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Research Preparation

Research Preparation

Section titled “Research Preparation”

Plan and Prepare for Research

Section titled “Plan and Prepare for Research”

Plan for Research

Section titled “Plan for Research”

templates are available for community members to use and edit.

Understanding the Topic or Tasks

Section titled “Understanding the Topic or Tasks”
  • Define the research topic - Clearly define the research topic or tasks to ensure the team is aligned on goals and deliverables.
  • Brainstorm approaches - Use brainstorming sessions or mind mapping to explore different aspects of the research.
  • Confirm scope - 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).

Identify the Scope of the Research

Section titled “Identify the Scope of the Research”
  • Define boundaries - Define the boundaries of the research, including geographical area, time frame, and specific aspects of the topic to be covered.
  • Determine objectives - Determine specific objectives such as identifying key players, understanding behaviors, or forecasting risks.
  • Identify limitations - Identify research limitations like data availability, ethical considerations, or resource constraints.
  • Define research questions - Define the research questions guiding the data collection and analysis process.

Identifying Necessary Data

Section titled “Identifying Necessary Data”

  • Type of Data: Determine whether qualitative, quantitative, or a mix of both is needed. This decision will influence data collection methods.

  • Sources of Data: List potential sources like public databases, surveys, interviews, or experimental data.

    • See the Guide for valuable datasets.

Developing a Collection Strategy

Section titled “Developing a Collection Strategy”

  • Methods: Choose appropriate data collection methods like surveys, web scraping, direct observation, or experiments.

  • Tools: Identify any software or tools required for the collection, such as survey platforms or data logging equipment.

  • Ethical Considerations: Address ethical implications, especially for human subjects, ensuring consent or ethics board approval if needed.

Formulating Hypotheses

Section titled “Formulating Hypotheses”

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

  • Alternative Hypothesis: “The content shows significant signs of being AI-generated.”

Structured Analytical Techniques (SATs), such as Analysis of Competing Hypotheses (ACH) and Key Assumptions Check (KAC), help refine hypotheses. Use the SATs wiki page to guide planning, brainstorming, data collection, and analysis.

Prepare for Research

Section titled “Prepare for Research”

Operationalizing Variables

Section titled “Operationalizing Variables”

  • Identifying Indicators: Decide on themes or patterns to look for in qualitative data and specific metrics for quantitative data.

  • Measurement Scale: Establish if data is nominal, ordinal, interval, or ratio to guide the analysis.

Ensuring Data Quality

Section titled “Ensuring Data Quality”

  • Pilot Testing: Conduct trial runs to ensure the reliability and validity of data collection methods.

  • Training Data Collectors: Train team members to minimize errors and ensure consistency.

  • Standardizing Data Entry: Create a standardized format for data entry to streamline processing and analysis.

Data Management Plan

Section titled “Data Management Plan”

  • Data Storage: Establish secure storage solutions accessible for analysis while respecting ethical considerations.

  • Data Processing Procedures: Define how data will be cleaned and prepared for analysis, including how to handle missing data.

  • Version Control: Implement a version control system for datasets to manage updates and collaboration.

Team Collaboration

Section titled “Team Collaboration”

  • Communication Channels: Set up regular meetings and communication protocols to keep the team informed.

  • Role Definition: Clarify roles and responsibilities in data collection and analysis.

  • Documentation: Maintain detailed records of data collection, issues, and resolutions.

Preparing Systems and Devices for Research

Section titled “Preparing Systems and Devices for Research”

Setting up devices and accounts for research is important for privacy, security, and obtaining unbiased results. Use the following resources to secure your workstation.

Virtual Machine for Research

Section titled “Virtual Machine for Research”

Virtual Machines or containerization improve security and privacy by isolating the research environment from the host system. See Up a Research Virtual Machine for more details.

Virtual Private Network (VPN) for Research

Section titled “Virtual Private Network (VPN) for Research”

A VPN can protect privacy while researching and help bypass website geographic restrictions. Check the community VPN guide to choose the right VPN for your research.

Kasm Virtual Environment

Section titled “Kasm Virtual Environment”

Kasm Workspaces allows you to run isolated browser sessions in a web browser, useful for research on devices without local resources. Kasm provides containerized desktops and browsers that can be spun up on-demand.

Pre-Browsing Checks

Section titled “Pre-Browsing Checks”

Run the following checks before browsing to ensure privacy and security:

  1. DNS Leak Test - Confirm your DNS is not leaking your location
  2. Cover Your Tracks (EFF) - Check browser fingerprinting and tracking protection
  3. Browser Cookie Tester - Test cookie behavior
  4. InAppBrowser - Check if in-app browsers inject JavaScript
  5. AdBlock Test - Verify ad blocking is working

See the full Digital Force Protection Guide for more detailed guidance.