GemGIS - Spatial Data Processing for Geomodeling

[AlexanderJuestel]

Submitting Author: Name (@AlexanderJuestel)
All current maintainers: (@AlexanderJuestel)
Package Name: GemGIS
One-Line Description of Package: Spatial Data Processing for Geomodeling
Repository Link: https://github.com/cgre-aachen/gemgis
Version submitted: 1.0.11 (soon 1.1 with bug fixes for some methods and the API Reference once it is working, no major functionality changes)
Documentation: https://gemgis.readthedocs.io/en/latest/
JOSS Publication: https://joss.theoj.org/papers/10.21105/joss.03709
JOSE Publication: https://jose.theoj.org/papers/10.21105/jose.00185
Editor: @yeelauren
Reviewer 1: @aleksandraradecka1
Reviewer 2: @martinfleis
Reviewer 3: @SimonMolinsky
Archive: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

---

Code of Conduct & Commitment to Maintain Package

• I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package after should it be accepted.
• I have read and will commit to package maintenance after the review as per the pyOpenSci Policies Guidelines.

Description

GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model building process. Postprocessing of model results will allow export from GemPy to geoinformation systems such as QGIS and ArcGIS or to Google Earth for further use.

GemGIS uses and combines the full functionality of GeoPandas, rasterio, OWSLib, Pandas, Shapely, PyVista and NumPy to simplify, accelerate and automate the workflows used to preprocess spatial data for geomodeling.

From https://gemgis.readthedocs.io/en/latest/

In addition, almost 70 tutorials illustrate the different functionalities of GemGIS.

Scope

• Please indicate which category or categories.
  Check out our package scope page to learn more about our
  scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization¹
  • Workflow automation
  • Citation management and bibliometrics
  • Scientific software wrappers
  • Database interoperability

Domain Specific & Community Partnerships

- [x] Geospatial
- [x] Education
- [ ] Pangeo

Community Partnerships

If your package is associated with an
existing community please check below:

• Pangeo
  • My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook

• For all submissions, explain how the and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):

Data extraction/processing: GemGIS uses the functionality of packages like GeoPandas, Shapely, or Rasterio to extract information from vector and raster data and to put it in a form that it can be used by the GemPy.

Data visualization: GemGIS uses the functionality of packages like matplotlib or PyVista to create static and dynamic plots of data and meshes. This includes digital elevation models or meshes of subsurfaces layers, boreholes geological cross sections or even seismic data.

Workflow automation: The entire purpose of GemGIS is to provide methods to accelerate the preparation of input data for GemPy. Over time, the package has also gained additional functionality to work with a variety of datasets utilized for subsurface applications, see Tutorials.

• Who is the target audience and what are scientific applications of this package?

The target audience is the open-source Geosciences community, researchers, students but also industry. GemGIS provides functionality to accelerate the preparation of input data for the structural geological modeling package GemPy which has been used in numerous publications. For applications at universities, we are in the final stages of getting a JOSE publication approved with more than 20 structural geological models that are used at RWTH Aachen University for teaching purposes and where GemGIS and GemPy will be included in future courses.

• Are there other Python packages that accomplish the same thing? If so, how does yours differ?

GemGIS does not reinvent the wheel but rather combines the functionality of already existing packages mentioned in the description above. The packages utilized the most in GemGIS are the well-known packages like GeoPandas, Shapely, Rasterio, Pandas, NumPy, PyVista, matplotlib, etc. We also decided against i.e. wrapping GeoPandas GeoDataFrames in our own class or creating many new classes so that users can still use the full functionality of the underlying packages. This is one big advantage in comparison to GemPy where i.e. the meshes of the resulting structural geological models cannot be extracted (GemGIS is capable of extracting them though). Another example is that raster data opened with GemGIS will be stored as PyVista PolyData datasets or as grids so that users can harvest the functionality of this amazing package.

• If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

Pre-submission inquiry: #126, @NickleDave

Technical checks

For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:

• does not violate the Terms of Service of any service it interacts with.
• uses an OSI approved license.
• contains a README with instructions for installing the development version. --> was added in cgre-aachen/gemgis@b5f71e3
• includes documentation with examples for all functions. --> will be checked once it is working again
• contains a tutorial with examples of its essential functions and uses.
• has a test suite.
• has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

Publication Options

• Do you wish to automatically submit to the Journal of Open Source Software? No, JOSS publication already existing: https://joss.theoj.org/papers/10.21105/joss.03709

JOSS Checks

• The package has an obvious research application according to JOSS's definition in their submission requirements. Be aware that completing the pyOpenSci review process does not guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
• The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
• The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
• The package is deposited in a long-term repository with the DOI:

Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.

Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?

This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.

• Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.

Confirm each of the following by checking the box.

• I have read the author guide.
• I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

Please fill out our survey

• Last but not least please fill out our pre-review survey. This helps us track
  submission and improve our peer review process. We will also ask our reviewers
  and editors to fill this out.

P.S. Have feedback/comments about our review process? Leave a comment here

Editor and Review Templates

The editor template can be found here.

The review template can be found here.

Footnotes

1. Please fill out a pre-submission inquiry before submitting a data visualization package. ↩

[AlexanderJuestel]

Hello,
There are two bullets that I still need to check, I am further open to make updates to the package to meet minimal criteria before review (Section 5 of the Maintainer Guide) if there is still anything missing.

[NickleDave]

Thank you @AlexanderJuestel for opening this and for linking back to #126.

I have gone ahead and started looking for an editor for this review.

Please do let us know when you get the API docs up, and then I will proceed with the initial checks we do before starting review.

[AlexanderJuestel]

@NickleDave, I have created a question on Stackoverflow (https://stackoverflow.com/questions/76883029/api-reference-building-locally-but-not-on-rtd) and I am trying one last thing and hope to make it work!

[NickleDave]

Not sure if I spotted the issue but I replied there: https://stackoverflow.com/a/76908429/4906855

You can also feel free to ask for help in our Discourse in the future (https://pyopensci.discourse.group/) (or now, if I haven't helped 😅)

[AlexanderJuestel]

@NickleDave I am trying your solution right now!

[AlexanderJuestel]

@NickleDave You solution did not work, unfortunately. I am only using two methods now to get a mini API Reference running but it also fails because a module, that is not even needed is missing. The only place this module appears is the __init__.py file. So maybe there is a link missing to this file? I do not know anymore...

I also opened a new topic on your Discourse! I hope someone has an idea!

[NickleDave]

Hi @AlexanderJuestel just checking back. I think we do have an editor that can run this review.

I know we were helping you with the API docs build but I'm a little out of the loop on where we left off. Could you give me a rough estimate of when you might have a chance to get to that? I don't mean to rush you--I'm sure you have other obligations as well; I just don't want to lose track of this review.

My guess is that, if possible, switching to a pyproject.toml that includes your dependencies, and then using pure Python virtual environments on readthedocs, might make the build easier. But it's possible I'm missing the real issue.

[AlexanderJuestel]

@NickleDave, thanks for checking in. I have to get back to @lwasser on Discourse still. It has been a little hectic here. I try to get back to her in the next few days!

[NickleDave]

Very understood, thank you @AlexanderJuestel.
I do not mean to rush you.
I think Leah is out of town right now but should be back on-line next week.
Early next week I will see if I can troubleshoot for you a little.