SlideShare ist ein Scribd-Unternehmen logo
1 von 42
Downloaden Sie, um offline zu lesen
DATA
SUPPORT
OPEN
Training Module 1.4
Introduction to
metadata
management
PwC firms help organisations and individuals create the value they’re looking for. We’re a network of firms in 158 countries with close to 180,000 people who are committed to
delivering quality in assurance, tax and advisory services. Tell us what matters to you and find out more by visiting us at www.pwc.com.
PwC refers to the PwC network and/or one or more of its member firms, each of which is a separate legal entity. Please see www.pwc.com/structure for further details.
DATASUPPORTOPEN
This presentation has been created by PwC
Authors:
Makx Dekkers, Michiel De Keyzer, Nikolaos Loutas
and Stijn Goedertier
Presentation
metadata
Slide 2
Open Data Support is funded by
the European Commission
under SMART 2012/0107 ‘Lot
2: Provision of services for the
Publication, Access and Reuse of
Open Public Data across the
European Union, through
existing open data
portals’(Contract No. 30-CE-
0530965/00-17).
© 2014 European Commission
Disclaimers
1. The views expressed in this presentation are purely those of the authors and may not, in any
circumstances, be interpreted as stating an official position of the European Commission.
The European Commission does not guarantee the accuracy of the information included in this
presentation, nor does it accept any responsibility for any use thereof.
Reference herein to any specific products, specifications, process, or service by trade name,
trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement,
recommendation, or favouring by the European Commission.
All care has been taken by the author to ensure that s/he has obtained, where necessary,
permission to use any parts of manuscripts including illustrations, maps, and graphs, on which
intellectual property rights already exist from the titular holder(s) of such rights or from her/his
or their legal representative.
2. This presentation has been carefully compiled by PwC, but no representation is made or
warranty given (either express or implied) as to the completeness or accuracy of the information it
contains. PwC is not liable for the information in this presentation or any decision or
consequence based on the use of it.. PwC will not be liable for any damages arising from the use of
the information contained in this presentation. The information contained in this presentation is
of a general nature and is solely for guidance on matters of general interest. This presentation is
not a substitute for professional advice on any particular matter. No reader should act on the basis
of any matter contained in this publication without considering appropriate professional advice.
DATASUPPORTOPEN
Learning objectives
By the end of this training module you should have an understanding
of:
• What metadata is;
• The terminology and objectives of metadata management;
• The different dimensions of metadata quality;
• The use of controlled vocabularies for metadata;
• Metadata exchange and aggregation;
• Metadata management in Open Data Support.
Slide 3
DATASUPPORTOPEN
Content
This module contains ...
• An explanation of what is metadata;
• An outline of the metadata lifecycle;
• An introduction to metadata quality;
• An overview of the metadata management and exchange approach
implemented by Open Data Support through the Open Data
Interoperability Platform.
Slide 4
DATASUPPORTOPEN
What is metadata?
Definition, examples and reusable standards.
Slide 5
DATASUPPORTOPEN
What is metadata?
“Metadata is structured information that describes, explains, locates,
or otherwise makes it easier to retrieve, use, or manage an
information resource. Metadata is often called data about data or
information about information.”
-- National Information Standards Organization
http://www.niso.org/publications/press/UnderstandingMetadata.pdf
Metadata provides information enabling to make sense of data (e.g.
documents, images, datasets), concepts (e.g. classification schemes)
and real-world entities (e.g. people, organisations, places, paintings,
products).
Slide 6
DATASUPPORTOPEN
Types of metadata
• Descriptive metadata, describe a resource for purposes of
discovery and identification.
• Structural metadata, e.g. data models and reference data.
• Administrative metadata, provides information to help manage
a resource.
Slide 7
In this tutorial we are focusing mainly on descriptive metadata
for datasets.
Administrative metadata is also partly covered.
DATASUPPORTOPEN
Examples of metadata
Slide 8
Can
Book
Dataset
Label
Catalogue card
Dataset description (DCAT)
Provides metadata on
DATASUPPORTOPEN
Two approaches for providing metadata on the
Web
XML (Tree/container approach) RDF (Triple-based approach)
Slide 9
DATASUPPORTOPEN
Managing the
metadata of your
datasets
Slide 10
DATASUPPORTOPEN
Metadata management is important
Metadata needs to be managed to ensure ...
• Availability: metadata needs to be stored where it can be accessed and
indexed so it can be found.
• Quality: metadata needs to be of consistent quality so users know that it can
be trusted.
• Persistence: metadata needs to be kept over time.
• Open License: metadata should be available under a public domain license
to enable its reuse.
The metadata lifecycle is larger than the data lifecycle:
• Metadata may be created before data is created or captured, e.g. to
inform about data that will be available in the future.
• Metadata needs to be kept after data has been removed, e.g. to inform
about data that has been decommissioned or withdrawn.
Slide 11
DATASUPPORTOPEN
Metadata schema
“A labelling, tagging or coding system used for recording cataloguing
information or structuring descriptive records. A metadata schema
establishes and defines data elements and the rules governing the use
of data elements to describe a resource.”
Slide 12
RDF
Schema
XML
Schema
DATASUPPORTOPEN
Reuse existing vocabularies for providing
metadata to your resources
General purpose standards and specifications:
• Dublin Core for published material (text, images),
http://dublincore.org/documents/dcmi-terms/
• FOAF for people and organisations, http://xmlns.com/foaf/spec/
• SKOS for concept collections, http://www.w3.org/TR/skos-reference
• ADMS for interoperability assets, http://www.w3.org/TR/vocab-adms/
Specific standard for datasets:
• Data Catalog Vocabulary DCAT, http://www.w3.org/TR/vocab-dcat/
Specific usage of DCAT and other vocabularies to support
interoperability of data portals across Europe:
• DCAT application profile for data portals in Europe,
http://joinup.ec.europa.eu/asset/dcat_application_profile/description
Slide 13
DATASUPPORTOPEN
Designing your metadata schema with RDF
Schema (RDFS) – reuse where possible
RDF schema is particularly good in combining terms from different
standards and specifications.
Slide 14
Do not re-invent terms that are
already defined somewhere else ,
when designing RDF schemas –
reuse terms where possible.
 For example, the DCAT
Application Profile for data
portals in Europe (DCAT-AP)
reuses terms from DCAT,
Dublin Core, FOAF, SKOS,
ADMS and others.
DATASUPPORTOPEN
Example: description of an open dataset with the
DCAT-AP
Description of the
Catalogue
Description of the
Dataset
Description of the
Distribution
Slide 15
DATASUPPORTOPEN
Controlled
vocabularies
Using thesauri, taxonomies and standardised lists of terms
for assigning values to metadata properties.
Slide 16
DATASUPPORTOPEN
What are controlled vocabularies?
A controlled vocabulary is a predefined list of values to be used as
values for a specific property in your metadata schema.
• In addition to careful design of schemas, the value spaces of metadata
properties are important for the exchange of information, and thus
interoperability.
• Common controlled vocabularies for value spaces make metadata
understandable across systems.
Slide 17
DATASUPPORTOPEN
Which controlled vocabulary to be used for which
type of property
• Use code lists as controlled
vocabulary for free text or
“string” properties.
• Example DCAT-AP property:
• Example code list -
ObjectInCrimeClass (ListPoint)
• Use concepts identified by a
URI for reference to “things”.
• Example DCAT-AP property:
• Example taxonomy with terms
having a URI - EuroVoc
Slide 18
DATASUPPORTOPEN
Example –Publications Office’s Named Authority
Lists
• The Named Authority Lists offer
reusable controlled vocabularies
for:
 Countries
 Corporate bodies
 File types
 Interinstitutional procedures
 Languages
 Multilingual
 Resource types
 Roles
 Treaties
Slide 19
DATASUPPORTOPEN
The metadata
lifecycle
Creating, maintaining, updating, storing, publishing
metadata and handling deletion of data.
Slide 20
DATASUPPORTOPEN
Creating your metadata
Metadata creation can be supported by (semi-)automatic processes.
• Document properties generated in (office) tools, e.g. creation date.
• Spatial and temporal information captured by cameras, sensors...
• Information from publication workflow, e.g. file location or URL
However, other characteristics require human intervention:
• What is the resource about (e.g. linking to a subject vocabulary)?
• How can the resource be used (e.g. linking to a licence)?
• Where can I find more information about this resource (e.g. linking
to a Web site or documentation that describes the resource)?
• How can quality information be included?
Slide 21
DATASUPPORTOPEN
Maintaining your metadata
Approaches for maintaining metadata need to be appropriate for the
type of data that is being published.
• If data does not change, metadata can be relatively stable.
Changes (bulk conversions) can take place off-line when needed.
• If data changes frequently (e.g. real-time sensor data), metadata
needs to be closely coupled to the data workflow and changes need
to be practically instantaneous.
Slide 22
DATASUPPORTOPEN
Updating your metadata – planning for change
Metadata operates in a global context that is subject to change!
• Organisation – departments are established, merge with others,
responsibilities are handed over.
• Usage of the data – new applications emerge around data.
• Reference data – controlled vocabularies evolve and get linked.
• Data standards and technologies – technology lifecycle is getting
shorter all the time; what will tomorrow’s Web look like?
• Tools and systems – evolution of storage, bandwidth, mobile...
