Webinars in 2017

Save the Children (STC) is an international NGO that promotes children’s rights, provides relief and helps support children across the globe. With international headquarters in London, STC has 30 national members and supports local partners operating in over 100 countries worldwide. STC International maintains technical infrastructures that are available to members and local partners including SharePoint, Drupal and other information management applications. An effort to specify and implement a common resource library for curating and sharing internal technical resources has been underway since November 2015. This has included an inventory of existing (but heterogeneous) resource libraries on Save the Children’s work in the thematic area of Health and Nutrition, and agreement on a common metadata specification and some controlled vocabularies to be used going forward. This internal technical resource library has been aligned with Save the Children’s Resource Centre, a public web-accessible library that hosts comprehensive, reliable and up-to-date information on Save the Children’s work in the thematic areas of Child Protection, Child Rights Governance and Child Poverty.

This webinar will demonstrate how to design and build rich end-user search and discovery applications using Linked Data. The Linked Open Data cloud is a rapidly growing collection of publicly accessible resources, which can be adopted and reused to enrich both internal enterprise projects and public-facing information systems. The webinar will use the Linked Canvas application as its primary use-case. Linked Canvas is an application designed by Synaptica for the cultural heritage community. It enables high-resolution images of artworks and artifacts to be catalogued and subject indexed using Linked Data. The talk will demonstrate how property fields and relational predicates can be adopted from open data ontologies and metadata schemes, such as DCMI, SKOS, IIIF and the Web Annotation Model. Selections of properties and predicates can then be recombined to create Knowledge Organization Systems (KOS) customized for business applications. The demonstration will also illustrate how very-large-scale subject taxonomies and name authority files, such as the Library of Congress Name Authority File, DBpedia, and the Getty Linked Open Data Vocabularies collection, can be used for content enrichment and indexing. There will be a brief discussion of the general principles of graph databases, RDF triple stores, and the SPARQL query language. This technical segment will discuss the pros and cons of accessing remote server endpoints versus cached copies of external Linked Data resources, as well as the challenge of providing high-performance full text search against graph databases. The webinar will conclude by providing a demonstration of Linked Canvas to illustrate various end-user experiences that can be created with Linked Data technology: faceted search across data collections; pinch and zoom navigation inside images; the exploration of concepts and ideas associated with specific points of interest; the discovery of conceptually related images; and the creation of guided tours with embedded audio-visual commentary.

Um perfil de aplicação de metadados (MAP) é um constructo que fornece um modelo semântico para publicação de dados na Web de Dados. Este modelo semântico não é mais do que um modelo de dados com a definição de propriedades e restrições às propriedades. Cada propriedade é apresentada com um termo de um vocabulário RDF associado, com a definição do domínio e contra-domínio e ainda a sua cardinalidade. De acordo com o documento da DCMI “Os níveis de interoperabilidade para os metadados Dublin Core” um MAP é um constructo que potencia a interoperabilidade semântica dos dados. O que isto realmente significa é que quando uma comunidade de prática decide pôr-se de acordo em seguir um MAP, isto é, em seguir um conjunto de regras para publicar os seus dados como Linked Open Data, isso permite que os dados publicados na LOD cloud sejam processados automaticamente por agentes de software. Um MAP é portanto um constructo de muita importância, e por isso é essencial a existência de um método para o seu desenvolvimento. É muito importante fornecer aos modeladores de MAPs uma base comum de entendimento para que o desenvolvimento de um MAP deixe de ser um conjunto não sistemático de actividades e passe a ser algo mais organizado de forma a resultar em MAPs de melhor qualidade. Este Webinar apresenta o Me4MAP, um método para o desenvolvimento de perfis de aplicação de metadados. O Me4MAP é uma proposta que foi desenvolvida no âmbito de um projecto de doutoramento e que está ainda a ser testada e aperfeiçoada. É uma proposta que parte de uma perspectiva de engenharia de software. E, acima de tudo, é um um ponto de partida para o estudo e o desenho de métodos para o desenvolvimento de MAPs.

