Research Preparation: Difference between revisions

A series of [[research-template|research templates]] will be available for community members to use and edit [[about-research-template|research-template]])

==== Understanding the Topic or Tasks ====

= Clearly define the research topic or tasks to ensure the team is aligned on the goals and deliverables. =

#'' This could involve brainstorming sessions or mind mapping to explore different aspects of the research.

= Confirm the scope of the research and the specific questions or problems that need to be answered (e.g., identifying a company’s center of gravity, understanding a target audience, or analyzing a network for vulnerabilities). =

<span id="identify-the-scope-of-the-research."></span>

==== Identify the scope of the research. ====

= Define the boundaries of the research, including the geographical area, time frame, and specific aspects of the topic that will be covered. =

= Determine the specific objectives of the research, such as identifying key players, understanding behaviors, or forecasting risks. =

= Determine the research’s limitations (constraints and restraints), such as data availability, ethical considerations, or resource constraints. =

= Define the research questions guiding the data collection and analysis process. =

'' '''Type of Data''': Determine whether you need qualitative, quantitative, or a mix of both. This decision will determine your data collection methods.

'' '''Sources of Data''': List potential sources from which data can be retrieved. These might include public databases, surveys, interviews, or experimental data.

 

See the [[rstudio|Rstudio Guide]] for examples of datasets that may be valuable.

'' '''Methods''': Based on the data type needed, choose appropriate collection methods such as surveys, web scraping, direct observation, or experiments.

'' '''Tools''': Identify any software or tools required to collect data. This could be survey platforms, web crawlers, or data logging equipment.

'' '''Ethical Considerations''': Consider any ethical implications of your data collection, especially involving human subjects. You may need to obtain consent or approval from an ethics board.

'' Null Hypothesis: “The content shows no significant signs of being AI-generated.”

'' Alternative Hypothesis: “The content shows significant signs of being AI-generated.” - If your data suggests the null hypothesis is false, you have evidence to support the alternative hypothesis. Typically you would phrase this as “Data indicate that the null hypothesis is rejected in favor of the alternative hypothesis; in other words, #### Research Team Hypotheses Aligning the hypotheses that will guide the research is important when working in a team. This ensures that everyone works towards the same objectives and interprets the data consistently. Brainstorming and discussing the hypotheses as a team can help refine and solidify them. Structured Analytical Techniques (SATs) such as Analysis of Competing Hypotheses (ACH) and Key Assumptions Check (KAC) can be used to evaluate and prioritize hypotheses.

Use Structured Analytic Techniques (SATs) ([[structured-analytic-techniques|SATs wiki page]]) to guide planning, brainstorming, collection, and analysis.

 

'' '''Identifying Indicators''': Decide what themes or patterns you’ll look for in qualitative data and the specific metrics you’ll use in quantitative data.

'' '''Measurement Scale''': Establish whether the data will be nominal, ordinal, interval, or ratio to guide the analytical techniques applied later.

'' '''Pilot Testing''': Conduct a trial run of your data collection methods to identify potential issues and ensure that your data will be reliable and valid.

'' '''Training Data Collectors''': If you’re working with a team to collect data, provide thorough training to minimize errors and ensure consistency in data collection.

'' '''Standardizing Data Entry''': Create a standardized format for data entry to facilitate easier data processing and analysis.

'' '''Data Storage''': Determine how and where data will be securely stored, considering the ethical implications and practical accessibility for analysis.

'' '''Data Processing Procedures''': Outline the steps that will be taken to clean and prepare data for analysis, including how missing data will be handled.

'' '''Version Control''': Implement a version control system for your datasets, especially if multiple team members will be handling the data.

'' '''Communication Channels''': Set up regular meetings and define clear communication protocols to keep the team informed and aligned.

'' '''Role Definition''': Clarify each team member’s role and responsibilities in the data collection and analysis to prevent overlap and ensure coverage of all necessary tasks.

* '''Documentation''': Maintain detailed documentation throughout the data collection and analysis process. This should include a log of data collection activities, any issues encountered, and how they were resolved.

Setting up your device and accounts for research is essential for a few reasons, including privacy and security, but also for obtaining unbiased results that may be skewed based on past searches, current location, associated accounts, and a variety of other metadata. Use the resources below to prepare for research by securing your workstation. ### Virtual Machine for Research Virtual machines are a great way to compartmentalize your research environment and protect your data. They can also create a standardized research environment for a team and maintain a consistent research environment across different devices.

Virtual Machine or containerization improves security and privacy by isolating the research environment from the host system. It also allows for easy replication and sharing of the research environment across different devices.

[[research-virtual-machines|Setting Up a Research Virtual Machine]] ### Virtual Private Network (VPN) for Research Consider also using a VPN to protect your privacy and security while conducting research. A VPN can help prevent your data from being intercepted and bypass geographic restrictions on certain websites and services.

There is a [https://wiki.irregularchat.com/en/community/recommendations/vpn community guide to VPN] services that can help you choose the right VPN for your research needs.

Kasm is a virtual environment that allows you to run a virtual machine in a web browser. This can be useful for running a research environment on a device that does not have the necessary resources to run a virtual machine locally. '''Find the self-hosted version of Kasm [[links|here]]''' ### Pre-Browsing Checks Check to confirm your VM and Browser configuration and VPN. 1. [https://dnsleaktest.com/ DNS / IP Leak Test] - Confirm your location is what you want it to be. 1. [https://coveryourtracks.eff.org/ Cover Your Tracks EEF] - Browser Canvasing Check 1. [https://www.grc.com/cookies/forensics.html Browser Cookie Tester] 1. [https://inappbrowser.com/ InAppBrowser] 1. [https://canyoublockit.com/extreme-test/ AdBlock Test] - Confirm your ad-blocker or DNS is blocking Ads

Full Digital Force Protection Guides [[dfp-guide|here]]