Open archives initiative. Protocol for metadata harvesting (OAI-PMH): descripción, funciones y aplicaciones de un protocolo

Barrueco, José Manuel; Coll, Imma Subirats

doi:10.1076/epri.12.2.99.15473

Cited by 16 publications

(5 citation statements)

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“…A general outline of the process is shown in Figure 3. Our methodology uses the principles proposed in [42]. Its main insight is the use of KOS combined with geospatial ranking functions for finding the most relevant toponyms associated with a footprint and then compare these with place names described in the metadata.…”

Section: Methodsmentioning

confidence: 99%

“…This step is optional if we have access to some kind of metadata dump. The process of metadata harvesting consists in collecting metadata descriptions stored in digital repositories using protocols such as OAI-PMH [42] or Search/Retrieve via URL (SRU) 2 In our case we are using the SRU protocol. The SRU protocol uses three types of operations: explain, scan and searchRetrieve.…”

Section: Harvestingmentioning

confidence: 99%

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Improving the geospatial consistency of digital libraries metadata

Rentería-Agualimpia

López-Pellicer

Lacasta

et al. 2015

Journal of Information Science

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Consistency is an essential aspect of the quality of metadata. Inconsistent metadata records are harmful: given a themed query, the set of retrieved metadata records would contain descriptions of unrelated or irrelevant resources, and would even do not contain some resources considered obvious. This is even worse in when the description of the location is inconsistent. Inconsistent spatial descriptions may yield invisible or hidden geographical resources that cannot be retrieved by means of spatially themed queri es. Therefore, ensuring spatial consistency should be a primary goal when reusing, sharing and developing georeferenced digital collections. We present a methodology able to detect geospatial inconsistencies in metadata collections based on the combination of spatial ranking, reverse geocoding, geographic knowledge organization systems, and information retrieval techniques. This methodology has been applied to a collection of metadata records describing maps and atlases belonging to the Library of Congress. The proposed approach was able to identify automatically inconsistent metadata records (870 out of 10,575) and propose fixes to most of them (91.5%) These results support that the proposed methodology could assess the impact of spatial inconsistency in the retrievability and visibility of metadata records and improve their spatial consistency.

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Section: Methodsmentioning

confidence: 99%

Section: Harvestingmentioning

confidence: 99%

Improving the geospatial consistency of digital libraries metadata

Rentería-Agualimpia

López-Pellicer

Lacasta

et al. 2015

Journal of Information Science

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“…Sin embargo, a medida que estas plataformas se han vuelto esenciales para la publicación y difusión de investigaciones, surgen nuevas necesidades para los editores y académicos. (1,2,3,4,5) En muchas ocasiones, los editores de revistas académicas anhelan obtener una visión más profunda y contextual de sus publicaciones más allá de los informes básicos que proporcionan los sistemas web de las revistas como el OJS). (6,7) En ocasiones resulta oportuno explorar las redes de autoría o identificar la coocurrencia de términos clave en sus artículos, con la finalidad de realizar una presentación efectiva de sus revistas, llevar a cabo evaluaciones previas a la inclusión en bases de datos, seleccionar categorías adecuadas para sus revistas con vistas a su postulación para indexación en bases de datos, identificar las principales áreas de investigación o llevar a cabo análisis bibliométricos de sus contenidos.…”

Section: Introductionunclassified

Generación de grafos a partir de metadatos de revistas científicas con el sistema OAI-PMH

Gonzalez-Argote,

Gonzalez-Argote

2023

Seminars in Medical Writing and Education

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Access to scientific and scholarly information has become more accessible than ever before, in large part due to the proliferation of scholarly journals that use metadata systems to expose their content. Notable examples of these systems include the Open Journal Systems (OJS) and the Objects of Learning Metadata Protocol (OAI-PMH), which have significantly simplified the dissemination of research online. However, as these platforms have become essential for research publication and dissemination, new needs arise for publishers and scholars. A technological innovation-type study was conducted by generating codes for primary data generation with the ultimate goal of generating graphs for co-authorship networks and co-occurrence of terms. This paper focuses on a solution to this growing demand for enriched information. We will explore how generating graphs from scholarly journal metadata using the OAI-PMH system can address these specific needs. The generation of graphs from scholarly journal metadata using the OAI-PMH system and Python codes offers a powerful and versatile approach to the analysis of scholarly output. This study demonstrates the applicability of this methodology in the generation of keyword co-occurrence networks and co-authorship networks, providing a deeper and more contextual view of scientific publications. The relevance of this application extends to editors of academic journals as well as to scholars and researchers. For publishers, this tool facilitates the effective presentation of their journals, the evaluation of the quality and content of publications, the selection of categories for indexing, and the identification of emerging trends. On the other hand, for academics, this methodology fosters collaboration, enables more advanced bibliometric analyses, facilitates the presentation of results, and supports informed decision-making in their research areas.

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“…Currently (July 2018) the repository has 39.942 available titles, 63.294 authors and 6 areas of knowledge. CONICET Digital adopted the well-known DSpace platform to implement the repository, like most software to create repositories, DSpace supports OAI-PMH (Open Archive Initiative Protocol for Metadata Harvesting) [2] as an interface to expose the stored metadata. Although OAI-PMH is well known in the field of repositories, it is rarely known in other areas what makes integration with information from other domains difficult.…”

Section: Introductionmentioning

confidence: 99%

Improving Open Science Using Linked Open Data: CONICET Digital Use Case

Zárate

Buckle

Mazzanti

et al. 2019

JC&ST

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Scientific publication services are changing drastically, researchers demand intelligent search services to discover and relate scientific publications. Publishersneed to incorporate semantic information to better organize their digital assets and make publications more discoverable. In this paper, we present the on-going work to publish a subset of scientific publications of CONICET Digital as Linked Open Data. The objective of this work is to improve the recovery andreuse of data through Semantic Web technologies and Linked Data in the domain of scientific publications.To achieve these goals, Semantic Web standards and reference RDF schema’s have been taken into account (Dublin Core, FOAF, VoID, etc.). The conversion and publication process is guided by the methodological guidelines for publishing government linked data. We also outline how these data can be linked to other datasets DBLP, WIKIDATA and DBPEDIA on the web of data. Finally, we show some examples of queries that answer questions that initially CONICET Digital does not allow

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Open archives initiative. Protocol for metadata harvesting (OAI-PMH): descripción, funciones y aplicaciones de un protocolo

Cited by 16 publications

References 0 publications

Improving the geospatial consistency of digital libraries metadata

Improving the geospatial consistency of digital libraries metadata

Generación de grafos a partir de metadatos de revistas científicas con el sistema OAI-PMH

Improving Open Science Using Linked Open Data: CONICET Digital Use Case

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