Judging Criteria

This page provides information about Go Code Colorado 2020 which was canceled due to concerns about the spread of COVID-19. Check back early 2021 for information about the next Go Code Colorado.

GO CODE COLORADO JUDGING CRITERIA

 

The Challenge is sponsored by Go Code Colorado, the Colorado Secretary of the State, and the State of Colorado, 1700 Broadway Suite 200, Denver CO 80290, gocode.colorado.gov.

Judging Overview

This Go Code Colorado judging criteria is to be used by Go Code Colorado Judges  in choosing the winners of the challenge. Judges will score submissions based on the categories explained in detail here and will only score submissions that adhere to all Go Code Colorado Rules.

Semi-Final and Final judging will be based on material provided in each team’s GitHub repository in the Go Code Colorado GitHub Organization,  material covered during team presentations, and information provided in the submission forms. Scoring will be a weighted composite of the 5 factors shown in tables below.

The Business Application Track and Business Analytics Track are scored differently, according to the criteria outlined below.

 

Business Application Track Scoring Criteria


Overall Score

Total Points AvailableApplication CategoryApplication Category Description
40DataAdding value up the scale of data use: increasing accessibility, combination, analysis.
20QualityThe market ready tool is an MVP: functional, logical, sustainable, scale-able, and has a well designed user experience.
20InnovationThe originality of the application’s ability to solve a business problem or produce beneficial insights.
10ImplementationEffectiveness of the market ready tool in aiding the business in gathering information from the data.
10PresentationClear, concise, and engaging conveyance of the problem and how the product helps the business to their solution.
Total: 100

The Data and Quality components are scored according to the sub-categories explained below.


Data Score Breakdown

Sub CategoryDescriptionPoints Awarded
Data InnovationYou add value through both connecting discrete data sets and analyzing the combined data to create new insights that you deliver to a business decision-maker to help with a decision-making process.16
You add value by analyzing public data and creating new insights that you deliver to a business decision-maker to help with a decision-making process.12
You add value by connecting discrete data sets. You process and deliver public data to a business decision-maker with a relational connection so that it is useful for a business decision-making process.8
You add value by providing accessibility. The app delivers public data to a business decision-maker in a meaningful way so that it is useful for a business decision-making process.4
No value added to the data.0
Data IntegrationThe data is clearly visible in the code via API or platform/database integration and functions properly.8
The data is integrated, but not well defined or documented; data generally works as expected.4
Data not integrated into app or used for analysis.0
Data PresentationThe product displays the data (or data aggregation) in a clear and efficient format.8
The data presentation is unclear or confusing4
There is no clear use of data0
Data DocumentationA data diagram/documentation is provided that makes the data use clear8
The usage of data is visible but is unclear or poorly documented4
There is no clear use of data either via code or documentation0


Quality Score

Sub CategoryDescriptionPoints Awarded
User ExperienceThe product has no working defects and is user friendly, and the experience is interactive and displays dynamic data.6
The product is built to a working product standard, can be navigated, but has some bugs. Data experience is interactive and displays dynamic data.4
The product is difficult to navigate or hard to understand. Data experience is minimal2
The product is not functioning or available on any test or live server, app store or embedded on a website. No data displayed.0
SustainabilityProduct is built on software or platform with active support and requires no manual updates. Examples: Angular 1 vs 2 or NodeJS 0.10 vs LTS. Product is designed for scale-ability.6
Product is built on software/platform/libraries with active support and requires minimal manual updates. Product may not be easily scaled.4
Product is built on software or platform that has been forked/modified from supported/original source. Scaling project would require extensive overhaul of product.2
Product corrupted without frequent maintenance, and/or code is not properly licensed. Not scale-able.0
FunctionalityThe product is completely functional and responds correctly under all functional tests producing the correct responses and the data is represented correctly.4
The product is mostly functional and responds correctly under all functional tests producing the correct responses and the data is represented correctly with acceptable obfuscation.3
The product is marginally functional with numerous errors. The product may respond correctly under certain circumstances, but there are significant errors, incomplete code sections, or the data representation is obfuscated.2
The product is minimally functional with significant portions of the code missing or incomplete. The product is largely non-responsive to most functional tests, and the data representation is clearly incorrect or otherwise distorted.1
The product is not functional, meeting no significant design specifications, and/or the interface does not display data.0
Logical Structure and DocumentationDocumentation and code are extremely well organized, properly formatted, without spelling/grammar errors and related code sections are logically grouped. Data is optimally stored, has a well documented schema and Data Architecture Diagram.4
Documentation and code are easy to follow with logical groupings of related code, but minor formatting problems. Data stored in web server/file system, Data Architecture Diagram. Or inversely, data is optimally stored but no documentation.3
Documentation and code are readable only with significant effort, and there is little to no formatting and/or significant problems with its organization. Data updates are manual, and. Data Architecture Diagram is poorly documented.2
Documentation and code are poorly organized and difficult to read without consistency in formatting and logical code grouping. Data setup logic is unclear, and no Data Architecture Diagram.1
Documentation and code are readable only by someone extremely knowledgeable with its layout and purpose. No data use.0


