Projects

Selected open-source, data science, and research engineering projects by Akewak Jeba.

My projects focus on reproducible data access, scientific software, machine learning, and research infrastructure. I especially enjoy building the layer between difficult source systems and researchers who need clean, analyzable data.

Cultural heritage & bibliographic data

finna — Finna API for R

An open-source R package for retrieving and analyzing cultural heritage metadata from Finland’s Finna service. It provides reproducible access to records from libraries, museums, archives, and other cultural heritage organizations.

Focus: API clients · metadata retrieval · reproducible workflows · digital humanities

Documentation GitHub

finto — Semantic vocabularies and ontologies

R tooling for accessing Finnish vocabulary and ontology services. The work supports concept lookup, multilingual metadata enrichment, semantic search, and the use of controlled vocabularies in computational research.

Focus: linked data · ontologies · multilingual metadata · semantic enrichment

fennica — Finnish national bibliography workflows

Tools and analysis workflows for working with Finnish national bibliography data at scale, including harmonization and computational analysis of historical publication metadata.

Focus: bibliographic data science · metadata harmonization · cultural history · R

Computational biology

LimROTS

A hybrid statistical method and Bioconductor package that combines empirical Bayes modeling with reproducibility-optimized statistics for robust differential expression analysis.

Focus: statistical programming · proteomics · Bioconductor · reproducibility

Bioconductor

iSEEtree

An interactive explorer for hierarchical biological data, developed as part of a collaborative scientific software project.

Focus: interactive analysis · visualization · hierarchical data · Bioconductor

Research engineering

AI-assisted reproducible analysis

Methodological work exploring how AI systems can help researchers construct transparent computational workflows across data retrieval, cleaning, variable construction, statistical analysis, visualization, and reporting.

Focus: AI agents · reproducibility · evaluation · statistical workflows · provenance

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