Data Manangement Handbook for S-ENDA partners

Data governance

Purpose

Data governance is a data management concept that ensures the availability, usability, integrity, and security of organisational data. It also establishes rules and procedures to ensure data security and compliance thoughout the data life cycle. This chapter explains how we organize and direct data management efforts to ensure that:

• Data guidelines are implemented throughout the organisation;

• Data management practices are in line with and contribute to the institute’s strategic aims;

• The data management regime is reviewed and updated accordingly.

S-ENDA partners have a commitment to integrate FAIR data governance practices into geodata frameworks.

Data life cycle management

Data life cycle management is steered by documentation describing how data generated or used in an activity will be handled throughout the lifetime of the activity and after the activity has been completed. This is living documentation that follows the activity and specifies what kind of data will be generated or acquired, how the data will be described, where the data will be stored, whether and how the data can be shared, and how the data will be retired (archived or deleted). The purpose of life cycle management is to safeguard the data, not just during their “active” period but also for future reuse of the data, and to facilitate cost-effective data handling.

This DMH recommends the following concepts of life cycle management to be implemented:

• An institution specific Data Management Handbook (MET has a common template available here);

• Extended discovery metadata for data in internal production chains (these are metadata elements that provide the necessary information for life cycle management just described);

• A Data Management Plan (DMP) document.

The goal is that life cycle management information shall be readily available for every dataset managed by the institute.

Data Management Plan

A Data Management Plan (DMP) is a document that outlines how the data life cycle management will be conducted for datasets utilized and generated in specific projects. Typically, these are externally financed projects for which such documentation is required by funding agencies.

The Research Council (Norges forskningsråd - NFR) has implemented guidelines mandating publicly accesible DMPs from its funded projects. For more details on NFR's guidelines regarding the contents of a DMP, click here for more information regarding NFR's guidelines for the contents of a DMP. We recommend adhering to these guidelines for any data management project.

While larger internal projects covering many datasets might benefit from a dedicated document of this nature, generally writing formal DMPs for the various datasets is not cost-effective. In such cases it is more appropriate to employ metadata to steer data handling processes (metadata-steered data management) and thereby automate as much of those processes as possible.

Examples of DMP services:

¹ The institute has used or uses the service

Example of a Data Management Plan Template

EasyDMP, as an example, is a web tool designed to facilitate and standardize the creation of Data Management Plan (DMP) documents. It can be customized according to specific governance requirements by each institution. It provides a list of questions to be answered by the person responsible for providing the DMP.

An EasyDMP template is divided into sections:

• Data Summary -> A general introduction about data types, sources, quantity, targets, context.
• FAIR Data -> Expanding on Findability, Accessibility, Interoperability, Reusability.
• Allocations of Resources -> Infrastructures, funding, responsible persons.
• Data Security -> Does the data require specific restrictions or limited access?
• Ethical Aspects -> Any special consideration about the specific ethical implications related to data?
• Other -> Any additional information not covered before.