Metadata needs to be kept up-to-date to the extent possible, taking into
account the available time and budget.
Slide 23
DATASUPPORTOPEN
Storing your metadata – what are the options?
Depending on operational requirements, metadata can be embedded
with the data or stored separately from the data.
• Embedding the metadata in the data (e.g. office documents, MP3,
JPG, RDF data) embedding makes data exchange easier.
• Separating metadata from data (e.g. in a database), with links to
corresponding data files makes management easier.
Depending on the availability of tools and requirements on
performance and capacity, metadata can be stored in a ‘classic’
relational database or an RDF triple store.
Slide 24
DATASUPPORTOPEN
Handling deletions of data
In many cases, metadata must survive even after deletion of the data
it describes.
Decommissioning or deletion of data happens, for example:
• When data is no longer necessary.
• When data is no longer valid.
• When data is wrong.
• When data is withdrawn by the owner/publisher
In that case the metadata should, contain information that the data was
deleted, and if it was archived, how and where an archival copy can be
requested.
Slide 25
DATASUPPORTOPEN
Publishing your metadata – what are the options?
• ‘Open’ publication: direct access on URIs
- This is the option most in line with the vision of Linked Open Data
and allows the ‘follow-your-nose’ principle.
• Make your metadata available through a SPARQL endpoint
- This allows external systems to send queries to an RDF triple store.
- Requires knowledge about the schema used in the triple store.
• Deferred publication: access to exported file in RDF
- Produced by converting non-RDF data to RDF.
- Allows off-line bulk harvesting and caching of data collections.
- Allows implementation of access control.
Slide 26
See also:
http://www.slideshare.net/OpenDataSupport
/licence-your-data-metadata
DATASUPPORTOPEN
Metadata quality
The quality and completeness of the description metadata
of your datasets, directly affects their searchability and
reuse.
Slide 27
DATASUPPORTOPEN
Metadata quality is about... (1/3)
• The accuracy of your metadata - are the characteristics of the
resource correctly reflected?
- e.g. indicating the right title, the right license, the right publisher enables
users to discover resources that they need.
• The availability of your metadata – can the metadata be accessed
now and over time into the future?
- e.g. making it available for indexing and downloading, and include it in
in a regular back-up process.
• The completeness of your metadata – are all relevant
characteristics of the resource captured (as far as practically and
economically feasible and necessary for the application)?
- e.g. indicating the licence that governs reuse or the format of the
distribution enables filters on those aspects.
Slide 28
See also:
http://www.slideshare.net/OpenDataSupport/open-data-quality
DATASUPPORTOPEN
Metadata quality is about ... (2/3)
• The conformance of your metadata to accepted standards – is the
metadata conforming to a specific metadata standard or an
Application Profile?
- e.g. the description of a dataset conforms to the DCAT-AP.
• The consistency of your metadata – does the data not contain
contradictions?
- e.g. not having multiple and contradictory license statements for the
same piece of data.
• The credibility and provenance of your metadata – is the
metadata based on trustworthy sources?
- e.g. linking to reference data published and managed by a stable
organisation (e.g. the EU Publications Office).
Slide 29
DATASUPPORTOPEN
Metadata quality is about ... (3/3)
• The processability of the metadata – is the metadata properly
machine-readable?
- e.g. making the metadata of a dataset available in RDF and/or XML, and
not as free text.
• The relevance of the metadata – does the metadata contain the
right amount of information for the task at hand?
- e.g. limit the information to optimally serve the users’ needs.
• The timeliness of your metadata – is the metadata corresponding to
the actual (current) characteristics of the resource and is it published
soon enough?
- e.g. indicating the last modification date of the resource, thus making
sure the metadata is fresh so that users will see the latest information.
Slide 30
DATASUPPORTOPEN
Exchanging
metadata of datasets
Mapping your metadata to a common metadata
vocabulary, such as the DCAT-AP, and exchanging the
metadata across platforms.
Slide 31
DATASUPPORTOPEN
Homogenising metadata
When exchanged between systems, metadata should be mapped to a
common model so that the sender and the recipient share a common
understanding on the meaning of the metadata.
• On the schema level metadata coming from different sources can be based
on different metadata schemas, e.g. DCAT, schema.org, CERIF, own
internal model...
• On the data (value) level, the metadata properties should be assigned
values from different controlled vocabularies or syntaxes, e.g.:
- Language: English can be expressed as
http://publications.europa.eu/resource/authority/language/ENG or as
http://id.loc.gov/vocabulary/iso639-1/en
- Dates: ISO8601 (“20130101”) versus W3C DTF (“2013-01-01”)
Slide 32
DATASUPPORTOPEN
Example: Homogenising metadata about datasets
The DCAT Application Profile for data portals in Europe
The DCAT-AP can
be used as the
common model for
exchanging
metadata with open
data platforms
across Europe
and/or with a data
broker (e.g. The
Open Data
Interoperability
Platform - ODIP).
Slide 33
EXPLORE
FIND
IDENTIFY
SELECT
OBTAIN
Public admi nistrations
Busi nesses
Standar disation bodi es
Academia
Data Portal
Data Portal
Data Portal
Data Portal
Data Portal
Data Portal
Metadata
Broker
Data
Consumers
See also:
http://joinup.ec.europa.eu/asset/dcat_application_profile/home
DATASUPPORTOPEN
Mapping example – data.gov.uk
Slide 34
dct:title (Dataset)
dct:description
dct:publisher
dct:title (Distribution)
Dcat:accessURL
dct:language
dcat:keyword
dct:license
dcat:downloadURL, dct:issued,
dct:format, dct: description
dct:spatial
dct:theme
dct:issued
dct:modified
adms:contactPoint
dct:temporal
DATASUPPORTOPEN
What can the Open Data Interoperability Platform
do?
• Harvest metadata from an Open
Data portal.
• Transform the metadata to RDF.
• Harmonise the RDF metadata
produced in the previous steps with
DCAT-AP.
• Validate the harmonised metadata
against the DCAT-AP.
• Publish the description metadata as
Linked Open Data.
Slide 35
ODIPP
Pan-European
Data portal
See also:
http://www.slideshare.net/OpenDataSupport/promoting-the-re-use-
of-open-data-through-odip
DATASUPPORTOPEN
Conclusions
• Metadata provides information on your data and resources. The
quality of the metadata directly affects the discoverability and reuse
of your the resources.
• A structured approach should be followed for metadata management.
• The metadata lifecycle extends the lifecycle of datasets (metadata
before publication and after deletion).
• Homogenised metadata enable the operation of metadata brokers,
which can in turn lower the access barriers to your resources, leading
to improved visibility and discoverability, and thus increasing their
reuse potential.
Slide 36
DATASUPPORTOPEN
Group exercise and questions
Slide 37
In groups of two, select one dataset from your country and
describe it with the DCAT Application Profile.
Does your organisation have a minimum set of metadata to be
provided together with Open Data?
What would be the main barriers, according to you, for the
(re)use of standard controlled vocabularies in your metadata?
Do you have any data and/or metadata governance
methodology at the corporate level?
http://www.visualpharm.com
http://www.visualpharm.com
http://www.visualpharm.com
http://www.visualpharm.com
Take also the online test here!
DATASUPPORTOPEN
Thank you!
...and now YOUR questions?
Slide 38
DATASUPPORTOPEN
References
Slide 6, 7:
• NISO. Understanding Metadata.
http://www.niso.org/publications/press/UnderstandingMetadata.pdf
Slide 9:
• Dublin City University. Chapter 3: Introduction to XML.
http://wiki.eeng.dcu.ie/ee557/g2/326-EE.html
• W3C. RDF Primer. http://www.w3.org/TR/rdf-primer/
Slide 12:
• http://gondolin.rutgers.edu/MIC/text/how/catalog_glossary.htm
• Dublin Core. Example XML Schema.
http://dublincore.org/schemas/xmls/qdc/dc.xsd
• Dublin Core, Example RDF Schema.
http://dublincore.org/2012/06/14/dcterms.rdf
Slide 14, 33:
• The ISA Programme. DCAT Application Profile for Data Portals in Europe - Final
Draft.
https://joinup.ec.europa.eu/asset/dcat_application_profile/asset_release/dcat-
application-profile-data-portals-europe-final-draf
Slide 18:
• ListPoint. ObjectInCrimeClass.
http://www.listpoint.co.uk/CodeList/details/ObjectInCrimeClass/1.2/1
Slide 19:
• Publications Office. Countries Name Authority List. http://open-
data.europa.eu/en/data/dataset/2nM4aG8LdHG6RBMumfkNzQ
Slide 39
DATASUPPORTOPEN
Further reading
Understanding Metadata, NISO.
http://www.niso.org/publications/press/UnderstandingMetadata.pdf
Ben Jareo and Malcolm Saldanha. The value proposition of a
metadata driven data governance program. Best Practices Metadata.
May 2012.
https://community.informatica.com/mpresources/Communities/IW2
012/Docs/bos_30.pdf
John R. Friedrich, II. Metadata Management Best Practices and
Lessons Learned. The 10th Annual Wilshire Meta-Data Conference
and the 18th Annual DAMA International Symposium. April 2006.
http://www.metaintegration.net/Publications/2006-Wilshire-DAMA-
MetaIntegrationBestPractices.pdf
Slide 40
DATASUPPORTOPEN
Related initiatives
Metadata Management. Trainer screencasts,
http://managemetadata.com/screencasts/msa/
MIT Libraries. Data Management and Publishing. Reasons to Manage
and Publish Your Data, http://libraries.mit.edu/guides/subjects/data-
management/why.html
ISA Programme. DCAT Application Profile for European Data Portals,
https://joinup.ec.europa.eu/asset/dcat_application_profile/descripti
on
Generating ADMS-based descriptions of assets using Open Refine
RDF, https://joinup.ec.europa.eu/asset/adms/document/generate-
adms-asset-descriptions-spreadsheet-refine-rdf
The Dublin Core Medatata Initiative, http://dublincore.org/
Slide 41
DATASUPPORTOPEN
Be part of our team...
Find us on
Contact us
Join us on
Follow us
Open Data Support
http://www.slideshare.net/OpenDataSupport
http://www.opendatasupport.euOpen Data Support
http://goo.gl/y9ZZI
@OpenDataSupport contact@opendatasupport.eu
Slide 42

