Research Tasks

The intention is to identify fundamental tasks required for operational or broad research. Identifying each task and performance step will allow adjustments based on experience and changes to data and platforms.

The verbs used are from Bloom’s Taxonomy: https://www.utica.edu/academic/Assessment/new/Blooms Taxonomy - Best.pdf

Plan for Research

Devise Operational Research Strategies

• Identify Objectives: Clearly define what the research aims to achieve =

• Gather Requirements: Enumerate the data and resources required to meet the research objectives. =

• Assess Availability: Confirm the accessibility of required proprietary and open-source resources for operational research. =

• Develop Strategy: Outline a comprehensive plan detailing efficiently utilizing proprietary and open-source resources. =

• Schedule Implementation: Set a timeline for the execution of the research strategy. =

• Review Protocols: Ensure all plans comply with security protocols related to proprietary and open-source access and usage. =

• Obtain Approvals: Secure necessary authorizations from oversight entities to proceed with the plan. =

Formulate Research Questions Based on Intelligence Leads

• Review Intelligence Leads: Analyze available intelligence to uncover information gaps or areas requiring further investigation. =

• Brainstorm Questions: Generate a list of potential questions that, if answered, would provide valuable insights. =

• Prioritize Questions: Rank the questions based on their relevance and the potential impact of the answers. =

• Refine Questions: Refine each question to be clear, concise, and answerable through research. =

• Align with Objectives: Ensure each research question aligns with operational objectives. =

• Validate Questions: Consult with subject matter experts to validate the relevance and necessity of each question. =

• Document Questions: Record the finalized research questions in an organized manner for future reference and action. =

Obtain Data

Extract Data from Proprietary and Open-Source Repositories

• Identify Data Needs: Determine the specific data types and sources required to address research questions. =

• Utilize Research Tools: Leverage specialized tools and software to access and extract data from identified repositories. =

• Ensure Compliance: Adhere to legal and ethical guidelines governing data extraction from proprietary and open-source repositories. =

• Verify Data Relevance: Regularly cross-check extracted data against research objectives to ensure relevance and utility. =

• Store Data Securely: Implement secure storage solutions to protect the integrity and confidentiality of extracted data. =

• Document Extraction Process: Maintain records of data extraction methods, sources, and dates for transparency and reproducibility. =

• Review and Update Extraction Techniques: Periodically reassess and update data extraction techniques to adapt to evolving data landscapes. =

Validate Data Using Proprietary Sources

• Confirm Source Credibility: Ensure the proprietary sources being used are credible and reliable. =

• Cross-Reference Data: Validate the data by cross-referencing with other reputable sources for accuracy. =

• Apply Data Validation Techniques: Utilize statistical or analytical methods to assess the quality and integrity of the data. =

• Document Source and Data Quality: Maintain detailed records of data sources and the validation processes applied. =

• Seek Expert Verification: Where necessary, consult subject matter experts to corroborate the data’s accuracy and relevance. =

• Continuously Monitor for Changes: Regularly check the proprietary sources for any updates or changes to the data. =

• Report and Address Discrepancies: Promptly report any discrepancies or inconsistencies found during validation for resolution. ### Develop Protocols for Requesting Information (RFI) =

• Define RFI Guidelines: Establish clear guidelines for the formulation and submission of RFIs. =

• Identify Information Needs: Precisely define the information required to fulfill research objectives. =

• Create Standardized Templates: Develop templates for RFI submissions to ensure consistency and completeness. =

• Implement Submission Process: Set up a streamlined process for submitting and tracking RFIs. =

• Train Team Members: Educate team members on RFI protocols and the importance of adherence. =

• Monitor RFI Status: Regularly monitor the status of submitted RFIs and follow up as needed. =

• Incorporate Feedback: Continuously improve RFI protocols based on feedback and evolving research needs. =

Monitor and Track RFI Submissions and Responses

• Implement Tracking System: Utilize software or databases to track RFI submissions and responses. =

• Record Submission Details: Log details of each RFI submission, including date, content, and recipient. =