Innovation Score

DescriptionPoints Awarded
A new and different way has been created that provides businesses with resources through a tool that helps them improve themselves, their community, or their environment.20
A better way to provide businesses with resources has been created that helps businesses improve themselves, their community, or their environment.10
The product created is not new and does not improve businesses.0


Implementation Score

DescriptionPoints Awarded
The product is highly effective in facilitating a business in gathering insights from data.10
The product is moderately effective in facilitating a business in gathering insights from data.5
The product does not effectively facilitate businesses in gathering insights from data0


Presentation Score

DescriptionPoints Awarded
Clear, concise, and engaging conveyance of the product and how it helps the business to find solutions.10
Product is presented, but with moderate clearness and conciseness in a moderately engaging manner.5
No presentation0

 

Business Analytics Track Scoring Criteria


Overall Score

Total Points AvailableAnalytics CategoryAnalytics Category Description
40DataAdding value through effective storytelling, combination, appropriate analysis, and actionable output.
20QualityThe analysis is accurate, repeatable, and produces a degree of confidence in the information provided.
20RelevanceHow useful the analysis result is to the business’s problem.
10Data StoryAbility to clearly identify the business's issue and provide information from an analysis as a solution to that issue.
10PresentationClear, concise, and engaging conveyance of the business's identified problem and resulting solution
Total: 100

The Data and Quality components are scored according to the sub-categories explained below.


Data Score Breakdown

Sub CategoryDescriptionPoints Awarded
Data StorytellingYour data story clearly defines the problem and how your analysis solves the problem.16
Your data story has an undefined problem, but the analysis shows interesting and useful results.12
Your data story clearly defines the problem and but is unclear on how your analysis solves the problem.8
Your data story has an undefined problem, and the analysis results are not relevant.4
Your data story has no clear problem definition or there is no analysis.0
Data CombinationsThree or more datasets were combined in meaningful ways to add value to the analysis, and a data architecture diagram is provided that is accurate.12
Two or less datasets were combined in meaningful ways to add value to the analysis, and a data architecture diagram is provided that is accurate.8
It seems there were datasets combined, but there is no documentation or data architecture diagram4
There are no data combinations.0
Data Analysis ValueThe analysis is diagnostic, descriptive, predictive, and prescriptive.12
In addition to being descriptive or diagnostic, the analysis is also prescriptive or predictive.8
The analysis is purely descriptive or diagnostic.4
There is no novelty to the analysis, the data is presented in its raw form.0


Quality Score Breakdown

Sub CategoryDescriptionPoints Awarded
Data Method AccuracyThe analysis has a statistically acceptable p value (or related metric) with highly accurate and clear results.6
The analysis has a statistically acceptable p value (or related metric) and results are accurate but unclear.4
The analysis has an unacceptable p value (or related method), but the results are useful and informative.2
The analysis has an unacceptable p value or is otherwise not well executed.0
Data Method ConfidenceThe analysis has high confidence in being relevant and useful to a business decision maker.6
The analysis has confidence in being relevant and useful to a business decision maker.4
The analysis has low confidence in being relevant to a business decision maker.2
The analysis has no confidence in being relevant and useful to a business decision maker.0
Repeatability of AnalysisThe analysis is fully repeatable.4
Some parts of the analysis are repeatable.2
The analysis is not repeatable.0
DocumentationThe analysis is documented thoroughly and clearly and the documentation is publicly accessible, with Data Architecture Diagram easily discoverable from README file.4
The analysis is documented with Data Architecture Diagram, but could be more thorough/accessible.2
The analysis is not documented.0


Relevance Score

DescriptionPoints Awarded
A new and insightful analysis that provides businesses valuable information to improve themselves, their community, or their environment.20
An insightful analysis that provides businesses valuable information to improve themselves, their community, or their environment.10
The analysis is not new and does not allow businesses to improve themselves, their community, or their environment.0


Data Story Score

DescriptionPoints Awarded
The analysis clearly identifies an area of improvement for a business and provides an effective solution.10
The analysis identifies an area of improvement for a business and provides a solution.5
The analysis does not identify an area of improvement for a business and does not provide a solution.0


Presentation Score

DescriptionPoints Awarded
Clear, concise, and engaging conveyance of the analysis' identified problem and resulting solution.10
Analysis is presented with moderate clearness and conciseness in a moderately engaging manner.5
No presentation0

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