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (20)

Introducation to metadata
Introducation to metadataIntroducation to metadata
Introducation to metadata
 
Metadata: A concept
Metadata: A conceptMetadata: A concept
Metadata: A concept
 
Dspace software
Dspace softwareDspace software
Dspace software
 
Metadata
MetadataMetadata
Metadata
 
Metadata
MetadataMetadata
Metadata
 
Digital Preservation
Digital PreservationDigital Preservation
Digital Preservation
 
Introduction to subject cataloguing
Introduction to subject cataloguingIntroduction to subject cataloguing
Introduction to subject cataloguing
 
Metadata standards
Metadata standardsMetadata standards
Metadata standards
 
Metadata harvesting
Metadata harvestingMetadata harvesting
Metadata harvesting
 
Metadata Use Cases You Can Use
Metadata Use Cases You Can UseMetadata Use Cases You Can Use
Metadata Use Cases You Can Use
 
Z39.50: Information Retrieval protocol ppt
Z39.50: Information Retrieval protocol pptZ39.50: Information Retrieval protocol ppt
Z39.50: Information Retrieval protocol ppt
 
Data Catalog for Better Data Discovery and Governance
Data Catalog for Better Data Discovery and GovernanceData Catalog for Better Data Discovery and Governance
Data Catalog for Better Data Discovery and Governance
 
Dspace
DspaceDspace
Dspace
 
Marc 21
Marc 21Marc 21
Marc 21
 
Introduction to DSpace
Introduction to DSpaceIntroduction to DSpace
Introduction to DSpace
 
Big Data Analytics with Hadoop
Big Data Analytics with HadoopBig Data Analytics with Hadoop
Big Data Analytics with Hadoop
 
Dublin core Presentation
Dublin core PresentationDublin core Presentation
Dublin core Presentation
 
Data Warehouse Architectures
Data Warehouse ArchitecturesData Warehouse Architectures
Data Warehouse Architectures
 
Introduction to Data Engineering
Introduction to Data EngineeringIntroduction to Data Engineering
Introduction to Data Engineering
 
Digital preservation
Digital preservationDigital preservation
Digital preservation
 

Andere mochten auch

Metadata an overview
Metadata an overviewMetadata an overview
Metadata an overviewrobin fay
 
Metadata in data warehouse
Metadata in data warehouseMetadata in data warehouse
Metadata in data warehouseSiddique Ibrahim
 
What is Metadata?
What is Metadata?What is Metadata?
What is Metadata?Adgistics
 
Taxonomies and Metadata in Information Architecture
Taxonomies and Metadata in Information ArchitectureTaxonomies and Metadata in Information Architecture
Taxonomies and Metadata in Information ArchitectureAccess Innovations, Inc.
 