• Monitor Response Timeframes: Keep track of expected and actual response times for each RFI. =

• Analyze Response Quality: Evaluate the quality and relevance of responses received to RFIs. =

• Follow up on Pending RFIs: Proactively follow up on RFIs that have not received timely responses. =

• Report on RFI Outcomes: Regularly report on the status and outcomes of RFIs to relevant stakeholders. =

• Adjust RFI Strategy: Revise RFI strategies based on response patterns and effectiveness. =

Operate Virtual Research Environments for Data Acquisition

• Set Up Virtual Environments: Establish secure and efficient virtual environments for data acquisition activities. =

• Maintain Data Confidentiality: Implement measures to ensure data confidentiality within virtual environments. =

• Facilitate Remote Collaboration: Enable features that allow for effective remote collaboration among research team members. =

• Monitor Virtual Environment Usage: Track the usage of virtual environments to optimize performance and security. =

• Provide Technical Support: Offer ongoing technical support for users of virtual research environments =

Decommission Virtual Research Environments Ensuring Data Integrity

• Plan Decommissioning: Develop a comprehensive plan outlining steps to decommission the virtual environment safely. =

• Secure Data Backup: Ensure all critical data within the environment is backed up securely before decommissioning. =

• Validate Data Integrity: Confirm the integrity and completeness of the backed-up data. =

• Eradicate Sensitive Data: Permanently delete sensitive data within the environment to prevent unauthorized access. =

• Conduct Security Audits: Perform thorough security audits to ensure no data breaches or vulnerabilities exist. =

• Document Decommissioning Process: Keep detailed records of the decommissioning process, including actions to secure data. =

• Notify Relevant Parties: Inform all stakeholders about the decommissioning and confirm that all necessary data has been transferred or secured. =

Initiate Retrieval of Data from Proprietary Repositories

• Identify Specific Data Needs: Clearly define the data required from the proprietary repositories. =

• Request Access Permissions: Obtain the necessary permissions or access rights to retrieve data from the repositories. =

• Utilize Appropriate Retrieval Tools: Employ the correct tools or software for efficient and effective data retrieval. =

• Ensure Compliance with Protocols: Follow all established protocols and guidelines for data retrieval from proprietary sources. =

• Verify Data Authenticity: Check the retrieved data for authenticity and relevance to the research objectives. =

• Securely Transfer Data: Ensure the safe and secure transfer of data from the proprietary repositories to your system. =

• Document Retrieval Processes: Maintain detailed records of the data retrieval process, including source, date, and retrieval method. =

Process Data

Clean Datasets for Analysis

• Identify Inconsistencies: Review datasets to identify any errors, missing values, or inconsistencies. =

• Remove Irrelevant Data: Eliminate data that is not relevant to the research objectives. =

• Correct Errors: Amend any inaccuracies or errors in the dataset. =

• Handle Missing Values: Address missing data appropriately, either by imputation or removal, depending on the context. =

• Normalize Data: Standardize the format of the data to ensure consistency across the dataset. =

• Document Cleaning Process: Keep a record of all data cleaning actions taken, including reasons for significant changes. =

• Re-verify Post-Cleaning: Ensure the dataset’s integrity is maintained after cleaning. =

Categorize and Tag Data Elements to Ensure Consistency

• Define Categories: Establish clear and relevant categories for data elements. =

• Develop a Tagging System: Create a systematic approach for tagging data elements according to the defined categories. =

• Apply Tags to Data: Systematically categorize and tag each data element. =

• Review for Consistency: Regularly review tagged data to ensure consistency and accuracy in categorization. =

• Adjust Categories and Tags as Needed: Modify the categorization and tagging system as needed based on evolving research needs. =

• Document Categorization Process: Maintain records of how data elements are categorized and tagged. =

• Train Team Members: Educate team members on the categorization system to ensure uniform application of tags. =

Cross-Verify Data Accuracy with Multiple Sources

• Identify Comparable Sources: Locate multiple credible sources for cross-verification. =

