1. Metadata for Large Science: The ICAT Data Model Brian Matthews, Leader, Scientific Applications Group, E-Science Centre, STFC Rutherford Appleton Laboratory brian.matthews@stfc.ac.uk

2. The ICAT software suite Catalogues all experiment related information Metadata gathered via integration with existing IT systems proposal systems data acquisition Provides a well defined API for easy embedding into any applications. Distributed Data Metadata Catalogue Generic Catalogue Access Interface Data Access and Analysis

3. Integrated e-Infrastructure Proposal Metadata Catalogue Information Experiment Data Acquisition System Secure Storage Data Analysis Publication E-Pubs Proposal System All Data and Metadata Capture is automated.

4. Model Motivation A common general format/standard for Scientific Studies and data holdings metadata did not exist By proposing Model and Implementation: –A specification for the types of metadata which should be captured during Scientific Studies –Cataloguing and organising data holdings: provide access for the Data Owner –Ease citation, collaboration, and integration –Allow easy Integration of distributed heterogeneous metadata systems into a homogeneous (virtual) Platform Therefore – The Common Scientific Metadata Model (CSMD) developed.

5. Core Scientific Metadata Model Metadata Granule Topic Study Description Access Conditions Data Location Data Description Keywords providing a index on what the study is about. Provenance about what the study is, who did it and when. Conditions of use providing information on who and how the data can be accessed. Detailed description of the organisation of the data into datasets and files. Locations providing a navigational aid to where the data on the study can be found. References into the literature and community providing context about the study. Related Material Legal Note Copyright, patents and conditions of use etc relating to the study and the data in the study.

6. Investigation PublicationKeywordTopic Sample Sample Parameter Dataset Dataset Parameter Datafile Datafile Parameter Investigator Reference / Proposal Id Previous Reference Facility Instrument Title Abstract Etc. Name Name/Units/Value etc Searchable Is Sample Parameter Is Dataset Parameter Is Datafile Parameter Verified Name Units String Value Numeric Value Range Top Range Bottom Error Full Reference URL Repository Name Parent Id Topic Level User Id Role Name Chemical Formula Safety Information Name Units String Value Numeric Value Range Top Range Bottom Error Name Sample Id Description Name Units String Value Numeric Value Range Top Range Bottom Error Name Description Version Location Format Format Version Create Time Modify Time Size Checksum Related Datafile Parameter Authorisation Source Datafile Id Destination Datafile Id Relation S/W Aplication S/W Version User Id Role e.g Admin, Deleter, Updater, Reader, Creater, Downloader etc. Element Type Element Id CSMD in more detail

7. CSMD Used on DataPortal Implementation used as Data Interface for DataPortal Single view of heterogeneous systems/schemas Acts as a stress test of the model –Limitations feed into Model Requirements –New requirements feed back into implementation

8. ICAT 3.3 Database Schema

9. Core Scientific Metadata Model Usage Used on many projects since 2001 –STFC ICat Serving data from STFC Facilities (ISIS, DLS) SNS, Canada, Australia –e-Minerals, e-Materials – collaborations to provide access to Grid resources – with ISIS users. Outside STFC MyGrid BioInformatics project –information model based on version 1 of the CSMD Model This is being taken in the myIB project –Application to Integrated biology –Extending to provenance tracking in computational steering Also influence projects: –Comb-eChem, eBank, eCrystals –NERC DataGrid CCP1(Collaborative Computational Project in Quantum Chemistry) –assessed CSMD for metadata needs on their Grid Data Management Middleware

10. Interoperability Sharing data across boundaries –Across different research lifecycles –Across institutions –Across information objects –Across disciplines –Across time Characteristics –Loosely coupled –Across different authorities –Different internal models Infrastructure to support science across disciplines, scientific institutions and research groups Interoperable Metadata Models as a way we can enable Interoperable Data

11. Publishing the CSMD Currently published as: ICAT 3.3 database schema ICAT API CCLRC Scientific Metadata Model: Version 2 -Sufi & Matthews 2004 UML Model XML Schema Need to update and formally publish Dublin Core Application Profile Sharable and collaborative A “flat” model An exchange model NameSubject Term URI http://www.stfc.ac.uk/csmd/elements/3.0/topic Refines http://purl.org/dc/elements/1.1/subject NameTopic Has Encoding Scheme DC Subject Encoding Schemes Has Encoding Scheme ISIS Subject Encoding Schemes Comment ISIS Subject Encoding Schemes are available from http://www.stfc.ac.uk/schemes/ISIS/Subject http://www.stfc.ac.uk/schemes/ISIS/Subject ObligationRecommended

12. Towards a Facilities Ontology Ontologies are used to capture knowledge about a domain of interest. Increased flexibility when representing frequently changing viewpoints. Alterations can be made in the model without changing applications. Allows a unified view of heterogeneous data sources. Remove conflicts and terminological uncertainties. Facilitate moderated searches, optimisation of results ISIS Ontology At present over 10,000 keywords describing experiments in ISIS ICAT Free text terms - NO Structure of keywords Organise and formalise into an ontology Map familiar terms in one domain to related terms in different domains Search data by category across studies Cross facility searching of related scientific data from the various scientific facilities e.g. CLF and DLS - elsewhere Some initial work in this area – Louisa Casely-Hayford Re NXDL

14. Sample, Investigator and Experiment Ontologies Sample Investigator Experiment

15. CSMD and Simulations Detailed Information about the Data Analysis and underpinning Computational Simulations: Simulation/Analysis Code and version Simulation Set-up and Parameters Information about the Compute Resource Key Parameter from the Simulation Results Keywords and Classifications Links to Analysed Secondary Data Currently limited support in the CSMD Could provide link to Software libraries.

16. Sharing Publications CSMD offers the potential to integrate the outputs of scientific research: data and publications. Institutional Repository s/w now very well established –ePrints, DSpace, Fedora, ePubs –Large body of expertise available –Standard metadata models and protocols: DC-APs, FRBR, OAI-PMH, OAI-ORE –Not yet embedded in science practise except HEP! Linking science data and publications –Not yet well established –Needs data Identifiers and citation DOIs, Data Journals –Needs peer review of data –Can (and should?) be done on a P2P basis

17. Issues on Metadata in EDNP Integration with other Projects and Facilities. – Interchangeable Metadata to do this – Providing the input tools – Providing the APIs – Providing the User Interfaces Data Policy and Ownership. Data and Metadata Curation for long-term reuse.

18. Questions? brian.matthews@stfc.ac.uk