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Data Science, Semantics & AI/ML

Science is evolving, as is data science, needing a combination of data extraction, wrangling, pipelining, modelling and visualisation. Zifo has real-world experience in all these areas and how to integrate ontologies, semantic enrichment and data consumption with AI and ML.

ontology-development-governance

Ontology definition and governance in commercial and open-source platforms alongside deep domain and technical knowledge to support your FAIR and semantic data journey.

data-extraction-and-wrangling

Extracting data from and transforming to alternate formats including graph data structures like RDF, special structures like ADF etc to support loading to data lakes, warehouses for reuse and data FAIRification

model-development-management

Data modelling, plumbing, wrangling, transformation, management, and enrichment all support Machine Learning (ML) & artificial intelligence (AI) as need good quality data to work well.

grapha-data

Generating, transforming non-graph data, and graph data storage platforms like GRAKN, NEPTUNE, NEO4J etc. alongside ontology definition & management supports interoperable and reusable data.

semantics-mdm-data-enrichment

Master Data Management (MDM), Semantics and Data Enrichment can help maximise data value, trust in data and support the FAIRification of data assets and digital transformation.

program-delivery

Machine Learning (ML) and Artificial Intelligence (AI) model development, integration and management to support scientific decisions and analysis.

translational-sciences

Bidirectional translation of biomedical knowledge from the early research laboratory, through development and manufacturing to clinical & patient-oriented and population-based research