Information Lifecycles

This page describes the important steps in the creation, (re-)use and preservation of information.

There are a large number of models for the “data lifecycle”. The Data Life Cycle Models and Concepts (https://ceos.org/document_management/Working_Groups/WGISS/Interest_Groups/Data_Stewardship/White_Papers/WGISS_Data-Lifecycle-Models-And-Concepts.pdf ) collected together many data lifecycle models, and more recently Revisiting the Data Lifecycle with Big Data Curation https://core.ac.uk/download/pdf/162675829.pdf

All are some variation of the following, not necessarily sequential, steps:

• Planning

• Acquiring

• Processing

• Analysing

• Preserving

• Discovering

• Accessing

• Reusing/re-processing

• Combining

This list includes all the FAIR Principles.

Of primary importance in all these steps is what is generally called “metadata”. However it is important to use a more detailed taxonomy, including those terms defined in the OAIS Reference Model, in order to ensure that all the relevant types of metadata, with enough of each type, is collected along the way.

The document Information Preparation to Ensure Long Term Use (IPELTU), which is in the process of being standardized by CCSDS and ISO, provides checklists for every stage of data production and use to ensure that the appropriate types of metadata are collected. The way in which these pieces of information can be added, and preserved, in LABDRIVE will be described.

Ingestion

The important consideration when information is taken into the archive is that enough "metadata" must be collected in order to be ready to preserve, find and use that information. In particular enough must be collected to create the Archival Information Packages. These are described in Collecting Information needed for Re-Use and Preservation