Introduction to Dublin Core Metadata
Introduction to Dublin Core MetadataIntroduction to Dublin Core Metadata
Introduction to Dublin Core MetadataHannes Ebner
 
Metadata For Catalogers (introductions)
Metadata For Catalogers (introductions)Metadata For Catalogers (introductions)
Metadata For Catalogers (introductions)robin fay
 
Metadata is a Love Note to the Future
Metadata is a Love Note to the FutureMetadata is a Love Note to the Future
Metadata is a Love Note to the FutureRachel Lovinger
 
The linked open government data and metadata lifecycle
The linked open government data and metadata lifecycleThe linked open government data and metadata lifecycle
The linked open government data and metadata lifecycleOpen Data Support
 
Promoting the re use of open data through ODIP
Promoting the re use of open data through ODIPPromoting the re use of open data through ODIP
Promoting the re use of open data through ODIPOpen Data Support
 
Unleashing the value of metadata with Talend
Unleashing the value of metadata with Talend Unleashing the value of metadata with Talend
Unleashing the value of metadata with Talend Jean-Michel Franco
 
Web Application Performance
Web Application PerformanceWeb Application Performance
Web Application PerformanceCodeFireTech
 
Implementing Effective Data Governance
Implementing Effective Data GovernanceImplementing Effective Data Governance
Implementing Effective Data GovernanceChristopher Bradley
 
Review of Data Management Maturity Models
Review of Data Management Maturity ModelsReview of Data Management Maturity Models
Review of Data Management Maturity ModelsAlan McSweeney
 
Successful Content Management Through Taxonomy And Metadata Design
Successful Content Management Through Taxonomy And Metadata DesignSuccessful Content Management Through Taxonomy And Metadata Design
Successful Content Management Through Taxonomy And Metadata Designsarakirsten
 
Metadata Strategies
Metadata StrategiesMetadata Strategies
Metadata StrategiesDATAVERSITY
 

Andere mochten auch (20)

Metadata an overview
Metadata an overviewMetadata an overview
Metadata an overview
 
Metadata Workshop
Metadata WorkshopMetadata Workshop
Metadata Workshop
 
Metadata in Business Intelligence
Metadata in Business IntelligenceMetadata in Business Intelligence
Metadata in Business Intelligence
 
Metadata in data warehouse
Metadata in data warehouseMetadata in data warehouse
Metadata in data warehouse
 
What is Metadata?
What is Metadata?What is Metadata?
What is Metadata?
 
Taxonomies and Metadata in Information Architecture
Taxonomies and Metadata in Information ArchitectureTaxonomies and Metadata in Information Architecture
Taxonomies and Metadata in Information Architecture
 
Does metadata matter?
Does metadata matter?Does metadata matter?
Does metadata matter?
 
Taxonomy And Metadata
Taxonomy And MetadataTaxonomy And Metadata
Taxonomy And Metadata
 
Introduction to Dublin Core Metadata
Introduction to Dublin Core MetadataIntroduction to Dublin Core Metadata
Introduction to Dublin Core Metadata
 
Metadata For Catalogers (introductions)
Metadata For Catalogers (introductions)Metadata For Catalogers (introductions)
Metadata For Catalogers (introductions)
 
Metadata is a Love Note to the Future
Metadata is a Love Note to the FutureMetadata is a Love Note to the Future
Metadata is a Love Note to the Future
 
The linked open government data and metadata lifecycle
The linked open government data and metadata lifecycleThe linked open government data and metadata lifecycle
The linked open government data and metadata lifecycle
 
Promoting the re use of open data through ODIP
Promoting the re use of open data through ODIPPromoting the re use of open data through ODIP
Promoting the re use of open data through ODIP
 
JOSA TechTalk: Metadata Management
in Big Data
JOSA TechTalk: Metadata Management
in Big DataJOSA TechTalk: Metadata Management
in Big Data
JOSA TechTalk: Metadata Management
in Big Data
 
Unleashing the value of metadata with Talend
Unleashing the value of metadata with Talend Unleashing the value of metadata with Talend
Unleashing the value of metadata with Talend
 
Web Application Performance
Web Application PerformanceWeb Application Performance
Web Application Performance
 
Implementing Effective Data Governance
Implementing Effective Data GovernanceImplementing Effective Data Governance
Implementing Effective Data Governance
 
Review of Data Management Maturity Models
Review of Data Management Maturity ModelsReview of Data Management Maturity Models
Review of Data Management Maturity Models
 
Successful Content Management Through Taxonomy And Metadata Design
Successful Content Management Through Taxonomy And Metadata DesignSuccessful Content Management Through Taxonomy And Metadata Design
Successful Content Management Through Taxonomy And Metadata Design
 
Metadata Strategies
Metadata StrategiesMetadata Strategies
Metadata Strategies
 

Ähnlich wie Introduction to metadata management

Design and manage persistent URIs
Design and manage persistent URIsDesign and manage persistent URIs
Design and manage persistent URIsOpen Data Support
 
Designing and developing vocabularies in RDF
Designing and developing vocabularies in RDFDesigning and developing vocabularies in RDF
Designing and developing vocabularies in RDFOpen Data Support
 
Linked Open Data Principles, Technologies and Examples
Linked Open Data Principles, Technologies and ExamplesLinked Open Data Principles, Technologies and Examples
Linked Open Data Principles, Technologies and ExamplesOpen Data Support
 
Llinked open data training for EU institutions
Llinked open data training for EU institutionsLlinked open data training for EU institutions
Llinked open data training for EU institutionsOpen Data Support
 
Data Management Plans: a gentle introduction
Data Management Plans: a gentle introductionData Management Plans: a gentle introduction
Data Management Plans: a gentle introductionMartin Donnelly
 
FAIR data: what it means, how we achieve it, and the role of RDA
FAIR data: what it means, how we achieve it, and the role of RDAFAIR data: what it means, how we achieve it, and the role of RDA
FAIR data: what it means, how we achieve it, and the role of RDASarah Jones
 
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...EUDAT
 
Modeling Data Life Cycles with PROV
Modeling Data Life Cycles with PROVModeling Data Life Cycles with PROV
Modeling Data Life Cycles with PROVEUDAT
 
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...EUDAT
 
Keynote Presentation at MTSR07
Keynote Presentation at MTSR07Keynote Presentation at MTSR07
Keynote Presentation at MTSR07Gauri Salokhe
 
Information landscapes – modelling your information assets (part 1 – as is)
Information landscapes – modelling your information assets (part 1 – as is)Information landscapes – modelling your information assets (part 1 – as is)
Information landscapes – modelling your information assets (part 1 – as is)Metataxis
 
Intro to Data Management Plans
Intro to Data Management PlansIntro to Data Management Plans
Intro to Data Management PlansSarah Jones
 
Linking HPC to Data Management - EUDAT Summer School (Giuseppe Fiameni, CINECA)
Linking HPC to Data Management - EUDAT Summer School (Giuseppe Fiameni, CINECA)Linking HPC to Data Management - EUDAT Summer School (Giuseppe Fiameni, CINECA)
Linking HPC to Data Management - EUDAT Summer School (Giuseppe Fiameni, CINECA)EUDAT
 
The state of global research data initiatives: observations from a life on th...
The state of global research data initiatives: observations from a life on th...The state of global research data initiatives: observations from a life on th...
The state of global research data initiatives: observations from a life on th...Projeto RCAAP
 
Data Management and Horizon 2020
Data Management and Horizon 2020Data Management and Horizon 2020
Data Management and Horizon 2020Sarah Jones
 
OpenAIRE webinar on Open Research Data in H2020 (OAW2016)
OpenAIRE webinar on Open Research Data in H2020 (OAW2016)OpenAIRE webinar on Open Research Data in H2020 (OAW2016)
OpenAIRE webinar on Open Research Data in H2020 (OAW2016)OpenAIRE
 

Ähnlich wie Introduction to metadata management (20)

Design and manage persistent URIs
Design and manage persistent URIsDesign and manage persistent URIs
Design and manage persistent URIs
 
Designing and developing vocabularies in RDF
Designing and developing vocabularies in RDFDesigning and developing vocabularies in RDF
Designing and developing vocabularies in RDF
 
Linked Open Data Principles, Technologies and Examples
Linked Open Data Principles, Technologies and ExamplesLinked Open Data Principles, Technologies and Examples
Linked Open Data Principles, Technologies and Examples
 
What is a DMP
What is a DMPWhat is a DMP
What is a DMP
 
Llinked open data training for EU institutions
Llinked open data training for EU institutionsLlinked open data training for EU institutions
Llinked open data training for EU institutions
 
Introduction to linked data
Introduction to linked dataIntroduction to linked data
Introduction to linked data
 
Data Management Plans: a gentle introduction
Data Management Plans: a gentle introductionData Management Plans: a gentle introduction
Data Management Plans: a gentle introduction
 
FAIR data: what it means, how we achieve it, and the role of RDA
FAIR data: what it means, how we achieve it, and the role of RDAFAIR data: what it means, how we achieve it, and the role of RDA
FAIR data: what it means, how we achieve it, and the role of RDA
 
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...
 
