David Giaretta Colorado Springs 16 Jan 2007 BNSC Agency Report David Giaretta Colorado Springs 16 Jan 2007

Funding UK Support for DAI-IPR comes from CASPAR (http://www.casparpreserves.eu) and DCC (http://www.dcc.ac.uk)

The CASPAR Consortium

Areas of interest IPR DAI Certification BoF

IPR XFDU and SIP work will be used within CASPAR as a packaging implementation Hope that Registry work should be compatible with CASPAR Registry

Certification BOF Needed for CASPAR validation

Rep. Info. Use and maintenance Looking at this view of the high level architecture, the lower left hand corner is about finding and using RepInfo, with a special mention of the role of a Registry (actually a system of registries) The rest of the diagram is about how to maintain RepInfo i.e. how to share the effort in identifying and creating RepInfo as it is needed

Registry for Representation Info The Digital Object could have RepInfo packed with it, as well as CPID 1 – User gets data from archive. Data has associated Curation Persistent Identifier (CPID) 1 2 – User unfamiliar with data so requests Rep.Info.using CPID 2 This gives an example of the way in which a Registry might be used. Note that the RepInfo may kept WITH the data in the archive. However we should look on this as a form of “caching” of the RepInfo. 3 – User receives Rep.Info – which has its own CPID in case it is not immediately usable 3 Support automated access & processing

Use of RepInfo DCC Label – points to other RepInfo CPID Structure = CPID Semantics = CPID Rendering s/w = CPID Each “bag of bits” has an associated pointer (CPID) to a Label CPID copy CPID Structure = CPID Semantics = CPID Rendering s/w = CPID Registry External

CASPAR information flow architecture Rep Info Introducing the layered view of CASPAR which points out that we need to deal with more than RepInfo e.g. Digital Rights etc. The items in the red ellipse are the RepInfo we have been talking about previously. The virtualisation is introduced in order to help with automation i.e. we need programmes to process the bytes – how can we make this easier? CASPAR information flow architecture

CASPAR architecture

DAI PAIMAS and PAIS will form basis of CASPAR ingest implementation

Accreditation/Certification for repositories Long-standing demand for ability to measure Trustability of digital repositories Part of OAIS “roadmap” RLG/NARA working group Version 1.0 Audit and Certification Checklist about to be released New open workgroup to produce ISO standard for Audit and Certification See http://mailman.ccsds.org/cgi-bin/mailman/listinfo/moims-rac to join mailing list Over 100 members in mailing list Wiki at http://wiki.digitalrepositoryauditandcertification.org

The CASPAR web site – important to stress collaboration with projects outside the CASPAR consortium. www.casparpreserves.eu

CASPAR Testbeds Three testbeds Cultural: UNESCO Performing Arts: INA , IRCAM Scientific: ESA and CCLRC Complex, multi-source, multifaceted data Many common preservation & evaluation & validation issues Some specific requirements on preservation (technical, delivery, legal) Specific user communities/ Knowledge bases Also test the OAIS model Now we introduce the Testbeds – noting that it is extremely important to look bottom up using a very wide range of examples. That is the particular strength of CASPAR – we have to look across a very wide range of disciplines. Clearly we aim at creating components which support not just Arts, Science and Heritage – we believe that what we produce should be much more broadly applicable.

Conclusions Information and Knowledge – needs more than just storing the “bits” Understanding and being able to process the vast amount of unfamiliar data which is available is hard It is expensive Costs must be shared So far the Open Archival Information Systems Reference Model provides conceptual framework Many similarities can be exploited Many subtleties need to be explored Watch this space

Backup slides

Science: CCLRC example World map of ionosondes The following few slides gives some examples of data – and it is important to stress that these are simply examples of graphical display of the data we are actually interested in.

Example of use of RepInfo Laser facility produces Binary data normally used by proprietary software Describe using EAST data description language Use in generic application (shown here) to display/process

Some Issues Difficult to derive physical quantities from data Can be analysed in multiple ways Raises fundamental questions about Representation Information Common automated method is proprietary Data structure also proprietary Paper documentation - restricted access Provenance and trust

ESA example GOME Global Ozone Monitoring Instrument on ERS-2 Ozone monitoring from space has a particular relevance because the early satellite (i.e. before GOME) data showed the Ozone hole but during the original processing it was assumed that this must be a problem with the instrument and a notional value was put in which hid the hole. Only when ground based measurements showed that there was a hole was the original satellite data reprocessed with the correct algorithm.

GOME data processing Complex processing chains are involved.

GOME Level 2 product: Ozone profile at given location GOME Level 3 product: Integration of time and space data GOME Level 4 product: Integration of GOME, other data and models

Some Issues Provenance and Context of processed data relationship to Representation Information of raw data and Knowledge base of Designated Community This raises some fundamental questions about what RepInfo actually means.

UNESCO examples World Heritage List DATA: Scanned documents and maps Mandatory Documentation: Identification of property Description of property Justification of inscription State of conservation and factors affecting the property Protection and Management Monitoring Documentation Contact information of responsible authorities Signature on behalf of the State Party(ies) DATA: Scanned documents and maps Aerial and close range photography (Digital photogrammetry) Monument measurements (Laser scanning) Satellite images (Remote sensing and image processing) Multi-scale digital cartography (Geographic information systems (GIS) and CAD) 3D models, virtual tours (Computer visualization) Note this included more “document” style objects.

Performing Arts examples Score MAX/MSP patches Additional instructions Figure 2: Preservation of interactive multimedia performances Motion Analysis and Recognition Motion-Multimedia Mapping Strategy Multimedia Generation GUI (For monitor & control) Motion Capture and Processing Motions 3D motion data Multimedia output Mapping Parameters

Some Issues What is Preservation of “performability”? Authenticity Composer’s intention Authenticity Proprietary software and hardware Copyright Digital Rights Management

Shared Infrastructure Registries of Representation Information Persistent Identifier name resolvers DOI? ARK? URL? – none are guaranteed Interfaces – support preservation and interoperability Standards – Preservation Description Information Fixity, Provenance, Reference, Context Identifying some of the common infrastructure which is needed for digital preservation