Backup your data
To avoid accidental loss of data you should:
preserve
Choose and use standard terminology to enable discovery
Terms and phrases that are used to represent categorical data values or for creating content in metadata records should reflect appropriate and accepted vocabularies in your community or institution. Methods used to identify and select the proper terminology include:
Create and document a data backup policy
A backup policy helps manage users' expectations and provides specific guidance on the "who, what, when, and how" of the data backup and restore process. There are several benefits to documenting your data backup policy:
Decide what data to preserve
The process of science generates a variety of products that are worthy of preservation. Researchers should consider all elements of the scientific process in deciding what to preserve:
Document and store data using stable file formats
File formats are important for understanding how data can be used and possibly integrated. The following issues need to be documented:
Ensure flexible data services for virtual datasets
In order for a large dataset to be effectively used by a variety of end users, the following procedures for preparing a virtual dataset are recommended:
Ensure integrity and accessibility when making backups of data
For successful data replication and backup:
Ensure the reliability of your storage media
All storage media, whether hard drives, discs or data tapes, will wear out over time, rendering your data files inaccessible. To ensure ongoing access to both your active data files and your data archives, it is important to continually monitor the condition of your storage media and track its age. Older storage media and media that show signs of wear should be replaced immediately. Use the following guidelines to ensure the ongoing integrity and accessibility of your data:
Identify and use relevant metadata standards
Many times significant overlap exists among metadata content standards. You should identify those standards that include the fields needed to describe your data. In order to describe your data, you need to decide what information is required for data users to discover, use, and understand your data. The who, what, when, where, how, why, and a description of quality should be considered. The description should provide enough information so that users know what can and cannot be done with your data.
Identify data sensitivity
Steps for the identification of the sensitivity of data and the determination of the appropriate security or privacy level are:
Identify data with long-term value
As part of the data life cycle, research data will be contributed to a repository to support preservation and discovery. A research project may generate many different iterations of the same dataset - for example, the raw data from the instruments, as well as datasets which already include computational transformations of the data.
Identify suitable repositories for the data
Shaping the data management plan towards a specific desired repository will increase the likelihood that the data will be accepted into that repository and increase the discoverability of the data within the desired repository. When beginning a data management plan:
Plan data management early in your project
A Data Management Plan should include the following information:
Plan for effective multimedia management
Multimedia data present unique challenges for data discovery, accessibility, and metadata formatting and should be thoughtfully managed. Researchers should establish their own requirements for management of multimedia during and after a research project using the following guidelines. Multimedia data includes still images, moving images, and sound. The Library of Congress has a set of web pages discussing many of the issues to be considered when creating and working with multimedia data. Researchers should consider quality, functionality and formats for multimedia data.
Preserve information: keep your raw data raw
In order to preserve the raw data for future use:
Provide a citation and document provenance for your dataset
For appropriate attribution and provenance of a dataset, the following information should be included in the data documentation or the companion metadata file:
Provide identifier for dataset used
In order to ensure replicable data access:
- Choose a broadly utilized Data Identification Standard based on specific user community practices or preferences
- DOI
- OIDs
- ARKs
- LSIDs
- XRIs
- URNs/URIs/URLs
- UUIDs)
- Consistently apply the standard
- Maintain the linkage
- Participate in implementing infrastructure for consistent access to the resources referenced by the Identifier
Recognize stakeholders in data ownership
When creating the data management plan, review all who may have a stake in the data so future users of the data can easily track who may need to give permission. Possible stakeholders include but are not limited to:
Store data with appropriate precision
Data should not be entered with higher precision than they were collected in (e.g if a device collects data to 2dp, an Excel file should not present it to 5 dp). If the system stores data in higher precision, care needs to be taken when exporting to ASCII. E.g. calculation in excel will be done to the highest possible precision of the system, which is not related to the precision of the original data.
