Hi, I'm Ben

Building public dashboards on EITI's companies database, with USGS, World Bank, and UN Comtrade data: domestic revenue mobilization, transition minerals, and production and exports, including the EITI Dashboard.

A national platform for Nature-based Solutions in the Philippines: hazard and ecosystem data, screening for pilot cities, and an NbS catalog.

An open data platform for extractive-industries transparency: EITI data across countries, companies, and sectors to filter, preview, and download.

A public dashboard of EITI data on domestic resource mobilization, reserves, and production and exports, built as a static site from the EITI database.

The guide to joining, organizing, or delivering the ASEAN AHEAD AI Career Readiness Course in the Philippines, with SmartCT.

Free, hands-on QGIS workbooks, from your first map to atlases, reports, and forestry tenure maps: 6 courses, 30 modules, and 71 exercises.

Spatial databases, GeoServer, spatial data infrastructure and GeoNode, web maps, and cloud-native geospatial—from desktop to web to cloud.

Python essentials, arrays and dataframes, an introduction to AI and ML, and geospatial Python: 2 courses, 13 modules, and 104 exercises.

An approachable introduction to the fundamentals of data literacy.

Consecutive consultancies on the Asian Development Bank's spatial data platform, from supporting ADB SPADE to running its Enterprise GIS.

Several contracts with one aim: turning EITI's summary data files and companies data into open data that is checked once and reused everywhere.

A three-day hands-on training on turning survey data from many sources and formats into a release people can trust: a pipeline that gets each round, checks it with pydantic and pandera, stores it in a database built from those checks, and shares it through Datasette. Taught in marimo, so participants ran it on an unseen survey with one command.

A five-day hands-on training with the PSA Agriculture and Fisheries Census Division and other divisions, one stage a day: store it (PostGIS, DuckDB, data lakes), share it (GeoServer, pygeoapi, OGC services), catalog it (GeoNode, metadata, SDI), use it (web maps and dashboards), and scale it (GeoParquet, PMTiles, COG, STAC).

A five-day hands-on training covering the full machine learning pipeline and common geospatial Python and ML stacks: Google Earth Engine in Python via geemap, raster and vector data with rasterio and geopandas, comparing classification models in scikit-learn, and running AI and deep-learning models with geoai.

A five-day training that laid the groundwork for using Python effectively—package and environment management, notebooks, syntax, and data structures—and introduced arrays and dataframes for future data, AI, and ML work. Alongside staples such as Jupyter, conda, and pandas, we explored modern tools such as uv, marimo, DuckDB, and polars.

A five-day virtual course, in BNHR's data-driven approach to capacity building, that introduced remote sensing with Google Earth Engine and its use in disaster risk reduction, urban planning, and environmental management.

A five-day course—hands-on, exercise-driven, and focused on tangible outcomes—that culminated in participants showcasing Python and QGIS projects such as processing automations, models, and interactive maps.

A five-day course on the components of geospatial data management: field data collection and custom attribute forms in QGIS, PostGIS, GeoServer, GeoNode, and QGIS in multi-user and enterprise environments.

Two three-day courses for geologists, engineers, technicians, data analysts, and specialists on fundamental geographic and QGIS skills and the advanced symbology their day-to-day work needs.

A five-day course on the geospatial concepts and QGIS functions useful in disease mapping and surveillance: data from CSVs and spreadsheets, open geospatial data sources, joining and styling layers, map-making, and data gathering with Kobo.

A five-day training-workshop on using QGIS, Python, spatial SQL, R, and other tools to develop and automate a geo-enabled master sample frame for the next national census.