Projects

The Human-Aware Data Acquisition Infrastructure (HADatAc) is an open-source software solution that enables combined acquisitions of data and metadata in a way that metadata is properly and logically connected to data. By data (and metadata) acquisition we mean the process of identifying data sources, interacting with these sources to move the data from their transient state into a persistent repository, and to enable the data to be retrieved from their persistent repositories through the use of queries.

ISWC 2024 Resource

HADatAc is an open source code project that has beeen under developed since 2014. Its infrastructure’s source code was moved into a public GitHub Reposi-
tory at in July, 5th 2015. Links for resources related to HADatAc, including the GitHub repository hosting the HADatAc open source code is listed in the table below.

HADatAc License of the source code is Apache License, Version 2.0.

HADatAc in GitHub Software Documentation

The Human-Aware Science Ontology (HAScO) "integrates a collection of well-established science-related ontologies, and aims to addressing issues related to data annotation for large data ecosystem, where data can come from diverse data sources including sensors, lab results, and questionnaires. The work reported in the paper is based on our experience developing HAScO, using it to annotate data collections to facilitate data exploration and analysis for numerous scientific projects, three of which will be described. Data files produced by scientific studies are processed to identify and annotate the objects (a gene, for instance) with the appropriate ontological terms. "

Along with the ontology itself, this project provides a HAScO-based Java API. This Java API is used as a foundation for both the HADatAc Infrastructure and SIR repositories.

HAScO Ontology VSTOI Ontology HASCO API in GitHub Software Documentation

This is a specific collaborative effort of developing application ontologies in support of Human Health Exposure Analysis Resource (HHEAR) and Children Health Exposure Analysis Resource (HHEAR) projects from NIEHS.

HHEAR Ontology CHEAR Ontology

The Semantic Instrument Repository (SIR) is an infrastructure that enables the canonical registration of SIR elements encoded as RDF resources. SIR core elements are Instruments, Detectors, Experiences, ResponseOptions. and Semantic Variables. From the collection of available elements, SIR is capable of rendering questionnaire instruments, generating Semantic Data Dictionaries.   

SIR (the app's GUI)in GitHub SIRAPI in GitHub Software Documentation