AI Open Network Research Project Example

Project Title Here (i.e: Social media botnet detection and analysis)

• Tagline: (i.e: Analyze political botnet activity on Twitter and develop effective counter-measures)
• Date: (Date the research opened, i.e: October 2016)
• Category: [Applied Research, Fundamental Research]
• Contact(s): researcher(s) @example.com

Project Status:

• Explain what stage the project is at as of now, in few points:

  • Brainstorming Phase: disucssing approaches to tackle part 1/2/3.. of the problem.

  • Baseline model is built, here are results:

    	Accuracy	Loss	Time	Data
    Model Name - Author X	2.xxx	70	1hr	20 datapoints
    Model Two - Author Y	89.xxx	3	2wks	50k datapoints

Community Links:

• Mailing list: (By the authors ideally)
• Slack/Gitter Channel Links

Problem description:

Explain the goal outcome here in few sentences.

Why this problem matters:

This is a more in depth explanation into the problem from the previous section:

• Some downfalls without this research existing.
• Current approaches into how this task is being accomplished: [manually, ml-linear models, not have been attempted]
• Getting a little technical here wouldn't be bad perhaps, (technical in terms of the project suggested approach).

Essentially, this can be a convincing point for other researchers with common interest to join.

How to measure success:

• Given the dataset and disucssed approaches, what could be a good measure of good result.
• Or perhaps include benchmarks to compare against and improve up-on.

Datasets:

The more data resources, the better!

Please include information about the nature of the data (if possible): For example:

• Company A, API: (Limit on 100 calls per minute) Link to the API documentation

• Open Dataset: (10 Gb), Link to a paper about the dataset (if possible). if not, then some project that uses the dataset.

• Another suggested format by Megan Risdal:

  • The context: How was the data collected and why?
  • Contents: What fields are in your data? What are their units of measurement? Are there missing values or other recording flaws?
  • Goals: What are the objectives of this dataset is introduced for?
  • Acknowledgments: Who do you owe thanks for sharing this dataset? Provide details on the datasets’s provenance. This is not only important in collaborative social data science, but may also be a part of respecting the dataset owner’s license.

Examples:

• Iris Dataset information given on the page.
• Twitter API.

Extracting Data - Preprocessing details:

If applicable, point to scripts that:

• Fetches the data for train/test.
• Performs preprocessing to the given approaches towards the project. (i.e: Tokenization, Word Embedding, RGB Image Reshaping)

Relevant Work:

This will be one of the main key places for other researchers to contribute to during the project lifetime.

• Papers that tackle either:
  • this same research goal.
  • that uses approaches to other problems outside the scope of this research, however, insightful and relevant in building the architecture of this research's model.

Contribute:

Few things to have in here:

• Provide a starting point readme file and status of the current project for new researchers. These projects can take months if not longer sometimes to complete, such information will help onboarding faster.
• Guideline on how to edit-add new resources to this project, if there is a specific requirement, mention them. i.e:
  • Please create a branch and do a pull-request when adding to this example project.
  • Open Issues if something is not clear in the readme, or found linguistic/ grammar mistakes.

References Used To Write This Guide:

• Megan Risdal. A Guide to Open Data Publishing & Analytics
• Shawn Anderson, Social Media Bot Detection

PS: Last few notes:

• Be Nice & Be Respectful.
• Value other people's work, please reference them. Don't just copy & paste what you find elsewhere when it comes to sharing information.
• Give constructive criticism, as in if you see something not working, or wrong, suggest an attempt to tackle resolving the issue.
• Please Ask Questions: This is one big attempt to open up opportunity for everyone being able to contribute, if they can add value towards these research topics.
• Also, keep in mind that most of the researchers that are opening these projects might have full-time work/research. If there is a specific question, try opening an issue, use the given open communication channels rather than direct contact.