enterprise scale