Research Preparation: Difference between revisions

From Irregularpedia
Jump to navigation Jump to search
Newer edit →
VisualWikitext
Initial
 
format and categories
Tag: wikieditor
Line 5: Line 5:
== Plan for Research ==
== Plan for Research ==


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


<span id="understanding-the-topic-or-tasks"></span>
<span id="understanding-the-topic-or-tasks"></span>
==== Understanding the Topic or Tasks ====
=== Understanding the Topic or Tasks ===


= Clearly define the research topic or tasks to ensure the team is aligned on the goals and deliverables. =
# Clearly define the research topic or tasks to ensure the team is aligned on goals and deliverables.
#'' This could involve brainstorming sessions or mind mapping to explore different aspects of the research.
# 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). =
# 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>
<span id="identify-the-scope-of-the-research"></span>
==== Identify the scope of the research. ====
=== 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. =
# Define the boundaries of the research, including geographical area, time frame, and specific aspects of the topic to be covered.
= Determine the specific objectives of the research, such as identifying key players, understanding behaviors, or forecasting risks. =
# Determine specific objectives 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. =
# Identify research limitations like data availability, ethical considerations, or resource constraints.
= Define the research questions guiding the data collection and analysis process. =
# Define the research questions guiding the data collection and analysis process.


<span id="identifying-necessary-data"></span>
<span id="identifying-necessary-data"></span>
=== Identifying Necessary Data ===
=== Identifying Necessary Data ===


'' '''Type of Data''': Determine whether you need qualitative, quantitative, or a mix of both. This decision will determine your data collection methods.
* '''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 from which data can be retrieved. These might include public databases, surveys, interviews, or experimental data.
* '''Sources of Data''': List potential sources like public databases, surveys, interviews, or experimental data.
 
** See the [[rstudio|RStudio Guide]] for valuable datasets.
See the [[rstudio|Rstudio Guide]] for examples of datasets that may be valuable.


<span id="developing-a-collection-strategy"></span>
<span id="developing-a-collection-strategy"></span>
=== Developing a Collection Strategy ===
=== Developing a Collection Strategy ===


'' '''Methods''': Based on the data type needed, choose appropriate collection methods such as surveys, web scraping, direct observation, or experiments.
* '''Methods''': Choose appropriate data collection methods like 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.
* '''Tools''': Identify any software or tools required for collection, such as survey platforms 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.
* '''Ethical Considerations''': Address ethical implications, especially for human subjects, ensuring consent or ethics board approval if needed.


<span id="formulating-hypotheses"></span>
<span id="formulating-hypotheses"></span>
=== Formulating Hypotheses ===
=== Formulating Hypotheses ===


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


Use Structured Analytic Techniques (SATs) ([[structured-analytic-techniques|SATs wiki page]]) to guide planning, brainstorming, collection, and analysis.
Structured Analytical Techniques (SATs), such as Analysis of Competing Hypotheses (ACH) and Key Assumptions Check (KAC), are helpful for refining hypotheses. Use the [[structured-analytic-techniques|SATs wiki page]] to guide planning, brainstorming, data collection, and analysis.


<span id="prepare-for-research"></span>
<span id="prepare-for-research"></span>
Line 51: Line 50:
=== Operationalizing Variables ===
=== Operationalizing Variables ===


Before collecting data, clearly define how each variable will be measured. This includes:
* '''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.
'' '''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.


<span id="ensuring-data-quality"></span>
<span id="ensuring-data-quality"></span>
=== Ensuring Data Quality ===
=== Ensuring Data Quality ===


'' '''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.
* '''Pilot Testing''': Conduct trial runs to ensure reliability and validity of data collection methods.
'' '''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.
* '''Training Data Collectors''': Train team members to minimize errors and ensure consistency.
'' '''Standardizing Data Entry''': Create a standardized format for data entry to facilitate easier data processing and analysis.
* '''Standardizing Data Entry''': Create a standardized format for data entry to streamline processing and analysis.


<span id="data-management-plan"></span>
<span id="data-management-plan"></span>
=== Data Management Plan ===
=== Data Management Plan ===


'' '''Data Storage''': Determine how and where data will be securely stored, considering the ethical implications and practical accessibility for analysis.
* '''Data Storage''': Establish secure storage solutions that are accessible for analysis while respecting ethical considerations.
'' '''Data Processing Procedures''': Outline the steps that will be taken to clean and prepare data for analysis, including how missing data will be handled.
* '''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 your datasets, especially if multiple team members will be handling the data.
* '''Version Control''': Implement a version control system for datasets to manage updates and collaboration.


