El documento habla sobre los metadatos. Explica que los metadatos son datos estructurados que describen recursos digitales para facilitar su búsqueda y recuperación. Describe los tipos de metadatos, como los administrativos, descriptivos y estructurales. También cubre estándares y esquemas de metadatos como Dublin Core y explica cómo se almacenan y gestionan los metadatos.
Data-Ed Slides: Best Practices in Data Stewardship (Technical)DATAVERSITY
In order to find value in your organization's data assets, heroic data stewards are tasked with saving the day- every single day! These heroes adhere to a data governance framework and work to ensure that data is: captured right the first time, validated through automated means, and integrated into business processes. Whether its data profiling or in depth root cause analysis, data stewards can be counted on to ensure the organization's mission critical data is reliable. In this webinar we will approach this framework, and punctuate important facets of a data steward’s role.
Learning Objectives:
- Understand the business need for a data governance framework
- Learn why embedded data quality principles are an important part of system/process design
- Identify opportunities to help drive your organization to a data driven culture
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
Palestra com dicas e passos importantes para implantação de Programas de Gestão e Governança de Dados (Data Governance). Gestão de Dados Estratégica. Bergson Lopes.
RDF is a general method to decompose knowledge into small pieces, with some rules about the semantics or meaning of those pieces. The point is to have a method so simple that it can express any fact, and yet so structured that computer applications can do useful things with knowledge expressed in RDF.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Data-Ed Slides: Best Practices in Data Stewardship (Technical)DATAVERSITY
In order to find value in your organization's data assets, heroic data stewards are tasked with saving the day- every single day! These heroes adhere to a data governance framework and work to ensure that data is: captured right the first time, validated through automated means, and integrated into business processes. Whether its data profiling or in depth root cause analysis, data stewards can be counted on to ensure the organization's mission critical data is reliable. In this webinar we will approach this framework, and punctuate important facets of a data steward’s role.
Learning Objectives:
- Understand the business need for a data governance framework
- Learn why embedded data quality principles are an important part of system/process design
- Identify opportunities to help drive your organization to a data driven culture
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
Palestra com dicas e passos importantes para implantação de Programas de Gestão e Governança de Dados (Data Governance). Gestão de Dados Estratégica. Bergson Lopes.
RDF is a general method to decompose knowledge into small pieces, with some rules about the semantics or meaning of those pieces. The point is to have a method so simple that it can express any fact, and yet so structured that computer applications can do useful things with knowledge expressed in RDF.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Tekslate.com is the Industry leader in providing Informatica Data Quality Training across the globe. Our online training methodology focus on hands on experience of Informatica Data Quality.
Data Governance Roles as the Backbone of Your ProgramDATAVERSITY
The method you follow to form your Data Governance roles and responsibilities will impact the success of your program. There are industry-standard roles that require adjustment to fit the culture of your organization when getting started, gaining acceptance, and demonstrating sustained value. Roles are the backbone of a productive Data Governance program.
Bob Seiner will share his updated operating model of roles and responsibilities in this topical RWDG webinar. The model Bob uses is meant to overlay your present organizational structure rather than requiring you to try and plug your organization into someone else’s model. This webinar will provide everything you need to know about Data Governance roles.
Bob will address the following in this webinar:
• An operating model of Data Governance roles and responsibilities
• How to customize the model to mimic your existing structure
• The meaning behind the oft-used “roles pyramid”
• Detailed responsibilities at each level of the organization
• Using the model to influence Data Governance acceptance
3 Phases of Healthcare Data Governance in AnalyticsHealth Catalyst
Healthcare data governance is a broad topic and covers more than data stewardship, storage, and technical roles and responsibilities. And it’s not easy to implement. It’s necessary, though, for health systems that are entering the world of analytics because the governance structure will enable the organizations to drive higher-quality, low cost care. In order for healthcare data governance to be most effective however, it needs to be adaptive because real healthcare data governance is much more fluid than any plan laid out on paper. Typically there are three phases that characterize successful analytics implementations: the early stage, the mid-term stage, and the steady state. As health systems begin to determine the effectiveness of their data governance strategy, it’s important to look at key metrics from their analytics implementations that will either trend up, remain solid, or trend down.