• Compare Data Points: Cross-check specific data points across different sources for consistency. =

• Document Discrepancies: Record any discrepancies found during cross-verification. =

• Resolve Conflicts in Data: Investigate and resolve conflicts in data by further analysis or consultation with experts. =

• Reaffirm Source Credibility: Regularly evaluate the credibility of the sources used for cross-verification. =

• Maintain a Verification Log: Keep a detailed log of cross-verification processes and outcomes. =

• Update Data as Necessary: Revise the dataset in light of new information obtained through cross-verification. =

Ensure Compliance with Data Protection Regulations and Ethical Standards

• Understand Relevant Regulations: Gain a thorough understanding of applicable data protection laws and ethical guidelines. =

• Implement Compliance Measures: Apply measures to ensure all data processing activities comply with these regulations. =

• Conduct Regular Compliance Audits: Periodically audit data processing activities for compliance. =

• Address Non-Compliance Issues: Identify and rectify any areas of non-compliance immediately. =

• Maintain Anonymity and Privacy: Ensure personal data is anonymized and privacy is protected where required. =

• Document Compliance Efforts: Keep detailed records of all efforts and measures taken to ensure compliance. =

• Stay Informed on Regulatory Changes: Regularly update knowledge on changes in data protection regulations and ethical standards. =

Analyze Data

Conduct Temporal and Geospatial Analysis to Map Trends

Evaluate Sentiment Fluctuations in Social Media Content

Integrate Correlation of Social Media Accounts with Specific Keywords

Assess Associations between Social Media Accounts and Relevant Hashtags

Examine Links between Social Media Accounts and Pertinent URLs

Compare Social Media Accounts with Provided Images for Verification

Locate Social Media Accounts Based on Geographical Data Analysis

Align Social Media Accounts with Target Account Data for Intelligence Insight

Correlate Published Images with Known Imagery to Detect Patterns

Identify Interactions Among Specified Social Media Accounts for Network Mapping

Measure Change in Data

Monitor Changes in Reported Violent Incidents

• Identify Data Sources: Pinpoint reliable sources of information on violent incidents (e.g., police reports, news outlets). =

• Collect and Aggregate Data: Regularly collect data on reported violent incidents and aggregate it for analysis. =

• Analyze Trends Over Time: Examine changes in the frequency, location, and nature of these incidents over time. =

• Correlate with External Factors: Investigate any correlations between changes in violent incidents and external factors (e.g., policy changes, social unrest). =

• Map Geographical Variations: Analyze geographical data to identify hotspots or changes in spatial patterns of violence. =

• Prepare Detailed Reports: Document findings in comprehensive reports, highlighting significant changes or trends. =

• Update Data Periodically: Ensure the data is regularly updated and re-analyzed to track ongoing trends. =

Track Changes in Media Reporting Patterns

• Establish Monitoring Framework: Define key variables for monitoring media reporting (e.g., tone, frequency, subjects covered). =

• Select Media Outlets: Choose a diverse range of media outlets for a comprehensive view. =

• Employ Media Monitoring Tools: Utilize tools for automated tracking of reporting patterns across selected media outlets. =

• Quantitative and Qualitative Analysis: Conduct both quantitative (e.g., number of articles on a topic) and qualitative (e.g., sentiment analysis) evaluations. =

• Identify Shifts in Coverage: Look for significant shifts in media focus, framing, or sentiment. =

• Correlate with External Events: Analyze how external events or changes influence media reporting. =

• Report on Media Dynamics: Compile insights into the evolving nature of media reporting. =

Analyze Changes in Wireless Signal Patterns

• Define Parameters for Analysis: Determine key metrics for wireless signal analysis (e.g., strength, coverage area, usage patterns). =

• Use Advanced Monitoring Tools: Implement sophisticated tools and technologies for signal monitoring and data collection. =

• Identify Patterns and Anomalies: Look for unusual patterns, disruptions, or enhancements in signal strength or coverage. =