<span id="team-collaboration"></span>
<span id="team-collaboration"></span>
=== Team Collaboration ===
=== Team Collaboration ===


'' '''Communication Channels''': Set up regular meetings and define clear communication protocols to keep the team informed and aligned.
* '''Communication Channels''': Set up regular meetings and communication protocols to keep the team informed.
'' '''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.
* '''Role Definition''': Clarify roles and responsibilities in data collection and analysis.
* '''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.
* '''Documentation''': Maintain detailed records of data collection, issues, and resolutions.


<span id="preparing-systems-and-devices-for-research"></span>
<span id="preparing-systems-and-devices-for-research"></span>
=== Preparing Systems and Devices for Research ===
=== Preparing Systems and Devices for Research ===


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.
Setting up devices and accounts for research is important for privacy, security, and obtaining unbiased results. Use the following resources to secure your workstation.
 
<span id="virtual-machine-for-research"></span>
==== Virtual Machine for Research ====


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.
Virtual Machines or containerization improve security and privacy by isolating the research environment from the host system. See [[research-virtual-machines|Setting Up a Research Virtual Machine]] for more details.


[[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.
<span id="vpn-for-research"></span>
==== Virtual Private Network (VPN) for Research ====


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.
A VPN can protect privacy while conducting research and help bypass geographic restrictions on websites. Check the [https://wiki.irregularchat.com/en/community/recommendations/vpn community VPN guide] to choose the right VPN for your research.


<span id="kasm-virtual-environment"></span>
<span id="kasm-virtual-environment"></span>
=== Kasm Virtual Environment ===
=== Kasm Virtual Environment ===


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
Kasm allows you to run a virtual machine in a web browser, useful for research on devices without local resources. Find the self-hosted version of Kasm [[links|here]].
 
<span id="pre-browsing-checks"></span>
=== Pre-Browsing Checks ===
 
Run the following checks before browsing to ensure privacy and security:
1. [https://dnsleaktest.com/ DNS / IP Leak Test] - Confirm your location.
2. [https://coveryourtracks.eff.org/ Cover Your Tracks EFF] - Browser canvas check.
3. [https://www.grc.com/cookies/forensics.html Browser Cookie Tester]
4. [https://inappbrowser.com/ InAppBrowser]
5. [https://canyoublockit.com/extreme-test/ AdBlock Test] - Ensure ads are blocked.
 
For more detailed guidance, see the full [[dfp-guide|Digital Force Protection Guide]].


Full Digital Force Protection Guides [[dfp-guide|here]]
[[Category:Research]]
[[Category:Planning]]
[[Category:Data Collection]]
[[Category:Team Collaboration]]

Revision as of 02:57, 24 September 2024

Plan and Prepare for Research

Plan for Research

A series of research templates will be available for community members to use and edit. For more, see research-template.

Understanding the Topic or Tasks

  1. Clearly define the research topic or tasks to ensure the team is aligned on goals and deliverables.
  2. This could involve brainstorming sessions or mind mapping to explore different aspects of the research.
  3. 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

  1. Define the boundaries of the research, including geographical area, time frame, and specific aspects of the topic to be covered.
  2. Determine specific objectives such as identifying key players, understanding behaviors, or forecasting risks.
  3. Identify research limitations like data availability, ethical considerations, or resource constraints.
  4. Define the research questions guiding the data collection and analysis process.

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.

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 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

  • 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), are helpful for refining hypotheses. Use the SATs wiki page to guide planning, brainstorming, data collection, and analysis.

Prepare for Research

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

  • Pilot Testing: Conduct trial runs to ensure 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

  • Data Storage: Establish secure storage solutions that are 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

  • 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

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

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

Virtual Private Network (VPN) for Research

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

Kasm Virtual Environment

Kasm allows you to run a virtual machine in a web browser, useful for research on devices without local resources. Find the self-hosted version of Kasm here.

Pre-Browsing Checks

Run the following checks before browsing to ensure privacy and security: 1. DNS / IP Leak Test - Confirm your location. 2. Cover Your Tracks EFF - Browser canvas check. 3. Browser Cookie Tester 4. InAppBrowser 5. AdBlock Test - Ensure ads are blocked.

For more detailed guidance, see the full Digital Force Protection Guide.

Retrieved from "https://irregularpedia.org/index.php?title=Research_Preparation&oldid=642"