RWDG Slides: What is a Data Steward to do?DATAVERSITY
Most people recognize that Data Stewards play an essential role in their Data Governance and Information Governance programs. However, the manner in which Data Stewards are used is not the same from organization to organization. How you use Data Stewards depends on your goals for Data Governance.
Join Bob Seiner for this month’s RWDG webinar where he will share different ways to activate Data Stewards based on the purpose of your program. Bob will talk about options to extend existing Data Steward activity and how to build new functionality into the role of your Data Stewards.
In this webinar, Bob will discuss:
- The crucial role of the Data Steward in Data Governance
- Different types of Data Stewards and what they do
- Aligning Data Steward activities with program goals
- Improving existing Data Steward actions
- Finding new ways to use your Data Stewards
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
How to Implement Data Governance Best PracticeDATAVERSITY
Data Governance Best Practice is defined as basis and guidelines for suggested governing activities. Organizations define best practices to be used as a point of comparison when determining their readiness, willingness and actions necessary to put a Data Governance program in place. But what are the best practices and how can they be implemented? This webinar will address these questions and more.
In this RWDG webinar, Bob Seiner will talk about how to create, validate, assess and implement Data Governance Best Practice with immediate impact on present and future Data Governance activities. The result of a Best Practice assessment is a thorough actionable plan focused on demonstrating value from your Data Governance program.This webinar will cover:
• Two Criteria for Data Governance Best Practice Development
• How to Assess against Best Practice to Build Program Success
• Examples of Industry Selected DG Best Practice
• How to Communicate DG Best Practice in a Non-Threatening Way
• How to Build DG Best Practice into Daily Operations
Data Governance Takes a Village (So Why is Everyone Hiding?)DATAVERSITY
Data governance represents both an obstacle and opportunity for enterprises everywhere. And many individuals may hesitate to embrace the change. Yet if led well, a governance initiative has the potential to launch a data community that drives innovation and data-driven decision-making for the wider business. (And yes, it can even be fun!). So how do you build a roadmap to success?
This session will gather four governance experts, including Mary Williams, Associate Director, Enterprise Data Governance at Exact Sciences, and Bob Seiner, author of Non-Invasive Data Governance, for a roundtable discussion about the challenges and opportunities of leading a governance initiative that people embrace. Join this webinar to learn:
- How to build an internal case for data governance and a data catalog
- Tips for picking a use case that builds confidence in your program
- How to mature your program and build your data community
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A native graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL.
Tekslate.com is the Industry leader in providing Informatica Data Quality Training across the globe. Our online training methodology focus on hands on experience of Informatica Data Quality.
Data Governance Roles as the Backbone of Your ProgramDATAVERSITY
The method you follow to form your Data Governance roles and responsibilities will impact the success of your program. There are industry-standard roles that require adjustment to fit the culture of your organization when getting started, gaining acceptance, and demonstrating sustained value. Roles are the backbone of a productive Data Governance program.
Bob Seiner will share his updated operating model of roles and responsibilities in this topical RWDG webinar. The model Bob uses is meant to overlay your present organizational structure rather than requiring you to try and plug your organization into someone else’s model. This webinar will provide everything you need to know about Data Governance roles.
Bob will address the following in this webinar:
• An operating model of Data Governance roles and responsibilities
• How to customize the model to mimic your existing structure
• The meaning behind the oft-used “roles pyramid”
• Detailed responsibilities at each level of the organization
• Using the model to influence Data Governance acceptance
3 Phases of Healthcare Data Governance in AnalyticsHealth Catalyst
Healthcare data governance is a broad topic and covers more than data stewardship, storage, and technical roles and responsibilities. And it’s not easy to implement. It’s necessary, though, for health systems that are entering the world of analytics because the governance structure will enable the organizations to drive higher-quality, low cost care. In order for healthcare data governance to be most effective however, it needs to be adaptive because real healthcare data governance is much more fluid than any plan laid out on paper. Typically there are three phases that characterize successful analytics implementations: the early stage, the mid-term stage, and the steady state. As health systems begin to determine the effectiveness of their data governance strategy, it’s important to look at key metrics from their analytics implementations that will either trend up, remain solid, or trend down.
