Interoperable

• (meta)data use a formal, accessible, shared, and broadly 

applicable language for knowledge representation.

• (meta)data use vocabularies that follow FAIR principles

• (meta)data include qualified references to other (meta)data

The Configurable Data Curation System (CDCS)

C.A. Becker, M.C. Brady, K.G. Brady, C.E. Campbell, A.L. Catel, P.J. Dessauw, A.A. Dima, G.R. Greene, R.J. Hanisch, 

B. Long, M.W. Newrock, R.L. Plante, P.F. Rigodiat, X. Schmitt, G. Sousa Amaral, Z.T. Trautt, J.A. Warren

Vision

The Configurable Data Curation System (CDCS) aims 

to support and enable:

• An Effective Research Data Lifecycle

• FAIR Data Principles

1

(Findable, Accessible, Interoperable, and Reusable)

• Modular System Design

Visit: 

https://cdcs.nist.gov/

Repositories

The CDCS empowers communities to deploy and 

operate specialized repositories, which enables 

Accessibility of data and metadata. Data and 

metadata are stored in Interoperable formats and 

can be retrieved by API. Examples of three materials 

repositories are shown below.

Registries

The CDCS empowers communities to deploy and 

operate specialized registries by enabling Findability

of data and resources. Examples for materials and 

metrology are shown below.

Modular System Design

The CDCS utilizes a modular 

web framework based on 

Django. A service can be 

configured via Django Package 

installation. Common features 

include a GUI, API, XSL 

visualization/transformation

and OIA-PMH.

Data Ingest

The CDCS enables Acquisition and Storage of data in 

Interoperable formats early in the data lifecycle. For 

example, the Materials Data Curation System2(MDCS) is 

shown below. The MDCS API enables automated curation.

Schemas

The CDCS enables Interoperability of data and metadata 

via XML technologies such as XML Schemas. In this way, it 

can support existing XML-based data standards, such as 

MatML, ThermoML, and MTConnect, which have a stable 

following in scientific and engineering communities. The 

CDCS also support data reuse through creation and 

exchange of modular, community-based schemas, 

supporting diverse users who leverage shared concepts. 

The MGI is developing a registry and repository for 

supporting this kind of exchange which will enable the 

Findability, Accessibility, and Reuse of these resources.

References

[1] Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, 

M., Baak, A., et al. (2016). The FAIR Guiding Principles for scientific data 

management and stewardship. Scientific Data, 3, 160018. 

https://doi.org/10.1038/sdata.2016.18

[2] Dima, A., Bhaskarla, S., Becker, C., Brady, M., Campbell, C., Dessauw, P., 

et al. (2016). Informatics Infrastructure for the Materials Genome Initiative. 

JOM, 68(8), 2053–2064. https://doi.org/10.1007/s11837-016-2000-4

Engagement

The CDCS represents a platform through which NIST and 

related communities have begun to mutually engage in 

discussion, development, and problem-solving. Driven by 

FAIR data principles, this has given rise to a number of 

activities through NIST, including:

• Community standards: To increase the availability and 

quality of community standards, NIST hosted 

workshops focused on community data model 

development.

• Interoperability: To increase integration among data 

platforms (for materials science and beyond), NIST 

hosted a hackathon focused on such integrations.

• Community development: To support the development 

of FAIR data communities (in materials science and 

elsewhere), NIST began an annual convention for 

growing and nurturing the CDCS community of users.

Findable

• (meta)data are assigned a globally unique and persistent 

identifier

• data are described with rich metadata 

• metadata clearly and explicitly include the identifier of the data it 

describes

• (meta)data are registered or indexed in a searchable resource

Accessible

• (meta)data are retrievable by their identifier using a standardized 

communications protocol

- the protocol is open, free, and universally implementable

- the protocol allows for an authentication and authorization 

procedure, where necessary

• metadata are accessible, even when the data are no longer 

available

Reusable

• meta(data) are richly described with a plurality of accurate and 

relevant attributes

- (meta)data are released with a clear and accessible data 

usage license

- (meta)data are associated with detailed provenance

- (meta)data meet domain-relevant community standards

Plan

Acquire

Process

Store Analyze

Share

Reuse

core_main_app

core_curate_appcore_explore_keyword_appcore_dashboard_appcore_explore_oaipmh_appcore_exporters_app

...

MDCS

Django 

Web 

Framework

DB

GUI

API OAI

XSL

Duration

Organizers

Format

Objective

(Optional)

pre-convention

Tutorials

1-2 Days

Stakeholders

Parallel Track

Education

Annual

Convention

2-3 Days

NIST Development Team

Single Track

Stakeholder Networking &

Annual Roadmapping

Exercise

(Optional)

post-convention

Code Sprints

1-2 Days

Stakeholders

Parallel Track

Software Development

Planning & Implementation