Intro

Here you will find a current list of projects that are using GitHub and/or ZenHub for hosting their deliverables and process management.

Take note that this list is not a mirror of COSA, a registry of open-source projects implementing CDISC standards, projects not necessarily part of CDISC.

The list below only includes open-source projects that CDISC is implementing themselves.

Analysis Results Standand (ARS)

The goal of the ARS team is to develop:

• Analysis Results Metadata Technical Specification (ARM-TS), to support automation, traceability, and creation of data displays
• Define an Analysis Results Data (ARD) structure, to support reuse and reproducibility of results data
• Illustrate and exercise ARD and ARM-TS with a set of machine-readable common safety displays
• Develop a logical analysis results metamodel to support ARM and ARD

CDISC Open Rules Engine (CORE)

CORE has been developed as an open-source product to make possible the execution of rules for validating clinical data.

Digital Data Flow (DDF)

The main purpose of DDF is to create the logical model (USDM), API definition, Implementation Guide (IG), and Controlled Terminology (CT) (together known as the "Digital Data Flow Reference Architecture"). This product, in turn, will be used as the basis for another project led by TransCelerate, Digital Data Flow. The reference architecture will provide a standard for anyone who wishes to create conformant standards-based technologies, which produce or consume study definitions.

CDISC Conformance Rules Editor

The Rules Editor project delivers an easy to use rule editor where data scientists can

• Author conformance rules in YAML
• Check the rule against the Conformance Rule Schema standard
• Test the rule against test data
• Publish the rule

Conceptual and Operational Standards Metadata Services (COSMoS)

Iterative approach to creating biomedical concepts and representing them in the Foundational Standards as dataset specializations with Value Level Metadata definitions. Biomedical Concepts fill gaps in the current standards by adding semantics, variable relationships, and the detailed metadata needed to generate CRFs or Define-XML.

CDISC Biomedical Concepts (BCs) include a two-layered approach.

• Conceptual/abstract layer that provides standards-agnostic, unambiguous semantic definition largely based on NCIt concepts.

• An implementation layer consisting of SDTM Dataset Specializations provides value level definition that facilitates metadata-driven automation.

Dataset-JSON v1.1

Dataset-JSON is a data exchange standard for sharing tabular data using JSON. It is designed to meet a wide range of data exchange scenarios, including regulatory submissions and API-based data exchange. Each Dataset-JSON dataset can optionally reference a Define-XML file containing detailed information about the metadata. One aim of Dataset-JSON is to address as many of the relevant requirements in the PHUSE 2017 Transport for the Next Generation paper as possible, including the efficient use of storage space.