RWDG Slides: What is a Data Steward to do?DATAVERSITY
Most people recognize that Data Stewards play an essential role in their Data Governance and Information Governance programs. However, the manner in which Data Stewards are used is not the same from organization to organization. How you use Data Stewards depends on your goals for Data Governance.
Join Bob Seiner for this month’s RWDG webinar where he will share different ways to activate Data Stewards based on the purpose of your program. Bob will talk about options to extend existing Data Steward activity and how to build new functionality into the role of your Data Stewards.
In this webinar, Bob will discuss:
- The crucial role of the Data Steward in Data Governance
- Different types of Data Stewards and what they do
- Aligning Data Steward activities with program goals
- Improving existing Data Steward actions
- Finding new ways to use your Data Stewards
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
How to Implement Data Governance Best PracticeDATAVERSITY
Data Governance Best Practice is defined as basis and guidelines for suggested governing activities. Organizations define best practices to be used as a point of comparison when determining their readiness, willingness and actions necessary to put a Data Governance program in place. But what are the best practices and how can they be implemented? This webinar will address these questions and more.
In this RWDG webinar, Bob Seiner will talk about how to create, validate, assess and implement Data Governance Best Practice with immediate impact on present and future Data Governance activities. The result of a Best Practice assessment is a thorough actionable plan focused on demonstrating value from your Data Governance program.This webinar will cover:
• Two Criteria for Data Governance Best Practice Development
• How to Assess against Best Practice to Build Program Success
• Examples of Industry Selected DG Best Practice
• How to Communicate DG Best Practice in a Non-Threatening Way
• How to Build DG Best Practice into Daily Operations
Data Governance Takes a Village (So Why is Everyone Hiding?)DATAVERSITY
Data governance represents both an obstacle and opportunity for enterprises everywhere. And many individuals may hesitate to embrace the change. Yet if led well, a governance initiative has the potential to launch a data community that drives innovation and data-driven decision-making for the wider business. (And yes, it can even be fun!). So how do you build a roadmap to success?
This session will gather four governance experts, including Mary Williams, Associate Director, Enterprise Data Governance at Exact Sciences, and Bob Seiner, author of Non-Invasive Data Governance, for a roundtable discussion about the challenges and opportunities of leading a governance initiative that people embrace. Join this webinar to learn:
- How to build an internal case for data governance and a data catalog
- Tips for picking a use case that builds confidence in your program
- How to mature your program and build your data community
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A native graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL.
Presentación elaborada para el curso de Archivos Digitales de la Universidad del Quindío, Programa Ciencia de la Información y Documentación, Bibliotecología y Archivística.
Presentación elaborada para el curso de Archivos Digitales de la Universidad del Quindío, Programa Ciencia de la Información y Documentación, Bibliotecología y Archivística.
El diseño de la herramienta.wiki.transficcion.euJesús Tramullas
Presentación sobre wiki semántico para corpus textual. Curso El pensamiento de las mujeres (1975-2025): Literatura, periodismo, filosofía (noviembre 2022).
Lo que no se documenta no existe. Introducción a la elaboración de documentac...Jesús Tramullas
Material de la conferencia Lo que no se documenta no existe. Introducción a la elaboración de documentación técnica. IX Jornadas de Wikimedia España, Almería, Noviembre de 2022.
