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Metadata Standards and Adoption: Challenges and Solutions

This discussion explores the challenges of adopting metadata standards in data centers and the responsibilities of scientists. It emphasizes the need for cost-efficient tools and processes, prioritizing data and metadata, and customizing standards for different communities. The importance of ontology, profiles, and compliance with standards is also highlighted. Recommendations for metadata implementation and access are provided, along with the importance of outreach, user needs analysis, and engaging stakeholders.

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Metadata Standards and Adoption: Challenges and Solutions

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  1. Problems/Disc. • Adoption of standards • Should there be standards? • (not a big problem – responsibility lies with data centre – onus not on scientist) • (peer to peer relationships) • (there is an obligation on the scientists scientists – if we are to support interop, scientists need to play a role) • (Standards is a big word – at what level do we standardizing?) • (we assume that there will be funding to support scientists) • (need cost efficient dm – tools and process) • Many standards – set priorities – data, metadata, • Form that can be translated – ie. Profiles – customizing standards for a community – ‘recall – pdf means nothing to me’ – • Consider effort in translation – standardization • Problem def: governance in defining community profiles – paricularly in distributed environment - need to look at international standards – profiling – minimum standard where community agrees and ind. Projects go beyond • To practitioners, metadata can be overwhelming • Fitness for use is a critical element of metadata – no more, no less • Diff. Between producers vs. consumers in terms of how we create metadata • Look at ontology at multiple levels: top level, domain and application – top level critical for sharing in ip • Problem def: Shortcoming of standards upon implementation – maturity and issue • Local requirements re. Compliance with ‘profiles’, standards etc.

  2. We are missing content standards – without we limit higher level interoperability – separation of syntactical, schematic and semantic interop – need to do more about schematic and semantic • Need to establish what exists: NERC, WMO • Do we need stndrds?: how do we enforce? If you allow all formats – becomes less efficent – possibly loss of information. Carrots/sticks. • Differentiate between metadata and data • Concept of codes • Objective is to facilitate not introduce obstacles – as simple as possible/practical • Establish benefits to the science community and the managers , ipy program etc. • Legacy – bridge the gap between data and users • Metadata seem quite clear - – profile is an issue – minimum level • Minimum standard for content / metadata services are a separate issue • Validation is an issue – 19139 is a current limitation • Standardized schema (from profile) a goal (?) – includes development of dictionaries – user semantics key • Re. Geo-standards – need to deal with field based conceptualizations and processes • Coordinate systems – local systems need to be considered. • Can this group take these recommendations and implement – reference standards and reference implementations – capacity in community to adhere to standards, profiles

  3. Recommendations Metadata (Primary) a) What should be in the metadata? • Metadata standard – 19115 – minimum profile (DIF, DIF+) – schema (19139) • Examine next level – dictionaries • Consider DOI as a requirement? (Persistent ids) (related to legacy, archiving) b) How do we provide ‘access’ to metadata? • 1) Recommendations on implementation – i.e. support union mapproach etadata harvesting - OAI-PMH (Data Centres) • 2) Recommendations on development of higher level services i.e. OGC Catalogue Service Data interop (Secondary) • Recommendations i.e. WMS/WFS/WCS/SOS • Currently implemented in some projects may be appropriate for others or new projects • Services typically domain of data centres • Need clear architectural Diagram – Providers, Data Centres, Users (Infrastructure, Mediator, Interface) • Next stage: schemas, semantics etc., URI strategy Community Liaison • Outreach? How do we engage data managers, providers, users? “Light a candle” • Engage stakeholders (users, providers, data managers, general public etc.). User Needs Analysis? How?

  4. Part II • Elaborate on outreach • How do we sell and train? • Do we need to sell it? If people want to participate then they will ‘figure it out’ • How do we make it attractive? • Related – after IPY, who owns Intellectual or Real Property? Different for North and South (ATS) • Do we research DRM and overall ownership of IPY data management – can have an impact on how we standardize, adoption etc. – how does this fit with IPY philosophy. Particularly and issue with privately funded projects. • Who are the target of outreach activities? Data Centres (not just WDCs), Providers(funders including), end users, tool developers • Possible resource (OGC) • Sciences and society aspect • Need to consider users • Keep it simple for providers of data (i.e. scientists). Minimum amount required to facilitate incorporation into standards compliant infrastructure • Look to other initiatives – Marine Metadata Initiative • Potential outreach and una activities at conferences • As a data community, consider outreach as part of ongoing activities • Workshop including those projects including data management components? Questionnaire with modest number of questions? • Phases of outreach – 1) supporting establishment 2) promoting established program

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