The Alma ILS supports both MARC and BIBFRAME data formats and includes a RESTful API for their customers to use in creating and editing BIBFRAME Work and BIBFRAME Instance data in Alma. Building on prior API driven integrations (https://youtu.be/Q0-ABLG4dyQ ) of linked data editors and the Alma ILS, this presentation will explore the opportunities of connecting BIBFRAME data in Alma to entity management software from the Share Family LOD Platform technology.
The JCricket entity editor is a manual entity editor from the Share Family designed to facilitate the management, editing and creation of entities for bibliographic and authority data. Within their discovery system, the Penn Libraries is planning on displaying work clusters that are retrieved from the Share LOD Platform APIs (https://upenn.box.com/s/k4fxbnez5zuelpk3xohp0q9xq0uqw16x ). Therefore, there is a need for catalogers to have the ability to curate or otherwise align data from the Alma ILS with LOD Platform clusters. A related tie-in that will be explored in this presentation is the ability for new BIBFRAME resources that are stored in the Alma system at Penn to be immediately reflected in the clustering available from LOD Platform APIs.
Assessing data quality of Linked Open Data in Cultural Heritage institutions
Dişli, Meltem & Candela, Gustavo
Cultural Heritage (CH) institutions have been exploring new ways to make their digital collections available. New initiatives have emerged to promote computational access and reuse in innovative ways in which high-quality data is essential. This session will present a reproducible approach to assessing data quality in Linked Open Data (LOD) repositories made available by CH institutions. The session includes an overview of the importance of assessing LOD quality, followed by a concise introduction to the data quality criteria, which are based on a literature review, the existing vocabularies used to describe data quality, and how Jupyter Notebook can be used to assess LOD repositories in a reproducible manner. The primary aim of this session is to facilitate best practices and guidelines in order to assess the data quality of LOD repositories, ensuring their broader adoption and reproducibility.
The application of Linked Data in libraries is not new. Libraries have started to take advantage of Linked Data for increased visibility and availability of their resources on the Web. For libraries, adopting linked data principles initiates a transformation moving bibliographic data away from library-specific MARC format to new web-based formats. While Linked Data is considered the necessary next step to make library resources more robust and easier to access, the reality of full Linked Data adoption is still far from ideal even with its promising benefits. Most empirical literature on Linked Data for libraries offers a landscape view of the rationale for Linked Data adoption and how to publish library bibliographic data as Linked Data. The majority of Linked Data initiatives occur in North America and Europe. Research on the library use of Linked Data in Asia, particularly in Taiwan, is limited. This study looks at the current state of Linked Data implementation among Taiwan academic libraries. An investigation is conducted to understand library professionals’ perceptions of Linked Data and their attitudes toward engaging in Linked Data implementation. In addition, by utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, this study is also to identify what factors influence library professionals’ intention to use Linked Data technologies in transforming library bibliographic data into Linked Data to connect library resources with many other resources on the Web.