Plato: A Service Oriented Decision Support System
for Preservation Planning
Christoph Becker, Hannes Kulovits,
Andreas Rauber
Vienna University of Technology
Vienna, Austria
www.ifs.tuwien.ac.at/dp
ABSTRACT
The fast changes of technologies in today’s information landscape have considerably shortened the lifespan of digital objects. Digital preservation has become a pressing challenge.
Different strategies such as migration and emulation have
been proposed; however, the decision for a specific tool e.g.
for format migration or an emulator is very complex. The
process of evaluating potential solutions against specific requirements and building a plan for preserving a given set of
objects is called preservation planning. So far, it is a mainly
manual, sometimes ad-hoc process with little or no tool support. This paper presents a service-oriented architecture
and decision support tool that implements a solid preservation planning process and integrates services for content
characterisation, preservation action and automatic object
comparison to provide maximum support for preservation
planning endeavours.
Categories and Subject Descriptors
H.3 [Information Storage and Retrieval]: H.3.7 Digital
Libraries
General Terms
Design,Experimentation,Measurement,Standardization
Keywords
Digital Preservation, Preservation Planning, decision support system, service oriented architecture
1.
INTRODUCTION
Digital preservation as the effort to preserve digital objects for a given purpose over long periods of time has become a highly recognised matter during the last years. Its
urgency has recently been reemphasised by the results of a
survey among archiving professionals [11].
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Hans Hofman
Nationaal Archief
The Hague, The Netherlands
www.nationaalarchief.nl
The two most often considered strategies for preservation
actions today are migration and emulation. Migration operates on the objects that are at risk and transforms them to
representations that are considered to be better suited for
long-term archiving in a given context. Emulation operates
on the environment of the objects, trying to simulate the
original environment that the objects need.
A number of tools performing preservation actions are
available; most often, there is no optimal solution for preserving a given set of objects. Complex requirements need
to be considered during the process of deciding upon a solution to adopt. Careful documentation and a well-defined
procedure are necessary to ensure that the outcome of a
preservation planning activity meets the instution’s needs.
Preservation planning aids in the decision making process
by evaluating available solutions against clearly defined and
measurable criteria and arriving at concrete plans for action
based on these evaluation results. During this process, the
planner needs to be informed about possible actions that are
applicable to the objects at question. On the other hand,
a preferably automatic verification and comparison of documents and objects before and after migration (or during
emulation) is needed to support the judgement of quality
of the applied preservation actions in terms of defined requirements. Moreover, the planning activity needs to be repeatable and well-documented to ensure traceability of both
decisions and the reasons underlying them.
This paper presents the Planets preservation planning component (Plato) which implements the planning methodology [8] developed within the DELOS and Planets projects
and integrates services for content characterisation, preservation action and object comparison to provide a serviceoriented decision support system for preservation planning.
The remainder of this paper is structured as follows. The
next section outlines related work in the area of preservation
planning, content characterisation and distributed preservation services. Section 3 describes the planning tool Plato,
providing a walkthrough of the underlying workflow and
highlighting the integration of services. Section 4 draws conclusions and points out directions for future work.
2. RELATED WORK
Digital preservation has become a highly active research
area in the last decade, as many memory institutions realised
that their content will cease to be accessible within years[12].
At the heart of a preservation endeavour lies preservation
planning, which is a core entity in the Reference Model for
an Open Archival Information System, OAIS [4].
The PLANETS preservation planning methodology[8] defines measurable requirements for preservation strategies in
a hierarchical form and evaluates them in a standardised
setting to arrive at a recommendation for a solution. The
procedure is independent of the solutions considered; it can
be applied for any class of strategy, be it migration, emulation or different approaches, and has been validated in a
series of case studies [1, 9]. An OAIS-based analysis of the
approach is shown in [10].
An important aspect of the evaluation process is the need
for automatic validation and comparison of objects. A number of tools and services have been developed that perform
content characterisation specifically for digital preservation.
The National Library of New Zealand Metadata Extraction Tool1 extracts preservation metadata for various input file formats. Harvard University Library’s tool JHove2
enables the identification and characterisation of digital objects. Collection profiling services build upon characterisation tools and registries such as PRONOM3 to create profiles
of repository collections [3].