Intro to RDM
Intro to RDMIntro to RDM
Intro to RDM
 
NISO/DCMI Webinar: Metadata for Public Sector Administration
NISO/DCMI Webinar: Metadata for Public Sector AdministrationNISO/DCMI Webinar: Metadata for Public Sector Administration
NISO/DCMI Webinar: Metadata for Public Sector Administration
 
Modeling Data Life Cycles with PROV
Modeling Data Life Cycles with PROVModeling Data Life Cycles with PROV
Modeling Data Life Cycles with PROV
 
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...
 
Keynote Presentation at MTSR07
Keynote Presentation at MTSR07Keynote Presentation at MTSR07
Keynote Presentation at MTSR07
 
Information landscapes – modelling your information assets (part 1 – as is)
Information landscapes – modelling your information assets (part 1 – as is)Information landscapes – modelling your information assets (part 1 – as is)
Information landscapes – modelling your information assets (part 1 – as is)
 
Intro to Data Management Plans
Intro to Data Management PlansIntro to Data Management Plans
Intro to Data Management Plans
 
Linking HPC to Data Management - EUDAT Summer School (Giuseppe Fiameni, CINECA)
Linking HPC to Data Management - EUDAT Summer School (Giuseppe Fiameni, CINECA)Linking HPC to Data Management - EUDAT Summer School (Giuseppe Fiameni, CINECA)
Linking HPC to Data Management - EUDAT Summer School (Giuseppe Fiameni, CINECA)
 
The state of global research data initiatives: observations from a life on th...
The state of global research data initiatives: observations from a life on th...The state of global research data initiatives: observations from a life on th...
The state of global research data initiatives: observations from a life on th...
 
Data Management and Horizon 2020
Data Management and Horizon 2020Data Management and Horizon 2020
Data Management and Horizon 2020
 
OpenAIRE webinar on Open Research Data in H2020 (OAW2016)
OpenAIRE webinar on Open Research Data in H2020 (OAW2016)OpenAIRE webinar on Open Research Data in H2020 (OAW2016)
OpenAIRE webinar on Open Research Data in H2020 (OAW2016)
 

Mehr von Open Data Support

Open government data and the psi directive et
Open government data and the psi directive etOpen government data and the psi directive et
Open government data and the psi directive etOpen Data Support
 
License your data and metadata et
License your data and metadata etLicense your data and metadata et
License your data and metadata etOpen Data Support
 
Introduction to open data quality et
Introduction to open data quality etIntroduction to open data quality et
Introduction to open data quality etOpen Data Support
 
Designing and developing vocabularies in rdf et
Designing and developing vocabularies in rdf etDesigning and developing vocabularies in rdf et
Designing and developing vocabularies in rdf etOpen Data Support
 
D2.1.2 training module 2.1 the linked open government data lifecycle v1.00
D2.1.2 training module 2.1 the linked open government data lifecycle v1.00D2.1.2 training module 2.1 the linked open government data lifecycle v1.00
D2.1.2 training module 2.1 the linked open government data lifecycle v1.00Open Data Support
 
Podatki & licenciranje metapodatkov
Podatki & licenciranje metapodatkovPodatki & licenciranje metapodatkov
Podatki & licenciranje metapodatkovOpen Data Support
 
Odprti podatki & kakovost metapodatkov
Odprti podatki  & kakovost metapodatkovOdprti podatki  & kakovost metapodatkov
Odprti podatki & kakovost metapodatkovOpen Data Support
 
Uvod v upravljanje z metapodatki
Uvod v upravljanje z metapodatkiUvod v upravljanje z metapodatki
Uvod v upravljanje z metapodatkiOpen Data Support
 
Odprti podatki javnega sektorja & Direktiva PSI
Odprti podatki javnega sektorja & Direktiva PSIOdprti podatki javnega sektorja & Direktiva PSI
Odprti podatki javnega sektorja & Direktiva PSIOpen Data Support
 
Open Data Support - Wie können wir Ihnen helfen?
Open Data Support - Wie können wir Ihnen helfen?Open Data Support - Wie können wir Ihnen helfen?
Open Data Support - Wie können wir Ihnen helfen?Open Data Support
 
Stałe identyfikatory URI – tworzenie i zarządzanie
Stałe identyfikatory URI – tworzenie i zarządzanieStałe identyfikatory URI – tworzenie i zarządzanie
Stałe identyfikatory URI – tworzenie i zarządzanieOpen Data Support
 
Zarządzanie metadanymi – wprowadzenie
Zarządzanie metadanymi – wprowadzenieZarządzanie metadanymi – wprowadzenie
Zarządzanie metadanymi – wprowadzenieOpen Data Support
 
Dane powiązane - wprowadzenie
Dane powiązane - wprowadzenieDane powiązane - wprowadzenie
Dane powiązane - wprowadzenieOpen Data Support
 
Įvadas į susietuosius duomenis
Įvadas į susietuosius duomenisĮvadas į susietuosius duomenis
Įvadas į susietuosius duomenisOpen Data Support
 
Atviri valdžios duomenys ir vsi direktyva
Atviri valdžios duomenys ir vsi direktyvaAtviri valdžios duomenys ir vsi direktyva
Atviri valdžios duomenys ir vsi direktyvaOpen Data Support
 
Open Data Support onsite training in Latvia (Latvian)
Open Data Support onsite training in Latvia (Latvian)Open Data Support onsite training in Latvia (Latvian)
Open Data Support onsite training in Latvia (Latvian)Open Data Support
 
Open Data Support - bridging open data supply and demand
Open Data Support - bridging open data supply and demandOpen Data Support - bridging open data supply and demand
Open Data Support - bridging open data supply and demandOpen Data Support
 
Open Data Support onsite training in Italy (Italian)
Open Data Support onsite training in Italy (Italian)Open Data Support onsite training in Italy (Italian)
Open Data Support onsite training in Italy (Italian)Open Data Support
 

Mehr von Open Data Support (20)

Open government data and the psi directive et
Open government data and the psi directive etOpen government data and the psi directive et
Open government data and the psi directive et
 
License your data and metadata et
License your data and metadata etLicense your data and metadata et
License your data and metadata et
 
Introduction to open data quality et
Introduction to open data quality etIntroduction to open data quality et
Introduction to open data quality et
 
Designing and developing vocabularies in rdf et
Designing and developing vocabularies in rdf etDesigning and developing vocabularies in rdf et
Designing and developing vocabularies in rdf et
 
D2.1.2 training module 2.1 the linked open government data lifecycle v1.00
D2.1.2 training module 2.1 the linked open government data lifecycle v1.00D2.1.2 training module 2.1 the linked open government data lifecycle v1.00
D2.1.2 training module 2.1 the linked open government data lifecycle v1.00
 
Podatki & licenciranje metapodatkov
Podatki & licenciranje metapodatkovPodatki & licenciranje metapodatkov
Podatki & licenciranje metapodatkov
 
Odprti podatki & kakovost metapodatkov
Odprti podatki  & kakovost metapodatkovOdprti podatki  & kakovost metapodatkov
Odprti podatki & kakovost metapodatkov
 
Uvod v upravljanje z metapodatki
Uvod v upravljanje z metapodatkiUvod v upravljanje z metapodatki
Uvod v upravljanje z metapodatki
 
Odprti podatki javnega sektorja & Direktiva PSI
Odprti podatki javnega sektorja & Direktiva PSIOdprti podatki javnega sektorja & Direktiva PSI
Odprti podatki javnega sektorja & Direktiva PSI
 
Open Data Support - Wie können wir Ihnen helfen?
Open Data Support - Wie können wir Ihnen helfen?Open Data Support - Wie können wir Ihnen helfen?
Open Data Support - Wie können wir Ihnen helfen?
 