A metadata application profile (MAP) is a construct that provides a semantic model for enhancing interoperability when publishing to the Web of Data. With a MAP, each property is defined as an RDF vocabulary term with the definition of domain, range, and cardinality. According to the DCMI document "Interoperability Levels for Dublin Core™ Metadata", a MAP is a construct that enhances semantic interoperability. Therefore, when a community of practice agrees to follow a MAP's set of rules for publishing data as Linked Open Data, it makes it possible for such data published the LOD cloud to be processed automatically by software agents.

With the increasing number of repositories, standards and resources we manage for digital libraries, there is a growing need to assess, validate and analyze our metadata - beyond our traditional approaches such as writing XSD or generating CSVs for manual review. Being able to further analyze and determine measures of metadata quality helps us better manage our data and data-driven development, particularly with the shift to Linked Open Data leading many institutions to large-scale migrations. Yet, the semantically-rich metadata desired by many Cultural Heritage Institutions, and the granular expectations of some of our data models, makes performing assessment, much less going on to determine quality or performing validation, that much trickier. How do we handle analysis of the rich understandings we have built into our Cultural Heritage Institutions' metadata and enable ourselves to perform this analysis with the systems and resources we have? This webinar sets up this question and proposes some guidelines, best practices, tools and workflows around the evaluation of metadata used by and for digital libraries and Cultural Heritage Institution repositories. What metrics have other researchers or practitioners applied to measure their definition of quality? How do these metrics or definitions for quality compare across examples – from the large and aggregation-focused, like Europeana, to the relatively small and project-focused, like Cornell University Library's own SharedShelf instance? Do any metadata assessment frameworks exist, and how do they compare to the proposed approaches in core literature in this area, such as Thomas Bruce and Diane Hillmann's 2004 article, "The Continuum of Metadata Quality"? The Digital Library Federation Assessment Interest Group (or DLF AIG) has a Metadata Working Group that has been attempting to build a framework that can be used broadly for digital repository metadata assessment - the state of this work, and the issues it has raised, will be discussed in this webinar as well. Finally, how does one begin to approach this metadata assessment – what tools, applications, or efforts for performing assessment exist for common digital repository applications or data publication mechanisms? This webinar hopes to provide some solutions to these questions within existing literature, work, and examples of metadata assessment happening 'on the ground'. The goal is for webinar participants to walk away prepared to handle their own metadata assessment needs by using the existing work outlined and being better aware of the open questions in this domain.

There is a growing interest in the publication and consumption of data on the Web. Government and non-governmental organizations already provide a variety of data on the Web, some open, others with access restrictions, covering a variety of domains such as education, economics, ECommerce and scientific data. Developers, journalists, and others manipulate this data to create visualizations and perform data analysis. Experience in this area reveals that a number of important issues need to be addressed in order to meet the requirements of both publishers and data consumers.

Existe um interesse crescente na publicação e consumo de dados na Web. Organizações governamentais e não-governamentais já disponibilizam uma variedade de dados na Web, alguns abertos, outros com restrições de acesso, abrangendo diversos domínios como educação, economia, segurança, patrimônio cultural, eCommerce e dados científicos. Desenvolvedores, jornalistas e outras pessoas manipulam esses dados para criar visualizações e realizar análises de dados. A experiência neste tema revela que é necessário abordar várias questões importantes a fim de satisfazer os requisitos tanto dos publicadores como dos consumidores de dados. Neste webinar discutiremos os principais desafios enfrentados pelos publicadores e consumidores de dados ao compartilharem dados na Web. Também introduziremos o conjunto de Boas Práticas, propostas pelo W3C, para enfrentar esses desafios. Finalmente, discutiremos os benefícios de envolver os publicadores de dados na utilização das Boas Práticas, bem como melhorar a forma que os conjuntos de dados são disponibilizados na Web.

Many libraries are experimenting with publishing their metadata as Linked Data to open up bibliographic silos, usually based on MARC records, to the Web. The libraries who have published Linked Data have all used different data models for structuring their bibliographic data. Some are using a FRBR-based model where Works, Expressions and Manifestations are represented separately. Others have chosen basic Dublin Core, dumbing down their data into a lowest common denominator format. The proliferation of data models limits the reusability of bibliographic data. In effect, libraries have moved from MARC silos to Linked Data silos of incompatible data models. There is currently no universal model for how to represent bibliographic metadata as Linked Data, even though many attempts for such a model have been made.