

Month: 2025-05. Key outcomes: Delivery of a Plotly-based Visualization Dashboards solution for OpenITI/FASDH25, consolidating Python data analysis scripts with web-based Plotly visualizations to analyze articles and provide interactive dashboards for homework plots (n-gram) and topic modeling visualizations. Major bugs fixed: none reported this month. Impact: equips teams with data-driven insights for content analysis and homework performance, enabling faster decision making and improved monitoring of article trends. Technologies/skills demonstrated: Python data analysis, Plotly, interactive dashboards, data visualization, n-gram analysis, topic modeling, Git/version control, modular scripting, and reproducible pipelines.
Month: 2025-05. Key outcomes: Delivery of a Plotly-based Visualization Dashboards solution for OpenITI/FASDH25, consolidating Python data analysis scripts with web-based Plotly visualizations to analyze articles and provide interactive dashboards for homework plots (n-gram) and topic modeling visualizations. Major bugs fixed: none reported this month. Impact: equips teams with data-driven insights for content analysis and homework performance, enabling faster decision making and improved monitoring of article trends. Technologies/skills demonstrated: Python data analysis, Plotly, interactive dashboards, data visualization, n-gram analysis, topic modeling, Git/version control, modular scripting, and reproducible pipelines.
April 2025 — OpenITI/FASDH25: Implemented automated article text analysis capabilities to enable rapid, data-driven insights from media articles. Delivered two Python scripts: (1) a Pattern Occurrence Counter that tallies occurrences of specified terms (e.g., Israeli, Palestine/Palestinian, Gazan) across articles in a folder and aggregates results; (2) a Gazetteer-based Place Name Counter that reads a gazetteer file and counts occurrences in the aljazeera_articles dataset, printing counts when matches are found. Both scripts are designed for reuse, and easy integration into research pipelines. Commit: c4e923b34f6037a605f826e8016857edb8296cad (Added new files).
April 2025 — OpenITI/FASDH25: Implemented automated article text analysis capabilities to enable rapid, data-driven insights from media articles. Delivered two Python scripts: (1) a Pattern Occurrence Counter that tallies occurrences of specified terms (e.g., Israeli, Palestine/Palestinian, Gazan) across articles in a folder and aggregates results; (2) a Gazetteer-based Place Name Counter that reads a gazetteer file and counts occurrences in the aljazeera_articles dataset, printing counts when matches are found. Both scripts are designed for reuse, and easy integration into research pipelines. Commit: c4e923b34f6037a605f826e8016857edb8296cad (Added new files).
Month: 2025-03 — OpenITI/FASDH25 Key features delivered: - Urdu corpus ingestion and metadata management: Ingested and organized the Urdu corpus including 7598_manger and related texts; added new manuscripts, metadata, and structured content to support search and scholarly study. Completed assigned-page work in Kamil_manger and Kamil_7598_manger; created new files and sections; local changes saved before pulling updates to ensure reproducibility. - Text analysis tooling for headings and place-name counting: Implemented tooling to analyze text files, extract headings, count words, and tally occurrences of place names (e.g., Gaza, Israel, Palestine) to support indexing and research. Major bugs fixed / stability improvements: - Safeguarded local edits before pulling upstream updates, reducing risk of data loss and merge conflicts; stabilized ingestion workflow. - Minor data consistency improvements across new and existing manuscript files during ingestion cycle. Overall impact and accomplishments: - Strengthened data infrastructure for Urdu corpus with richer metadata and searchable content, enabling faster search, indexing, and scholarly workflows. - Established scalable text analytics foundation for headings and place-name metrics to support research pipelines. - Demonstrated end-to-end feature delivery across ingestion and analysis tooling within a single repository, with clear progression through assigned page work. Technologies/skills demonstrated: - Data ingestion, metadata modeling, and corpus organization. - Text analysis tooling and basic NLP-related pipelines (headings, word counts, place-name counts). - Version control discipline: incremental commits, per-file changes, conflict avoidance. - Cross-manuscript collaboration and documentation of changes.
Month: 2025-03 — OpenITI/FASDH25 Key features delivered: - Urdu corpus ingestion and metadata management: Ingested and organized the Urdu corpus including 7598_manger and related texts; added new manuscripts, metadata, and structured content to support search and scholarly study. Completed assigned-page work in Kamil_manger and Kamil_7598_manger; created new files and sections; local changes saved before pulling updates to ensure reproducibility. - Text analysis tooling for headings and place-name counting: Implemented tooling to analyze text files, extract headings, count words, and tally occurrences of place names (e.g., Gaza, Israel, Palestine) to support indexing and research. Major bugs fixed / stability improvements: - Safeguarded local edits before pulling upstream updates, reducing risk of data loss and merge conflicts; stabilized ingestion workflow. - Minor data consistency improvements across new and existing manuscript files during ingestion cycle. Overall impact and accomplishments: - Strengthened data infrastructure for Urdu corpus with richer metadata and searchable content, enabling faster search, indexing, and scholarly workflows. - Established scalable text analytics foundation for headings and place-name metrics to support research pipelines. - Demonstrated end-to-end feature delivery across ingestion and analysis tooling within a single repository, with clear progression through assigned page work. Technologies/skills demonstrated: - Data ingestion, metadata modeling, and corpus organization. - Text analysis tooling and basic NLP-related pipelines (headings, word counts, place-name counts). - Version control discipline: incremental commits, per-file changes, conflict avoidance. - Cross-manuscript collaboration and documentation of changes.
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