Stałe identyfikatory URI – tworzenie i zarządzanie
Stałe identyfikatory URI – tworzenie i zarządzanieStałe identyfikatory URI – tworzenie i zarządzanie
Stałe identyfikatory URI – tworzenie i zarządzanie
 
Zarządzanie metadanymi – wprowadzenie
Zarządzanie metadanymi – wprowadzenieZarządzanie metadanymi – wprowadzenie
Zarządzanie metadanymi – wprowadzenie
 
Dane powiązane - wprowadzenie
Dane powiązane - wprowadzenieDane powiązane - wprowadzenie
Dane powiązane - wprowadzenie
 
atvirų duomenų kokybė
atvirų duomenų kokybėatvirų duomenų kokybė
atvirų duomenų kokybė
 
Įvadas į susietuosius duomenis
Įvadas į susietuosius duomenisĮvadas į susietuosius duomenis
Įvadas į susietuosius duomenis
 
Atviri valdžios duomenys ir vsi direktyva
Atviri valdžios duomenys ir vsi direktyvaAtviri valdžios duomenys ir vsi direktyva
Atviri valdžios duomenys ir vsi direktyva
 
Open Data Support onsite training in Latvia (Latvian)
Open Data Support onsite training in Latvia (Latvian)Open Data Support onsite training in Latvia (Latvian)
Open Data Support onsite training in Latvia (Latvian)
 
Open Data Support - bridging open data supply and demand
Open Data Support - bridging open data supply and demandOpen Data Support - bridging open data supply and demand
Open Data Support - bridging open data supply and demand
 
Open data quality
Open data qualityOpen data quality
Open data quality
 
Open Data Support onsite training in Italy (Italian)
Open Data Support onsite training in Italy (Italian)Open Data Support onsite training in Italy (Italian)
Open Data Support onsite training in Italy (Italian)
 

Kürzlich hochgeladen

Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxLoriGlavin3
 
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Nikki Chapple
 
Scale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterScale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterMydbops
 
Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfNeo4j
 
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality AssuranceInflectra
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
Varsha Sewlal- Cyber Attacks on Critical Critical InfrastructureVarsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructureitnewsafrica
 
Data governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationData governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationKnoldus Inc.
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfpanagenda
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfLoriGlavin3
 
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security ObservabilityGlenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security Observabilityitnewsafrica
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxLoriGlavin3
 
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...
Abdul Kader Baba- Managing Cybersecurity Risks  and Compliance Requirements i...Abdul Kader Baba- Managing Cybersecurity Risks  and Compliance Requirements i...
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...itnewsafrica
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsNathaniel Shimoni
 
2024 April Patch Tuesday
2024 April Patch Tuesday2024 April Patch Tuesday
2024 April Patch TuesdayIvanti
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesKari Kakkonen
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...Wes McKinney
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24Mark Goldstein
 

Kürzlich hochgeladen (20)

Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
 
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
 
Scale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterScale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL Router
 
Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdf
 
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
Varsha Sewlal- Cyber Attacks on Critical Critical InfrastructureVarsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
 
Data governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationData governance with Unity Catalog Presentation
Data governance with Unity Catalog Presentation
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdf
 
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security ObservabilityGlenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
 
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...
Abdul Kader Baba- Managing Cybersecurity Risks  and Compliance Requirements i...Abdul Kader Baba- Managing Cybersecurity Risks  and Compliance Requirements i...
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directions
 
2024 April Patch Tuesday
2024 April Patch Tuesday2024 April Patch Tuesday
2024 April Patch Tuesday
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examples
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
 