• Assess Impact of Infrastructure Changes: Evaluate the impact of new infrastructures, such as cell towers, on signal patterns. =

• Map Data Geospatially: Use geospatial mapping to visualize changes in wireless signals across different areas. =

• Investigate Causes of Signal Variations: Delve into potential causes behind significant changes in signal patterns. =

• Maintain Ongoing Monitoring: Continuously monitor wireless signals to capture evolving trends and immediate changes. =

Evaluate Shifts in Economic Indicators

• Select Key Economic Indicators: Choose relevant economic indicators (e.g., employment rates, market trends) for analysis. =

• Source Data from Reliable Entities: Obtain data from credible economic sources, like government reports and financial institutions. =

• Perform Time-Series Analysis: Analyze changes in these indicators over time to identify trends and patterns. =

• Cross-Refer with Policy Changes: Cross-reference economic shifts with policy changes or significant global events. =

• Use Statistical Methods for Analysis: Apply appropriate statistical methods to interpret economic data accurately. =

• Generate Comprehensive Economic Reports: Create detailed reports on the state and changes in the economy. =

• Continuously Update Economic Data: Regularly update economic data to provide timely and relevant analysis. =

Quantify Republishing Rates of Social Media Content

• Define Key Content: Identify the specific social media content (posts, tweets, articles) for monitoring. =

• Set Monitoring Tools: Utilize social media analytics tools to track republishing rates (shares, retweets). =

• Collect Data Over Time: Monitor and collect data on republishing rates over a set period. =

• Analyze Trends: Analyze the collected data to identify trends in republishing rates. =

• Compare with Baselines: Compare current data with historical baselines or expected rates. =

• Identify Influencing Factors: Investigate factors contributing to variations in republishing rates. =

• Document and Report Findings: Compile findings into reports for further analysis or decision-making. =

Gauge Interactions with Social Media Hashtags

• Select Target Hashtags: Identify the hashtags relevant to the research or campaign. =

• Track Hashtag Usage: Use analytics tools to track interactions (likes, comments, shares) involving these hashtags. =

• Measure Reach and Engagement: Calculate the reach and level of engagement each hashtag receives. =

• Analyze Audience Demographics: Gather demographic data of users interacting with the hashtags. =

• Interpret Temporal Patterns: Observe and interpret the usage patterns of hashtags over time. =

• Compare with Similar Hashtags: Benchmark against similar hashtags for contextual understanding. =

• Prepare Analytical Reports: Document and prepare detailed reports on the findings. =

Evaluate Engagement with Selected Keywords on Social Media

• Identify Keywords: Determine key phrases or words relevant to the research objectives. =

• Monitor Keyword Mentions: Set up tools to monitor mentions of these keywords across social platforms. =

• Analyze Engagement Metrics: Assess likes, comments, shares, and other engagement metrics associated with the keywords. =

• Contextualize Keyword Usage: Understand the context in which these keywords are used. =

• Map Keyword Popularity: Determine the popularity and spread of these keywords across different demographics and regions. =

• Identify Correlations and Trends: Look for correlations between keyword usage and specific events or trends. =

• Summarize Findings: Consolidate the data into comprehensive reports for insight and strategy formulation. =

Assess the Impact of Specific Social Media Accounts

• Select Accounts for Analysis: Choose the social media accounts relevant to the study. =

• Monitor Account Activity: Track the posting frequency, content type, and engagement levels of these accounts. =

• Measure Influence and Reach: Analyze the influence and reach of these accounts within their networks. =

• Evaluate Audience Interaction: Assess how the audience interacts with the content posted by these accounts. =

• Benchmark Against Comparable Accounts: Compare metrics with similar accounts for a relative impact assessment. =

• Determine Impact on Public Perception: Evaluate how these accounts affect public perception or opinion. =

• Report on Account Influence: Compile a detailed report outlining the influence and impact of the selected accounts. =

Establish a Baseline for Social Media Activity and Trends

• Define Measurement Criteria: Establish the criteria for measuring social media activity (engagement rates, audience growth). =

