Digital Curation Centre: DCC Charter & Statement of Principles

DCC Charter & Statement of Principles

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This Charter and Statement of Principles is intended to:

Convey key curation messages to primary stakeholders and to our wider community
Inform and influence political positioning in the curation and preservation landscape
Promote and publicise the DCC and curation concepts
Facilitate the process of consensus within the DCC on critical issues of identity and mission

What is digital curation?

Digital curation is maintaining and adding value to a trusted body of digital information for current and future use; it encompasses the active management of data throughout the information lifecycle.

Why curate?

Data are evidence supporting research and scholarship; better research is based on verifiable data, which may in turn lead to new knowledge.

Observational, environmental and other data are unique and cannot be recaptured or reproduced.

Data may represent records and have associated legal requirements; curation will allow us to protect the data for the future, and manage risks.

Where data is created in the course of research that is publicly funded, a duty to manage is implied, including the provision of access to data and data reuse. Meeting this obligation will be enabled by good data stewardship.

What data?

Curation requires effort and resources. In principle, any digital object or database may be perceived as likely to be of sufficient value for the effort and expense of curation. Data may be curated in the short-term, but may not require long-term preservation.

There are cost barriers to both curation and preservation, so an effective appraisal and selection process is essential. It is important to build an appropriate robust, distributed infrastructure to support curation. Components may include laboratory repositories, institutional repositories, subject or discipline repositories, databases and data centres.

Co-ordinated strategies and policies at research funder level are required, together with sufficient investment for the future.

When?

Curation applies throughout the information lifecycle, from before or at the point of data creation, through primary use to eventual disposal.

The DCC Curation Lifecycle Model describes the processes involved in curation. The lifecycle may continue indefinitely and curation cannot be left to the end of primary use, for example at the end of a funded project.

Who should have responsibility?

A number of roles and responsibilities are involved in curation and preservation practice within the Curation Lifecycle. Curation should start with the individual or group that creates or captures the information.

Curation requires a significant amount of domain knowledge; data scientists and data curators may add value to the original data. Users, custodians and reusers of the data and the funding bodies have curation responsibilities.

There is currently a shortage of experienced data scientists and curators with digital preservation experience.

How will curation be achieved?

The key is to follow good practice, including domain, national and international standards in the capture, management and archiving of data.

Processes and tools to assure easy discovery, control access and to facilitate data sharing and reuse are required. An infrastructure of data centres and trusted repositories, together with methodologies to demonstrate provenance and assure authenticity, are essential.

Curation practice in detail will depend on the domain or discipline. Data structure, scale and ownership must also be taken into account, as well as the diversity of cultures and research methodologies. Curation can build on and fit in with current practices, for example, researchers' informal sharing of ongoing research with colleagues; or their training, or the need to comply with formal regulatory and ethical procedures.

DCC Principles

The Digital Curation Centre has a commitment to:

Facilitate data creation, access, use and reuse in the short and longer term, together with global sharing, both within and across disciplines, sectors and communities.
Promote data sharing policies which include the production of a data management plan.
Advocate preservation and management models which provide an appropriate and established foundation for digital preservation activity, for example the OAIS Reference Model and ISO 15489: Information and Documentation - Records Management.
Promote the practice of creating documentation and metadata as a means of providing context for datasets, in order to facilitate the future discovery, access, use and reuse of data.¹
Support data creators to submit their data or other research materials to a trusted and sustainable repository, archive, data centre or other preservation service, for further curation and long-term preservation, in line with documented collecting policies and funder policy guidelines.²
Advocate that repositories, archives, data centres and other preservation services, identify, collect and share the data and information structures (representation information), that will be needed to render archived data in a form understandable over the long-term to its user communities (for example, in a Representation Information Registry Repository such as RRORI).
Stress the requirement for persistent identification of a digital object, to facilitate discovery, linking and citation of a dataset.
Recommend that institutions perform a formal data audit to assess the scale and scope of curation activity and use a structured methodology, such as the Data Audit Framework.
Promote effective curation tools such as the DRAMBORA Interactive Toolkit, which provides an appropriate approach for the audit of institutional and subject repositories.
Provide quality training and resources, such as Digital Curation 101 and the DCC Digital Curation Manual, as a means of building capacity and skills within the education community.

¹ The creation of metadata is an important part of the curation process and should be documented in the data management plan. Descriptive and preservation metadata are required. Appropriate frameworks of standards and protocols should be followed, to ensure that opportunities for discovery and data sharing are maximised. Note that some instruments used routinely in the research workflow, for example in the laboratory, may generate data and metadata outputs in proprietary formats.

Structured metadata may be supplemented by informal tags and keywords to add value and enhance discovery within social networks and other collaborative services. The collective intelligence including annotations, tags and comments associated with a digital object, contributes to contextual information and should be assessed as part of the Curation Lifecycle. Data objects and associated metadata, documentation and other representation information, form a "package" of information.

² Preservation services will assess the submitted information package in a selection or appraisal process, which includes evaluating the information package against a number of predefined criteria. These criteria may be related to the quality of the data object and its associated metadata, the usefulness of the data, the usability of the data by others and the uniqueness of the data. Datasets may be "cleaned up" for inclusion or ingest into the repository: transformation to other formats may be required to ensure long-term preservation.