This presentation was delivered by Simon Waddington from project partner King's College London during the PERICLES workshop entitled 'Appraisal, Quality Assurance and Risk Assessment in the Data Continuum'. The half-day workshop took place at IDCC on 25 February 2016 and presented the PERICLES approach to appraisal and quality assurance of complex digital objects. See more at: http://www.dcc.ac.uk/events/idcc16/workshops#Worskhop%209

1. GRANT AGREEMENT: 601138 | SCHEME FP7 ICT 2011.4.3
Promoting and Enhancing Reuse of Information throughout the Content Lifecycle taking account of Evolving
Semantics [Digital Preservation]
Simon Waddington (King’s College London)
IDCC, Amsterdam, 25 February 2016
Introduction to the PERICLES project

2. 9am
 Welcome
 Introduction to the aims of the session (5min) + Post-its
 Presentation of concepts and design ideas within the PERICLES model-driven approach
(25 min)
9:30am
 Presentation of technical appraisal methods and requirements for semi-automated
tools. (10 min)
 Policy implementation for automated change management and quality assurance. (20
min)
 Briefing and discussion on the breakout tasks, and introduce scenario. (10 min)
10.10am
 Coffee break
10:30am
 Review of post-its (5 min)
 Breakout groups to discuss
◦ Technical appraisal
◦ Quality assurance and application of policies
11:45am
 Collection of feedback from the groups with respect to practical implications of the
proposed approach
12pm -12:30pm
 Plenary discussion of different work group outcomes
 Summary and wrap-up


3.  The PERICLES project
 Project objectives
 Case studies
 Model-driven preservation
 Continuum approach

4.  PERICLES: " Promoting and Enhancing Reuse
of Information throughout the Content
Lifecycle taking account of Evolving
Semantics “
 EC FP7 Integrated Project, Digital Preservation
(Feb. 2013- Jan. 2017). 11 partners.

5.  Facilitate continued understanding, access to and
reuse of digital objects that are:
◦ heterogeneous, volatile, complex and highly interconnected
 Represent, derive and enforce policies that govern
◦ the management and evolution of content
◦ the management and evolution of the policies themselves
 Integrated test beds addressing different application
domains and users
◦ Use for prototyping and evaluation
 Sustainability of project outputs
◦ Gathering and disseminating the knowledge created by the project

6.  Capture and modelling of the environment
◦ Understand the wider context around digital objects that impacts their long-term
reuse
 Digital ecosystems
◦ Analogy with biological systems
◦ Evolving systems of interdependent entities
 Model-driven
◦ Abstraction of complex systems as models that can be manipulated independently
 Continuum approach
◦ Merging of active-life and archival phases
◦ Non-custodial
 Case studies
◦ Ensure relevance of results to practitioners. Should be extensible
◦ Used for requirements, test scenarios, evaluation, sample datasets

7.  Focuses on space science data
originating from the ESA and
International Space Station.
 For example
◦ Experiments that monitor the sun's
spectral variability to understand its
effects on climate (SOLAR)
 Raw data and telemetry are
captured by the SOLAR
instrument
 Data are calibrated by solar
scientists
 The final dataset is made
available to
◦ Scientists in other fields (e.g. climate)
◦ Users of other instruments

8. ISS SOLAR
instrument
B.USOC
Operations
centre
SOLAR
scientists
Other solar
scientists
Scientists in
other
disciplines
Raw data
and
telemetry
Filtered
SOLAR raw
data
Calibrated
SOLAR
data
Calibrated
data –
cross
instrument
Scientific
results in
other
disciplines
 Complex processing chain from data capture
to reuse by other scientific communities

9.  Software-based artworks
◦ Self-contained or networked systems
◦ Comprise hardware and software
elements
 Proprietary/open source/custom software
◦ Typically involve cutting edge
technology
 Unique and challenging to maintain
◦ Unlike physical artworks, often
necessary to replace elements
 Works can exist in multiple versions
◦ Synergies with the space science
experiments
 Complex dependencies
Sow Farm by John Gerrard
Brutalism, by Jose
Carlos Martinat

10.  Sampling-based approaches
◦ PLANETS
 Test bed – implement and evaluate potential changes on sample
sets of data
 Works well for individual objects – when we consider environment
there are many options
◦ SCAPE
 Scalable approach to PLANETS
 Descriptive models
◦ CASPAR
◦ TIMBUS
◦ Preservation Network Models
 PERICLES
◦ Build models automatically
◦ Use models for computation

11. SOLAR
experiment
 Data
 Applications
 Infrastructure

12.  Digital video playback
◦ Representation of a digital video resource
 Video artwork as an
aggregated resource
 Player dependency

13. ● Behavioural change
● E.g. technological change, organisational change, legal
frameworks, which have an impact on dependencies or
entities that may in turn affect other entities
● Semantic change
◦ E.g. User community knowledge and practices
● If significant change occurs, it may impair or
obstruct data reuse, access or interpretation

14. ● Relation between change and dependency
● Understanding dependencies between digital objects
and resources within their environment is the key to
assess and manage change
● Given objects A and B. A is dependent on B if changes to B
have a significant impact on the state of A, or if changes to B
can impact the ability to perform function X on A.”
Depends onEntity A Entity B

15.  "Digital Ecosystem" represents the surrounding
environment of a digital object that impacts reuse
 Digital ecosystem can include data objects,
software, user communities, processes, technical
services and their dependencies
 Scope
◦ The scope of the digital ecosystem depends on the
particular use case

16.  What is a model?
◦ Abstract representation (of some aspects) of a digital
ecosystem
◦ May only be approximate
 Behavioural modelling
◦ Encapsulation, visualisation
◦ Enable simulations, make predictions
 Knowledge modelling
● Enable continued understanding and interpretation
● Facilitate retrieval
 Reflexivity
 Modelling language
◦ Linked Resource Model (LRM)

18.  Reactive
◦ Implement changes when there is a known failure or
obsolescence (technology watch)
◦ Disadvantages
 Don’t enable forward planning or value assessment
 Could result in loss of availability if major actions are required
 Predictive
◦ Data-driven approaches to predicting change
◦ Estimate risk, proximity and impact
 Technological risk – often occurs rapidly
 User community change

19.  OAIS, DCC Lifecycle Model
◦ Clear separation between active life and appraisal
 In space science and time-based media,
active life and preservation intersect
◦ Space science experiments often run for decades
◦ Software based art is required for archival (e.g. reuse by
scholars) as well as periodic redisplay
 Non-custodial
◦ Don’t assume that assets are placed in custody of a third
party

20.  Contact: Simon Waddington
◦ simon.waddington@kcl.ac.uk
 Website
◦ http://pericles-project.eu/
 Public wiki
◦ https://projects.gwdg.de/projects/pericles-public/wiki
 Twitter
◦ https://twitter.com/PericlesFP7
 PERICLES Infrastructure Community of Practice