• Gather Historical Data: Collect historical data to form the basis of the baseline. =

• Determine Average Metrics: Calculate average metrics over a specified period to establish a baseline. =

• Analyze Seasonal Variations: Account for seasonal or event-driven variations in social media activity. =

• Regularly Update Baseline: Periodically review and update the baseline to reflect current trends. =

• Use Baseline for Comparative Analysis: Employ the baseline for comparative analysis in future monitoring. =

• Document Baseline Methodology: Keep detailed records of how the baseline was established and updated. =

Social Network Analysis

Generate Edge List Export Files Using Keywords

Create Edge List Export Files Based on Hashtag Analysis

Develop Edge Lists from Geolocated Social Media Data

Compile Edge Lists Involving Identified Social Media Accounts

Utilize Social Network Analysis to Interpret Edge Lists

Identify Key Communicators Through Social Network Analysis

Produce Reports

Synthesize Intelligence Reports Incorporating RFI and proprietary Insights

• Aggregate Data: Collect and consolidate all relevant RFI responses and proprietary insights pertinent to the intelligence question. =

• Corroborate Findings: Cross-reference the RFI and proprietary data with other sources to ensure reliability and accuracy. =

• Draft Report: Begin constructing the report, integrating insights from various sources into a cohesive narrative. =

• Apply Critical Analysis: Evaluate the implications of the data, identifying patterns, discrepancies, and actionable intelligence. =

• Revise for Clarity: Review the draft for clarity, ensuring that proprietary information is appropriately marked and that RFI insights are highlighted. =

• Seek Feedback: Present the draft to peers or superiors for feedback on the report’s content and adherence to intelligence reporting standards. =

• Finalize the Report: Incorporate feedback and finalize the report, readying it for dissemination. =

Disseminate Research Findings through Appropriate Channels

• Identify Audience: Determine the appropriate audience for the research findings based on clearance level, need-to-know, and relevance. =

• Select Channels: Choose the most secure and effective channels for dissemination, whether electronic, in-person briefings or secure telecommunication. =

• Prepare Dissemination Materials: If necessary, prepare additional materials such as executive summaries, presentation slides, or briefing notes. =

• Disseminate Findings: Share the findings through the selected channels, ensuring all communication protocols are followed. =

• Document Dissemination: Record the dissemination process, including who received the information and through what means. =

Prepare and Present Analysis Findings to Stakeholders

• Customize Presentation: Tailor the presentation of findings to the stakeholders’ level of expertise and interest. =

• Develop Visual Aids: Create visual aids like charts, graphs, and maps to enhance the presentation and understanding. =

• Rehearse Delivery: Practice the presentation to ensure precise delivery and prepare for potential questions. =

• Present Findings: Deliver the presentation, providing clear, concise, actionable intelligence and encouraging feedback. =

• Follow-Up: After the presentation, provide any additional information requested by stakeholders and offer to clarify any points as needed. =

Correlate and Compare Multi-source Data to Produce Comprehensive Insights

• Integrate Data Sets: Merge data from multiple sources to form a comprehensive dataset. =

• Identify Correlations: Use analytical tools to identify correlations and relationships within the data. =

• Assess Validity: Critically evaluate the correlations to ensure they are meaningful, not coincidental, or based on flawed data. =

• Highlight Key Insights: Draw attention to the most significant findings from the data comparison. =

• Document the Process: Ensure the methodology of data correlation is documented for transparency and reproducibility. =

Forecast Future Trends Based on Predictive Analysis

• Collect Historical Data: Gather historical data relevant to the analyzed trend. =

• Select Predictive Models: Choose appropriate predictive models based on the type of data and the trend analysis requirements. =

• Input Data into Models: Enter the collected data into the models to generate predictions. =

• Analyze Predictions: Review the output of the predictive analysis to identify potential future trends. =

• Validate Predictions: Where possible, validate the predictions with subject matter experts or other analytical methods. =

• Report Predictive Insights: Summarize the findings in a report that explains the likely future trends and the confidence level of the predictions. =