Feel free to post a question about the syllabus to the About the syllabus discussion.
[x] Update your ArcGIS Online (AGOL) profile to include a personalized photo or avatar and your areas of special skills (e.g., "I'm good at data vis", "I'm a StoryMap master", or "I literally know how to use Python").
[x] Includes your preferred name (so we know who you are)
[x] Includes the same profile image you used for your AGOL profile (to help us know it's you)
[x] Choose a focus: programming or analysis (delete the one you don't want).
Programming focus: you already have some experience using Python, so begin your journey by looking at Notebooks, the cloud-based programming environment for solving your geospatial problems
[x] Join the GroupMe chat (email your professor your preferred email for GroupMe)
Like a comment or just say "hi"
[x] Log into AGOL and make sure you are a member of the "AdvGIS - Fall 2021" group
[x] I completed the Ice Breaker challenge on the first day of classes
On GitHub
[x] Familiarize yourself with the Markdown syntax (see resources below)
[x] Introduce yourself to the class with a comment on the Welcome Discussion.
[x] (Wait until you hear from your instructor that it's okay to do this) Create a new issue on our repository's Issues, title it with your name (e.g., Davis's Checklist), copy-and-paste The Master Checklist content to the "Write" section, under Assignees: assign yourself, under Labels: checklist. Be sure to note your issue's unique number.
This is your copy of the master checklist
Use it to keep track of your accomplishments as you go through the semester
You may also see how your peers are progressing to judge your own time management
[x] Create your Report Wiki on our repository's Wiki page
This is where you submit your weekly tasks, goals, and accomplishments
See Home page for instructions
The Consultancy
[x] Find a team (in groups of up to three people) to work together
[x] Video (~20 min or less) that summarizes your article (background, methods, and results + your first impressions)
[ ] Video (~10 min or less) on data collection or creation (w/ map or visual)
[x] Audio/video (~ 5 min or less) on a geoprocess or challenge you faced
[x] Prepare a publicly accessible progress report for your client meeting
It may be your website, slideshow, StoryMap, or another web-accessible document. Make it clear on your website how / where to access it.
Be sure to include visual aids
Remember that your client is not a GIS expert; tone your report for a lay audience
[x] Schedule a progress report meeting with your client here
[x] Write down your thoughts regarding the experience of working through this project and the client meeting in your weekly report
Copy and paste your response here:
I found the client meeting to be very helpful in working through the reproducibility of the project. It forced me to ensure I understood all that we had done before and all we planned to do. This is especially helpful because we are working in a group -- when we split up work, some people can get behind on some aspects of the project and other are very familiar with other aspects. The client meeting ensured we all were familiar with every aspect of the project.
In general working through the project has gone smoothly. There have been some challenges with vagueness and inaccessibility with the paper, but working with a group that has diverse interests and skills has helped.
[x] Rate your paper's level of reproducibility (based on your opinion)
The levels are:
S: satisfactory (methods are clear and reproducible)
M: marginal (it is hard to say because some methods are unclear and/or data are outdated or not readily available)
U: unsatisfactory (there is no known way to reproduce these methods)
Our consultancy gives our paper the rating of M for the following reasons:
The paper provided all necessary layers and was mostly clear about it's steps and the features used and not used in ArcGIS and when coding, but it was not fully accessible in that they used software to create a prediction algorithm. Given that the entire point of the project was to create a prediction algorithm and use it, the reproducibility is largely diminished. Additionally, a few other steps were vague. For example, we thought we were going need to hand draw polygons, but really the authors provided a layer that had hand drawn polygons -- in this case, the wording was confusing.
The Special Works Solutions
Prepare two methodologies for solving one of the special works projects
The special works project should emphasize a skill set that one of the consultants identified as a weakness in the pre-semester survey
Solutions may be typed or recorded
Solution Method 1:
[x] Solved to "basic" level
[x] Solved to "intermediate" level (tick both boxes)
Solution Method 2:
[x] Solved to "basic" level
[x] Solved to "intermediate" level (tick both boxes)
[x] We posted our solutions to our consultancy website
[x] We presented a discussion of our solutions in class or on GitHub
The Novel Datasets
[x] Our consultancy created a novel dataset
[x] in a file geodatabase and/or
[x] in GeoJSON format
[x] We posted a link to our dataset (with a license, description, and relevant metadata) to our consultancy website
[x] We presented a discussion of our dataset (and the methods for its creation) in class or on GitHub
Engagement
[x] Sign up here to schedule to contribute at least once to each of the five weekly topics.
If you are a certificate student, instead sign up for one topic each week.
[x] Question of the week. Date: 11/5
[x] Data share of the week. Date: 10/8
[x] Ethics consideration of the week. Date: 11/26
[x] Vocab term of the week. Date: 10/22
[x] Method of the week. Date: 12/3
[x] Each week, respond to and/or engage with the five weekly discussion posts.
If there is no natural response, then please respond with a reaction to the comment.
[x] I responded to more than five discussion posts on GitHub (4)
[x] I responded to more than ten discussion posts on GitHub
[x] Share a selfie where you are holding or standing next to a physical item within Swem library (e.g., an open book, a painting, or a map) to our GitHub discussion board with a short description of the item and how it relates to a geospatial topic
[x] This includes creating folders and/or updating item names
[x] This includes updating the metadata (summary, description, terms of use, tags, and credits (attribution) appropriately on all shared items (organizationally, publicly or with groups)
[x] I shared a plan on how I organize my AGOL content and/or a system for tagging items in class or on GitHub
Complete at least three (3) hours or six (6) tutorials from one of the following sites: (1) Esri Academy; (2) ArcGIS Developer Guides; (3) Learn ArcGIS; (4) other approved resource (*include names of and links to each tutorial completed)
[x] I grant unrestricted permission to use media (e.g., web content, audio or video) I created for educational purposes
Note that you are not required to tick this box and, at any time, you may request that materials you made for this class be removed from use in past, current, and future classes
Getting Started
On GitHub
The Consultancy
The Reproducibility Project and Client Meeting
I found the client meeting to be very helpful in working through the reproducibility of the project. It forced me to ensure I understood all that we had done before and all we planned to do. This is especially helpful because we are working in a group -- when we split up work, some people can get behind on some aspects of the project and other are very familiar with other aspects. The client meeting ensured we all were familiar with every aspect of the project. In general working through the project has gone smoothly. There have been some challenges with vagueness and inaccessibility with the paper, but working with a group that has diverse interests and skills has helped.
The paper provided all necessary layers and was mostly clear about it's steps and the features used and not used in ArcGIS and when coding, but it was not fully accessible in that they used software to create a prediction algorithm. Given that the entire point of the project was to create a prediction algorithm and use it, the reproducibility is largely diminished. Additionally, a few other steps were vague. For example, we thought we were going need to hand draw polygons, but really the authors provided a layer that had hand drawn polygons -- in this case, the wording was confusing.
The Special Works Solutions
The Novel Datasets
Engagement
Become More Geoethical
Managing Your Data
Getting Started With Notebooks
Additional Practice
Complete at least three (3) hours or six (6) tutorials from one of the following sites: (1) Esri Academy; (2) ArcGIS Developer Guides; (3) Learn ArcGIS; (4) other approved resource (*include names of and links to each tutorial completed)
Final Touches