No solo de software libre vive la cultura libreJesús Tramullas
Ponencia sobre cultura libre en las Primeras Jornadas de Cultura Libre, Oficina de Conocimiento y Cultura Libres, Univ. Rey Juan Carlos, Madrid, marzo 2022
Cámaras en las trincheras: la cobertura de los fotógrafos de la Guerra Civil ...Jesús Tramullas
Trabajo presentado en las IV Jornadas sobre Investigación en Historia de la Fotografía. 1839-1939: Un siglo de fotografía. Zaragoza, octubre 2021. Autores: Luis M. Blanco, Carmen Agustín y Jesús Tramullas
Nuestra imaginación es la que ve y no los ojos: Wikipedia y la memoria de la ...Jesús Tramullas
Autores: Luis M. Blanco y Jesús Tramullas. Conferencia pronunciada en el Curso Literaturas Transicionales en Europa (Comparatismo y Humanidades Digitales), Zaragoza, septiembre 2021.
Desarrollo de colecciones de patrimonio cultural en entornos colaborativosJesús Tramullas
Conferencia en Coloquio internacional
Epigrafía humanística en España y Portugal:
estudio y edición digital.
Universidad de Alcalá de Henares, 9-10 Julio 2019
IMÁGENES SUBLIMINALES EN LAS PUBLICACIONES DE LOS TESTIGOS DE JEHOVÁClaude LaCombe
Recuerdo perfectamente la primera vez que oí hablar de las imágenes subliminales de los Testigos de Jehová. Fue en los primeros años del foro de religión “Yahoo respuestas” (que, por cierto, desapareció definitivamente el 30 de junio de 2021). El tema del debate era el “arte religioso”. Todos compartíamos nuestros puntos de vista sobre cuadros como “La Mona Lisa” o el arte apocalíptico de los adventistas, cuando repentinamente uno de los participantes dijo que en las publicaciones de los Testigos de Jehová se ocultaban imágenes subliminales demoniacas.
Lo que pasó después se halla plasmado en la presente obra.
La Unidad Eudista de Espiritualidad se complace en poner a su disposición el siguiente Triduo Eudista, que tiene como propósito ofrecer tres breves meditaciones sobre Jesucristo Sumo y Eterno Sacerdote, el Sagrado Corazón de Jesús y el Inmaculado Corazón de María. En cada día encuentran una oración inicial, una meditación y una oración final.
1. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
3. Metadatos.
2. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Término impreciso.
● Datos sobre datos:
● Etiquetas usadas para describir documentos,
imágenes, objetos digitales… con el propósito
de mejorar la navegación y la recuperación.
● Herramienta de búsqueda:
● Palabras clave no mostradas, pero usadas
por los motores de búsqueda y recuperación.
3. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
La definición de NISO.
● “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.”
NISO (2004) Understanding Metadata. Bethesda, NISO Press
4. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Un poco más de precisión.
● Colección de información estructurada
sobre un documento, objeto o parte de un
contenido.
● Da información sobre estructura, contexto y
significado.
● Siguen una regla o esquema.
● Se suelen definir unidades llamadas
elementos, campos, atributos o
propiedades.
● Pueden ser obligatorios u opcionales.
5. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
¿Datos sobre qué?
Tradicionalmente...
● Título.
● Autor.
● Fechas.
● Idioma.
● Materia.
● Editor.
● Palabras clave.
● Otros...
6. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Tipos de metadatos.
● Estructurales: modelo de tipo de
contenido y de atributos. Relaciones
dentro del objeto digital.
● Administrativos: Cómo, cuándo y quién
creó contenido; cómo usarlo, niveles de
acceso y status.
● Descriptivos: describen la materia o
asunto del contenido.
● Lenguajes de marcado: integran
metadatos en contenido.
7. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Tipos de metadatos
administrativos.
● Técnicos: describe los aspectos técnicos
del objeto digital.
● Preservación: apoyo al mantenimiento a
largo plazo del objeto digital, puede
combinar los tipos anteriores.
● Gestión propiedad intelectual: datos
para gestión de derechos.
8. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Usos de los metadatos.
● Búsqueda.
● Exploración.
● Enlaces contextuales.
● Agregación.
● Sindicación.
● Permisos de acceso.
● Personalización.
● Funcionalidades avanzadas.
● Interoperabilidad.
9. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Almacenamiento de metadatos.
● Bases de datos relacionales:
– Registro.
● Extructured Markup Language, XML:
– Documentos XML, conjunto de ficheros.