The eXtensible Characterisation Languages presented in
[2] support the automatic validation of document conversions and the evaluation of migration quality through a decomposition of digital objects into their elements, thus representing them in an abstract XML language.
Several approaches deal with distributed preservation architectures. Hunter [7] describes a distributed architecture
for preserving composite digital objects using ontologies and
web services. Ferreira [6] presents a system for performing
format migrations based on pre-specified requirements.
The EU project ‘Preservation and Long-Term Access via
Networked Services’ (PLANETS)4 is creating a distributed
service-oriented architecture as well as practical services and
tools for digital preservation [5]. Based on a common conceptual framework, it is developing services for preservation
action, characterisation, testing and planning, of which the
system presented in this paper forms part of.
3.
PLATO: PRESERVATION PLANNING
3.1 The preservation planning workflow
The Planets preservation planning workflow as described
in [8] consists of three main stages:
1. Requirements definition is the natural first step in
the planning procedure, collecting requirements from
the wide range of stakeholders and influence factors
that have to be considered for a given institutional
setting. This includes the involvement of curators and
domain experts as well as IT administrators and consumers. Requirements are specified in a quantifiable
way, starting at high-level objectives and breaking them
down into measurable criteria, thus creating an objective tree which forms the basis of the evaluation of
alternative strategies. Furthermore, as this evaluation
would be infeasible on the potentially very large collection of objects, the planner selects representative
sample objects that should cover the range of essential
characteristics present in the collection at hand.
1
http://meta-extractor.sourceforge.net/
http://hul.harvard.edu/jhove
3
http://www.nationalarchives.gov.uk/pronom
4
http://www.planets-project.eu
2
Figure 1: Preservation planning environment
2. The evaluation of potential strategies is carried
out empirically by applying selected tools to the defined sample content and evaluating the outcomes against
the specified requirements.
3. Analysis of the results takes into account the different weighting of requirements and allows the planner
to arrive at a well-informed recommendation for a solution to adopt.
3.2 The planning tool Plato
The planning tool presented here implements this threestage workflow and includes additional external services to
automate the process. It further extends it with a fourth
phase in which an executable preservation plan is created,
based on the well-documented recommendation. The software itself is a J2EE web application relying on open frameworks such as Java Server Faces and AJAX for the presentation layer and Enterprise Java Beans for the backend. It
is integrated in an interoperability framework that guarantees loose coupling of services and registries through standard interfaces and provides common services such as user
management, security, and a common workspace. Based on
this technical foundation, the aim is to create an interactive
and highly supportive software environment that advances
the insight of preservation planners and enables proactive
preservation planning.
Figure 1 illustrates the preservation planning environment,
putting the described workflow in the working context of services and registries as they are currently being implemented.
In principle, there are three aspects to consider: (1) Integrating registries for information discovery; (2) Integrating
Figure 2: Requirements definition in Plato
Figure 3: Visualisation of results
services for preservation action and characterisation of objects; and (3) Proactively supporting the planning with a
knowledge base that holds reusable patterns and templates
for requirements recurring in different planning situations.
The right choice of samples that are representative for the
collection under consideration is essential, as any skewed
representation might lead to wrong results. Collection
profiling services based on characterisation services and
format registries inform the selection process and ensure the
right stratification of samples. Risk assessment services
further assist by quantifying both the inherent risks of object
formats and the salient risks present in the objects which are
of particular relevance to a specific file format, such as the
number of pages for some document formats or the presence
of transparency layers in images.
The specification of requirements in a tree structure is
often done in a workshop setting. This is supported by both
a flexible web interface as depicted in Figure 2 and a direct
tree import from mind-mapping software5 . The knowledge
base provides recurring fragments and templates, such as
process requirements for an archival institution or essential
object characteristics for electronic documents in a library,
to assist in the process of tree creation.
Service discovery is the prime issue during the next step
of defining alternatives to consider for evaluation. Starting from the sample objects and their formats, the system
queries available registries of preservation actions and looks
up applicable tools such as emulators of the original environment or migration tools that can handle the provided input
format. The Planets registry moreover holds information on
benchmark evaluation results produced by experiments carried out in the Planets Testbed, which provides a controlled
environment for preservation experiments[5].
Preservation action tools that are accessible through a web
service are directly invoked during the execution of experiments on the sample objects; other tools such as emulators
have to be executed externally.
