Information Lifecycle Management (ILM) is a general approach that seeks to optimise the information manipulation taking into account its changing value over time. ILM (Information Lifecycle Management) already exists in implicit form in every enterprise information system and affects a lot of industrial verticals. The implementation is a permanent optimisation process with parameters information value, security requirements, service-level agreements, and existing storage infrastructure. The ILM process begins as a strategic planning of a multi-step integration concept and leads to integrated architectures for cost optimised use of the enterprise intellectual capital. This long process can start with integration of ILM components in the most important applications. Final goal should be the transition to a fully integrated, automated ILM environment that covers the whole enterprise data.
Document Lifecycle Management (DLM) seeks to support the complete lifecycle of documents – from their creation through the use, storage, and archival till their removal. DLM is strongly influenced by the application area and represents an easy way for integration of ILM components in the distinct application systems.
Common functionality of existing ILM (Information Lifecycle Management) and DLM systems support only the main stations of underlying documents lifecycle. Most of them do not consider to a satisfying degree the changing value of documents over time or have a very simple lifecycle management. Efficient document lifecycle management must be application-centric and based on more parameters connected to business processes.
There are a lot of sources about ILM/DLM that describe the overall concept and provide few concrete solution details. This paper discusses an approach for Document Lifecycle Management in the area of Computer Aided Engineering (CAE). The lifecycle of such documents and the particularity of their use in the different phases of the whole process are the basis for document classification and policy definition. The procedures and policies must be CAE specific but at the same time conform to the strategic concept of ILM.
Information Lifecycle Management Defined
Information Lifecycle Management Implementation phases
ILM is a process that integrates a broad range of technologies including storage infrastructure, database and security, combined with automated policy management.
The introduction of an ILM concept can be completed in several phases:
- Analysis of the existing storage infrastructure
- Data classification
- Creation of storage tiers for the different data classes
- Policy definition (migration policies, data access policies, compliance policies).
A storage infrastructure based on intelligent storage networks (as Storage area networks – SAN, Network Attached Storage – NAS, IP storage) is the technological prerequisite for any solution. Storage parameters as capacity, load, and integration possibilities should be carefully analyzed. Storage resource consolidation also belongs to this phase.
There are different ways that data can be classified. The most common type of classification is by age or date, but other types are possible, such as by product or privacy. A hybrid classification allows the combination of more classification criteria. We will concentrate on a hybrid document classification that considers application specific, security, and time-based criteria.
After the data classification phase, the documents are assigned to different Service-Levels that correspond to different storage tiers: high performance storage tier (for active and frequently accessed documents), low cost storage tier (potentially active but less frequently accessed data), online archive storage tier (seldom accessed data), offline archive storage tier (documents removed from the online storage and stored XML format). Each storage tier utilizes appropriate storage devices of the underlying storage infrastructure.
Policies provide the right place and behaviour of data at each phase of its lifecycle. Data migration policies determine when data is migrated between the storage tiers. Data access policies implement changes of the ownership of the data and ensure that only authorized users may access it in the different phases of its lifetime. Compliance policies conform to regulatory requirements and may impose rules in the areas of data retention, immutability, privacy, auditing and expiration.