Introduction to metadata management

  • 1. DATA SUPPORT OPEN Training Module 1.4 Introduction to metadata management PwC firms help organisations and individuals create the value they’re looking for. We’re a network of firms in 158 countries with close to 180,000 people who are committed to delivering quality in assurance, tax and advisory services. Tell us what matters to you and find out more by visiting us at www.pwc.com. PwC refers to the PwC network and/or one or more of its member firms, each of which is a separate legal entity. Please see www.pwc.com/structure for further details.
  • 2. DATASUPPORTOPEN This presentation has been created by PwC Authors: Makx Dekkers, Michiel De Keyzer, Nikolaos Loutas and Stijn Goedertier Presentation metadata Slide 2 Open Data Support is funded by the European Commission under SMART 2012/0107 ‘Lot 2: Provision of services for the Publication, Access and Reuse of Open Public Data across the European Union, through existing open data portals’(Contract No. 30-CE- 0530965/00-17). © 2014 European Commission Disclaimers 1. The views expressed in this presentation are purely those of the authors and may not, in any circumstances, be interpreted as stating an official position of the European Commission. The European Commission does not guarantee the accuracy of the information included in this presentation, nor does it accept any responsibility for any use thereof. Reference herein to any specific products, specifications, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favouring by the European Commission. All care has been taken by the author to ensure that s/he has obtained, where necessary, permission to use any parts of manuscripts including illustrations, maps, and graphs, on which intellectual property rights already exist from the titular holder(s) of such rights or from her/his or their legal representative. 2. This presentation has been carefully compiled by PwC, but no representation is made or warranty given (either express or implied) as to the completeness or accuracy of the information it contains. PwC is not liable for the information in this presentation or any decision or consequence based on the use of it.. PwC will not be liable for any damages arising from the use of the information contained in this presentation. The information contained in this presentation is of a general nature and is solely for guidance on matters of general interest. This presentation is not a substitute for professional advice on any particular matter. No reader should act on the basis of any matter contained in this publication without considering appropriate professional advice.
  • 3. DATASUPPORTOPEN Learning objectives By the end of this training module you should have an understanding of: • What metadata is; • The terminology and objectives of metadata management; • The different dimensions of metadata quality; • The use of controlled vocabularies for metadata; • Metadata exchange and aggregation; • Metadata management in Open Data Support. Slide 3
  • 4. DATASUPPORTOPEN Content This module contains ... • An explanation of what is metadata; • An outline of the metadata lifecycle; • An introduction to metadata quality; • An overview of the metadata management and exchange approach implemented by Open Data Support through the Open Data Interoperability Platform. Slide 4
  • 5. DATASUPPORTOPEN What is metadata? Definition, examples and reusable standards. Slide 5
  • 6. DATASUPPORTOPEN What is metadata? “Metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource. Metadata is often called data about data or information about information.” -- National Information Standards Organization http://www.niso.org/publications/press/UnderstandingMetadata.pdf Metadata provides information enabling to make sense of data (e.g. documents, images, datasets), concepts (e.g. classification schemes) and real-world entities (e.g. people, organisations, places, paintings, products). Slide 6
  • 7. DATASUPPORTOPEN Types of metadata • Descriptive metadata, describe a resource for purposes of discovery and identification. • Structural metadata, e.g. data models and reference data. • Administrative metadata, provides information to help manage a resource. Slide 7 In this tutorial we are focusing mainly on descriptive metadata for datasets. Administrative metadata is also partly covered.
  • 8. DATASUPPORTOPEN Examples of metadata Slide 8 Can Book Dataset Label Catalogue card Dataset description (DCAT) Provides metadata on
  • 9. DATASUPPORTOPEN Two approaches for providing metadata on the Web XML (Tree/container approach) RDF (Triple-based approach) Slide 9
  • 11. DATASUPPORTOPEN Metadata management is important Metadata needs to be managed to ensure ... • Availability: metadata needs to be stored where it can be accessed and indexed so it can be found. • Quality: metadata needs to be of consistent quality so users know that it can be trusted. • Persistence: metadata needs to be kept over time. • Open License: metadata should be available under a public domain license to enable its reuse. The metadata lifecycle is larger than the data lifecycle: • Metadata may be created before data is created or captured, e.g. to inform about data that will be available in the future. • Metadata needs to be kept after data has been removed, e.g. to inform about data that has been decommissioned or withdrawn. Slide 11
  • 12. DATASUPPORTOPEN Metadata schema “A labelling, tagging or coding system used for recording cataloguing information or structuring descriptive records. A metadata schema establishes and defines data elements and the rules governing the use of data elements to describe a resource.” Slide 12 RDF Schema XML Schema
  • 13. DATASUPPORTOPEN Reuse existing vocabularies for providing metadata to your resources General purpose standards and specifications: • Dublin Core for published material (text, images), http://dublincore.org/documents/dcmi-terms/ • FOAF for people and organisations, http://xmlns.com/foaf/spec/ • SKOS for concept collections, http://www.w3.org/TR/skos-reference • ADMS for interoperability assets, http://www.w3.org/TR/vocab-adms/ Specific standard for datasets: • Data Catalog Vocabulary DCAT, http://www.w3.org/TR/vocab-dcat/ Specific usage of DCAT and other vocabularies to support interoperability of data portals across Europe: • DCAT application profile for data portals in Europe, http://joinup.ec.europa.eu/asset/dcat_application_profile/description Slide 13
  • 14. DATASUPPORTOPEN Designing your metadata schema with RDF Schema (RDFS) – reuse where possible RDF schema is particularly good in combining terms from different standards and specifications. Slide 14 Do not re-invent terms that are already defined somewhere else , when designing RDF schemas – reuse terms where possible.  For example, the DCAT Application Profile for data portals in Europe (DCAT-AP) reuses terms from DCAT, Dublin Core, FOAF, SKOS, ADMS and others.
  • 15. DATASUPPORTOPEN Example: description of an open dataset with the DCAT-AP Description of the Catalogue Description of the Dataset Description of the Distribution Slide 15
  • 16. DATASUPPORTOPEN Controlled vocabularies Using thesauri, taxonomies and standardised lists of terms for assigning values to metadata properties. Slide 16
  • 17. DATASUPPORTOPEN What are controlled vocabularies? A controlled vocabulary is a predefined list of values to be used as values for a specific property in your metadata schema. • In addition to careful design of schemas, the value spaces of metadata properties are important for the exchange of information, and thus interoperability. • Common controlled vocabularies for value spaces make metadata understandable across systems. Slide 17
  • 18. DATASUPPORTOPEN Which controlled vocabulary to be used for which type of property • Use code lists as controlled vocabulary for free text or “string” properties. • Example DCAT-AP property: • Example code list - ObjectInCrimeClass (ListPoint) • Use concepts identified by a URI for reference to “things”. • Example DCAT-AP property: • Example taxonomy with terms having a URI - EuroVoc Slide 18
  • 19. DATASUPPORTOPEN Example –Publications Office’s Named Authority Lists • The Named Authority Lists offer reusable controlled vocabularies for:  Countries  Corporate bodies  File types  Interinstitutional procedures  Languages  Multilingual  Resource types  Roles  Treaties Slide 19
  • 20. DATASUPPORTOPEN The metadata lifecycle Creating, maintaining, updating, storing, publishing metadata and handling deletion of data. Slide 20
  • 21. DATASUPPORTOPEN Creating your metadata Metadata creation can be supported by (semi-)automatic processes. • Document properties generated in (office) tools, e.g. creation date. • Spatial and temporal information captured by cameras, sensors... • Information from publication workflow, e.g. file location or URL However, other characteristics require human intervention: • What is the resource about (e.g. linking to a subject vocabulary)? • How can the resource be used (e.g. linking to a licence)? • Where can I find more information about this resource (e.g. linking to a Web site or documentation that describes the resource)? • How can quality information be included? Slide 21
  • 22. DATASUPPORTOPEN Maintaining your metadata Approaches for maintaining metadata need to be appropriate for the type of data that is being published. • If data does not change, metadata can be relatively stable. Changes (bulk conversions) can take place off-line when needed. • If data changes frequently (e.g. real-time sensor data), metadata needs to be closely coupled to the data workflow and changes need to be practically instantaneous. Slide 22
  • 23. DATASUPPORTOPEN Updating your metadata – planning for change Metadata operates in a global context that is subject to change! • Organisation – departments are established, merge with others, responsibilities are handed over. • Usage of the data – new applications emerge around data. • Reference data – controlled vocabularies evolve and get linked. • Data standards and technologies – technology lifecycle is getting shorter all the time; what will tomorrow’s Web look like? • Tools and systems – evolution of storage, bandwidth, mobile... Metadata needs to be kept up-to-date to the extent possible, taking into account the available time and budget. Slide 23
  • 24. DATASUPPORTOPEN Storing your metadata – what are the options? Depending on operational requirements, metadata can be embedded with the data or stored separately from the data. • Embedding the metadata in the data (e.g. office documents, MP3, JPG, RDF data) embedding makes data exchange easier. • Separating metadata from data (e.g. in a database), with links to corresponding data files makes management easier. Depending on the availability of tools and requirements on performance and capacity, metadata can be stored in a ‘classic’ relational database or an RDF triple store. Slide 24
  • 25. DATASUPPORTOPEN Handling deletions of data In many cases, metadata must survive even after deletion of the data it describes. Decommissioning or deletion of data happens, for example: • When data is no longer necessary. • When data is no longer valid. • When data is wrong. • When data is withdrawn by the owner/publisher In that case the metadata should, contain information that the data was deleted, and if it was archived, how and where an archival copy can be requested. Slide 25
  • 26. DATASUPPORTOPEN Publishing your metadata – what are the options? • ‘Open’ publication: direct access on URIs - This is the option most in line with the vision of Linked Open Data and allows the ‘follow-your-nose’ principle. • Make your metadata available through a SPARQL endpoint - This allows external systems to send queries to an RDF triple store. - Requires knowledge about the schema used in the triple store. • Deferred publication: access to exported file in RDF - Produced by converting non-RDF data to RDF. - Allows off-line bulk harvesting and caching of data collections. - Allows implementation of access control. Slide 26 See also: http://www.slideshare.net/OpenDataSupport /licence-your-data-metadata
  • 27. DATASUPPORTOPEN Metadata quality The quality and completeness of the description metadata of your datasets, directly affects their searchability and reuse. Slide 27
  • 28. DATASUPPORTOPEN Metadata quality is about... (1/3) • The accuracy of your metadata - are the characteristics of the resource correctly reflected? - e.g. indicating the right title, the right license, the right publisher enables users to discover resources that they need. • The availability of your metadata – can the metadata be accessed now and over time into the future? - e.g. making it available for indexing and downloading, and include it in in a regular back-up process. • The completeness of your metadata – are all relevant characteristics of the resource captured (as far as practically and economically feasible and necessary for the application)? - e.g. indicating the licence that governs reuse or the format of the distribution enables filters on those aspects. Slide 28 See also: http://www.slideshare.net/OpenDataSupport/open-data-quality
  • 29. DATASUPPORTOPEN Metadata quality is about ... (2/3) • The conformance of your metadata to accepted standards – is the metadata conforming to a specific metadata standard or an Application Profile? - e.g. the description of a dataset conforms to the DCAT-AP. • The consistency of your metadata – does the data not contain contradictions? - e.g. not having multiple and contradictory license statements for the same piece of data. • The credibility and provenance of your metadata – is the metadata based on trustworthy sources? - e.g. linking to reference data published and managed by a stable organisation (e.g. the EU Publications Office). Slide 29
  • 30. DATASUPPORTOPEN Metadata quality is about ... (3/3) • The processability of the metadata – is the metadata properly machine-readable? - e.g. making the metadata of a dataset available in RDF and/or XML, and not as free text. • The relevance of the metadata – does the metadata contain the right amount of information for the task at hand? - e.g. limit the information to optimally serve the users’ needs. • The timeliness of your metadata – is the metadata corresponding to the actual (current) characteristics of the resource and is it published soon enough? - e.g. indicating the last modification date of the resource, thus making sure the metadata is fresh so that users will see the latest information. Slide 30
  • 31. DATASUPPORTOPEN Exchanging metadata of datasets Mapping your metadata to a common metadata vocabulary, such as the DCAT-AP, and exchanging the metadata across platforms. Slide 31
  • 32. DATASUPPORTOPEN Homogenising metadata When exchanged between systems, metadata should be mapped to a common model so that the sender and the recipient share a common understanding on the meaning of the metadata. • On the schema level metadata coming from different sources can be based on different metadata schemas, e.g. DCAT, schema.org, CERIF, own internal model... • On the data (value) level, the metadata properties should be assigned values from different controlled vocabularies or syntaxes, e.g.: - Language: English can be expressed as http://publications.europa.eu/resource/authority/language/ENG or as http://id.loc.gov/vocabulary/iso639-1/en - Dates: ISO8601 (“20130101”) versus W3C DTF (“2013-01-01”) Slide 32
  • 33. DATASUPPORTOPEN Example: Homogenising metadata about datasets The DCAT Application Profile for data portals in Europe The DCAT-AP can be used as the common model for exchanging metadata with open data platforms across Europe and/or with a data broker (e.g. The Open Data Interoperability Platform - ODIP). Slide 33 EXPLORE FIND IDENTIFY SELECT OBTAIN Public admi nistrations Busi nesses Standar disation bodi es Academia Data Portal Data Portal Data Portal Data Portal Data Portal Data Portal Metadata Broker Data Consumers See also: http://joinup.ec.europa.eu/asset/dcat_application_profile/home
  • 34. DATASUPPORTOPEN Mapping example – data.gov.uk Slide 34 dct:title (Dataset) dct:description dct:publisher dct:title (Distribution) Dcat:accessURL dct:language dcat:keyword dct:license dcat:downloadURL, dct:issued, dct:format, dct: description dct:spatial dct:theme dct:issued dct:modified adms:contactPoint dct:temporal
  • 35. DATASUPPORTOPEN What can the Open Data Interoperability Platform do? • Harvest metadata from an Open Data portal. • Transform the metadata to RDF. • Harmonise the RDF metadata produced in the previous steps with DCAT-AP. • Validate the harmonised metadata against the DCAT-AP. • Publish the description metadata as Linked Open Data. Slide 35 ODIPP Pan-European Data portal See also: http://www.slideshare.net/OpenDataSupport/promoting-the-re-use- of-open-data-through-odip
  • 36. DATASUPPORTOPEN Conclusions • Metadata provides information on your data and resources. The quality of the metadata directly affects the discoverability and reuse of your the resources. • A structured approach should be followed for metadata management. • The metadata lifecycle extends the lifecycle of datasets (metadata before publication and after deletion). • Homogenised metadata enable the operation of metadata brokers, which can in turn lower the access barriers to your resources, leading to improved visibility and discoverability, and thus increasing their reuse potential. Slide 36
  • 37. DATASUPPORTOPEN Group exercise and questions Slide 37 In groups of two, select one dataset from your country and describe it with the DCAT Application Profile. Does your organisation have a minimum set of metadata to be provided together with Open Data? What would be the main barriers, according to you, for the (re)use of standard controlled vocabularies in your metadata? Do you have any data and/or metadata governance methodology at the corporate level? http://www.visualpharm.com http://www.visualpharm.com http://www.visualpharm.com http://www.visualpharm.com Take also the online test here!
  • 38. DATASUPPORTOPEN Thank you! ...and now YOUR questions? Slide 38
  • 39. DATASUPPORTOPEN References Slide 6, 7: • NISO. Understanding Metadata. http://www.niso.org/publications/press/UnderstandingMetadata.pdf Slide 9: • Dublin City University. Chapter 3: Introduction to XML. http://wiki.eeng.dcu.ie/ee557/g2/326-EE.html • W3C. RDF Primer. http://www.w3.org/TR/rdf-primer/ Slide 12: • http://gondolin.rutgers.edu/MIC/text/how/catalog_glossary.htm • Dublin Core. Example XML Schema. http://dublincore.org/schemas/xmls/qdc/dc.xsd • Dublin Core, Example RDF Schema. http://dublincore.org/2012/06/14/dcterms.rdf Slide 14, 33: • The ISA Programme. DCAT Application Profile for Data Portals in Europe - Final Draft. https://joinup.ec.europa.eu/asset/dcat_application_profile/asset_release/dcat- application-profile-data-portals-europe-final-draf Slide 18: • ListPoint. ObjectInCrimeClass. http://www.listpoint.co.uk/CodeList/details/ObjectInCrimeClass/1.2/1 Slide 19: • Publications Office. Countries Name Authority List. http://open- data.europa.eu/en/data/dataset/2nM4aG8LdHG6RBMumfkNzQ Slide 39
  • 40. DATASUPPORTOPEN Further reading Understanding Metadata, NISO. http://www.niso.org/publications/press/UnderstandingMetadata.pdf Ben Jareo and Malcolm Saldanha. The value proposition of a metadata driven data governance program. Best Practices Metadata. May 2012. https://community.informatica.com/mpresources/Communities/IW2 012/Docs/bos_30.pdf John R. Friedrich, II. Metadata Management Best Practices and Lessons Learned. The 10th Annual Wilshire Meta-Data Conference and the 18th Annual DAMA International Symposium. April 2006. http://www.metaintegration.net/Publications/2006-Wilshire-DAMA- MetaIntegrationBestPractices.pdf Slide 40
  • 41. DATASUPPORTOPEN Related initiatives Metadata Management. Trainer screencasts, http://managemetadata.com/screencasts/msa/ MIT Libraries. Data Management and Publishing. Reasons to Manage and Publish Your Data, http://libraries.mit.edu/guides/subjects/data- management/why.html ISA Programme. DCAT Application Profile for European Data Portals, https://joinup.ec.europa.eu/asset/dcat_application_profile/descripti on Generating ADMS-based descriptions of assets using Open Refine RDF, https://joinup.ec.europa.eu/asset/adms/document/generate- adms-asset-descriptions-spreadsheet-refine-rdf The Dublin Core Medatata Initiative, http://dublincore.org/ Slide 41
  • 42. DATASUPPORTOPEN Be part of our team... Find us on Contact us Join us on Follow us Open Data Support http://www.slideshare.net/OpenDataSupport http://www.opendatasupport.euOpen Data Support http://goo.gl/y9ZZI @OpenDataSupport contact@opendatasupport.eu Slide 42