The evaluation of experiments is probably the most complex and, so far, least automated step in preservation planning. Until now, most of the judgement, e.g. if a migration
tool accurately preserves the colour model of an image or the
line breaks in a document, has to be carried out manually
by looking at the rendered objects. However, characterisation services are available that can measure some of the
essential characteristics of objects such as the dimensions
of images. In contrast to characterisation tools like JHove,
the extensible characterisation languages (XCL) [2] do not
attempt to extract a set of characteristics from a file, but instead are able to express the complete informational content
of a file in a format independent model.
Comparison services specify measurable properties as well
as property-specific metrics and their implementation as algorithms in order to identify degrees of equality between two
objects. This is in principle independent of the applied strategy, i.e. migration or emulation. The compared objects can
be both the original and a migrated object, or the original
object in two different environments. To allow comparison
and evaluation, a mapping is created between the requirements specified in the objective tree and the characteristics
that can be measured and compared automatically by the
available characterisation tools. This mapping partly stems
from the knowledge base, but can be adapted by the user.
Both XCL and other characterisation tools such as JHove
are integrated in the evaluation of experiments. This also includes risk assessment services which compare the risk scores
of objects resulting from the application of preservation actions against the scores of the original samples.
The transformation of measured values to a uniform scale
as needed for the aggregation of results and the importance
weighting of requirements are supported by the knowledge
base. Analysis of results is facilitated by a dynamic and
flexible visualisation as depicted in Figure 3, where the planner can choose between different aggregation methods and
dynamically configure the information content to analyse
the strengths and weaknesses of the alternatives considered.
Based on this analysis, a well-documented and solid recommendation for a solution can be made.
This recommendation forms the basis for building a preservation plan in the fourth stage. A preservation plan
contains a description of the context and the decision taken,
including the complete evidence base. This evidence base
comprises a thorough description of the planning context
5
http://freemind.sourceforge.net
and environment, ranging from the institution’s mission statement via user group characteristics and policies to the collection at hand (documented in a collection profile). Moreover it contains the chosen sample objects, the requirements
and additional documentation as well as considered solutions and the evaluation results. The plan furthermore contains cost indications and triggers for re-iterating the planning, and as a core part it entails a preservation action plan.
If the applied strategy and its deployment support it, this
is an executable workflow accessing distributed services.
During the fourth stage, the planner may select a subset
of the criteria used for evaluating solutions to be applied
automatically with each preservation action as a mechanism
for quality assurance. The corresponding characterisation
actions which are used for property extraction and validation
are then included in the executable preservation plan.
The first version of Plato is publicly accessible6 . It implements the workflow described in [8] and provides partial
service integration such as file format identification. The
next version will include a wider set of services for preservation actions and characterization, and result in a welldocumented preservation plan. The final version will then
include the creation of an executable preservation plan.
4.
DISCUSSION AND OUTLOOK
Until now, preservation planning is largely a manual and
tedious process where available solutions are evaluated against
the specific requirements of a particular situation. This paper described the basic architecture and features of a decision support system for preservation planning based on a
service oriented approach for distributed preservation solutions. The system implements a well-documented and
validated preservation planning methodology and integrates
registries and services for preservation action and characterisation. It furthermore provides a sophisticated web-based
interface for guiding the planner through the process.
Preservation action services are discovered in registries
and invoked through a BPEL-based workflow execution engine. The time-consuming and inherently subjective process
of evaluating the results is being objectified and automated
as far as possible by mapping identified requirements such as
essential characteristics of objects to properties that can be
automatically extracted and compared by characterisation
tools. A knowledge base supports the preservation planner
step by step in identifying requirements and mappings to
characteristics as well as transformation of the results and
importance weighting of the requirements.
Current and future work is aimed at the following aspects:
• Advanced collection profiling services that go beyond
the currently available solutions and deliver detailed
characteristics of the objects in a collection,
• Improving the automatic evaluation of preservation actions by integrating comparison services,
• Developing technology watch services that monitor the
environment and proactively trigger a planning activity, and
• Integrating recommender systems in order to provide
advanced decision support.
6
http://www.ifs.tuwien.ac.at/dp/plato
Acknowledgements
Part of this work was supported by the European Union in
the 6th Framework Program, IST, through the PLANETS
project, contract 033789.
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