● Resource Description Framework, RDF:
– Estructura de árbol, modelo de grafo.
– RDF/XML.
10. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Metadatos: elementos y
esquemas.
● El recurso u objeto es descrito usando
datos.
● Cada uno de esos datos se llama
elemento.
● Un conjunto de elementos diseñado para
un propósito específico es un esquema.
11. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Esquema de metadatos.
● Conjuntos de elementos de metadatos
diseñados para un propósito específico,
con reglas de uso.
● Definición de elementos: semántica.
● Definición de representación: reglas de
contenido.
● Definición de estructura: sintaxis.
● Ejemplos: Dublin Core EAD, TEI, LOM.
12. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Metadatos: Conceptos clave,1.
● Un esquema ampliamente aceptado y
usado se convierte en una especificación
de metadatos.
● Si lo reconoce una agencia de
normalización será un estándar o norma.
● Un perfil de aplicación es una
adaptación de un estándar o una
especificación a un contexto específico.
13. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Metadatos: Conceptos clave,2.
● Esquema de codificación: lista
controlada de valores aceptables con
sintaxis concreta.
● Tabla de equivalencias: especificación
para mapear entre normas de metadatos.
● Armonización: proceso de establecer
coherencia entre normas, para desarrollar
las tablas de equivalencias.
14. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Gestión de metadatos.
● Disponibilidad: debe ser almacenados
donde se pueda acceder a ellos.
● Calidad: debe ofrecer una calidad
consistente.
● Persistencia: debe asegurarse su
perduración a lo largo del tiempo.
● Licencia abierta: deben estar disponibles
con una licencia de dominio público que
haga posible su reutilización.
15. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
RDF.
● Modelo de grafo: unidades de información
conectadas por y con otras unidades de
información.
● El grafo está formado por tripletas.
● Tripleta: un sujeto conectado a un objeto.
● Los sujetos y algunos objetos se modelan
como clases, y describen tipos de recursos.
● Los predicados son propiedades, describen
relaciones.
● Se representan mediante URI, Uniform
Resource Identifier.
16. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Dublin Core (1995).
● Conjuntos de 15 elementos comunes a la
mayoría de objetos digitales.
● Norma ISO 15836, ANSI/NISO Z39.85.
● Versión extendida con calificadores:
DCTERMS.
● Singapore Framework for Dublin Core
Application Profiles: especificaciones del
uso del esquema para propósitos
específicos.
17. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Estándares para metadatos,1.
● Schema.org: 2011. Vocabulario RDF para
incluir semántica en páginas web. 600
tipos y 800 propiedades
● Web Ontology Language, OWL: sintaxis
para definir vocabularios para el web
semántico.
● Simple Knowledge Organization
System SKOS: codificar taxonomías,
tesauros, materias y otros esquemas de
clasificación.
18. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Estándares para metadatos,2.
● Friend of a Friend, FOAF: metadatos sobre personas y
organizaciones.
● Online Information eXchange, ONIX: intercambio de datos para
industrias editoras.
● Publishing Requirements for Industry Standard Metadata, PRISM.
● NewsML, rNews.
● Learning Objetc Metadata, LOM: recursos de aprendizaje.
● Exchangeable Image File Format, EXIF: metadatos para imágenes,
embebidos en el fichero.
● MPEG (7 y 21): descripción de objetos audiovisuales.
● Semantically-Interlinked Online Communities Project, SIOC.
● Text Encoding Initiative, TEI.
19. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
Estándares para objetos
culturales.
● Machine Readable Cataloging, MARC.
● Bibliographic Framework Initiative, BIBFRAME.
● Metadata Object Description Schema, MODS.
● Encoded Archival Description, EAD.
● CIDOC Conceptual Reference Model CIDOC CRM.
● Visual Resources Association Core, VRA Core.
● PREservation Metadata: Implementation Strategies,
PREMIS.
20. Aplicaciones para Recursos de Información Digital
Grado en Información y Documentación, Univ. de Zaragoza
Prof.Dr. J. Tramullas
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