1. Stanford University, Stanford, CA, USA
An Open Repository Model for Acquiring Knowledge about Scientific Experiments
EKAW 2016 – November 21th, 2016
Bologna, Italy
Martin O’Connor, Marcos Martínez-Romero, Attila L. Egyedi, Debra Willrett, John Graybeal, and Mark A. Musen
Stanford University, Stanford, CA, USA
Reproducibility problem in science.
Many scientific experiments not reproducible.
I am going to talk about a metadata model and an associated system called CEDAR that aims to address part of that challenge.
metadatacenter.org
Stanford University

2. Reproducibility Problem in Science
The problem regarding reproducible researches emerged in Amgen when its researchers made headlines in 2012 when they announced that they were not able to reproduce the findings of 47 out of 53 researchers on cancer.

3. Metadata Key to Addressing Problem
Crucial for reproducibility in biomedicine
Locate experimental datasets online
Understand how the experiments were performed
Reuse the data to perform new analyses
Journals and funding agencies increasingly require making experimental data and metadata available

4. Many Metadata Standards have been Developed

5. However: Metadata Submission is Hard

6. Metadata Submission is Hard - II
Summary Data Matrix
Submission Interface
Raw Data

7. Result: Poor Metadata
age
Age
AGE
`Age
age (after birth)
age (in years)
age (y)
age (year)
age (years)
Age (years)
Age (Years)
age (yr)
age (yr-old)
age (yrs)
Age (yrs)
age [y]
age [year]
age [years]
age in years
age of patient
Age of patient
age of subjects
age(years)
Age(years)
Age(yrs.)
Age, year
age, years
age, yrs
age.year
age_years
Variants of ‘age’ metadata field in Gene Expression Omnibus (GEO) repository

8. Our Solution: CEDAR - A Metadata Ecosystem
Overcome the impediments to creating high-quality metadata
Facilitate
Creation
Acquisition
Use
Evaluation
Refinement
Key goal: create a sharable metadata exchange format – a template model - for publishing, searching, exchanging metadata

9. CEDAR Template Model Goals
Must describe composite structure of templates
Implemented using standard formats
Express semantics
Metadata instances:
Linked to controlled terms
Easily serializable
Easily validated
Easily indexed
Interchange with RDF
High readable
Produced/consumed via REST APIs and usable in JavaScript front ends
Meets FAIR goals
Model (but also the standards used to implement it)

10. Using JSON Schema and JSON-LD for CEDAR Template Model
JSON Schema + JSON-LD
JSON-LD

11. What is JSON Schema?
Technology for describing and validating the structure of JSON documents
Provides a structural description of any JSON document
JSON documents that are specified with JSON Schema can be structurally validated against their associated schemas
Analogous to XML Schema

12. What is JSON-LD? A lightweight syntax to serialize Linked Data in JSON
Allows existing JSON to be interpreted as Linked Data with minimal changes
JSON-LD is primarily intended to be a way to:
use Linked Data in Web-based programming environments
build interoperable Web services
store Linked Data in JSON-based storage engines
Core contribution: add semantics to JSON documents
W3C Recommendation:

13. Using JSON Schema to Define Template Structure
{ "$schema": " " " "title": ”Study", "description": ”Study template", "type": "object", "_ui": {...}, "properties": { "title": {...}, ”description": {...}, ”principalInvestigator": {...} }, "required": ["title", "description", "principalInvestigator"] "additionalProperties": false }

14. Using JSON-LD to add Semantics to Metadata Instances
{ "title": { "Immune biomarkers study" }, "description": { "Immune biomarkers …" }, "principalInvestigator": { "name": { "Dr. P.I" }, "institution": { "name": { "Stanford" }, "zip": { "94305" } }

15. Using JSON-LD to add Semantics to Metadata Instances - II
{ " " { "title": " "name": " "description": " "zip": " "pi": " "institution": " }, "title": { "Immune biomarkers study" }, "description": { "Immune biomarkers …" }, ”principalInvestigator": { " " "name": { "Dr. P.I" }, "institution": { " " "name": { "Stanford" }, "zip": { "94305" } }

16. CEDAR Metadata Instances can be transformed to an RDF Graph

17. Model drives CEDAR Workbench
CEDAR Template Model
Controlled terminologies

18. Template Designer provides Template Creation
Basic template designer screen showing a Study template being created with ontology terms being specified as constraints for the diseased field

19. Metadata Editor automatically generates an Acquisition Interface

20. Metadata Editor Adds Semantics
Basic Metadata Editor screen showing Study instance being populated and Disease controlled term field being auto-completed

21. Initial Results Public alpha release in September 2016
Represented all public metadata in ImmPort repository (146 studies)
Represented an array of public ISA-created biomedical studies (~300)
Represented 60k ISO based Common Data Elements from NCI
Currently working with Stanford Digital Repository and several research groups

22. Summary
We have developed a standards-based template model for representing, publishing, and sharing templates and metadata
Provides strong interoperation with Linked Open Data
Metadata easy to create/consume using off-the-shelf tools
Very easy to work with using CEDAR tools

23. CEDAR Resources Web site: http://metadatacenter.org
Workbench:
GitHub: