ネットワーク情報環境におけるメタデータの長期利用性向上のためのメタデータスキーマの来歴記述に関する研究

筑波大学 (University of Tsukuba)201

Improving Discovery of and Access to Digital Repository Contents Using Semantic Web Standards: Columbia University’s Academic Commons

This article describes the progress made towards developing Academic Commons (AC), Columbia University’s digital repository, as an interoperable repository through the use of RDF and non-RDF Semantic Web technologies. Approaches taken include the implementation of microdata to add semantic markup to HTML content; a collaboration with Oregon State University’s (OSU) digital repository, ScholarsArchive@OSU (SA@OSU), to implement an application that indexes RDF data from OSU for use in AC; as well as an exploration of the recently released MODS RDF

Highlights of library data models in the era of Linked Open Data

Semantic Web technologies and Linked data form a new reference framework for libraries. The library community aims to integrate its data with the Semantic Web and as a result new library data models have been developed. In this context, significant research effort focuses on the alignment between the library models with relevant models developed by other communities in the cultural heritage domain. However there exist several issues concerning the interoperability between all these data models. This paper seeks to contribute in the interoperability of four models, namely FRBR, FRBRoo, EDM and BIBFRAME. It highlights the commonalities and the divergences between them by using a case bibliographic record and by exploring how this record is represented by each one of them

Spatial ontologies for architectural heritage

Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications

CrossCult D2.4 Refined digital cultural resource data & data structure

This report presents the CrossCult digital datasets of the four project pilots.It contains a description of the methods and data structures used to semantically model and ingest the digital resources of the pilots into the CrossCult Knowledge Base following the semantics of the CrossCult Upper-level ontology, a set of examples of semantic enrichment, information retrieval and association discovery among the pilots’ resources and other related information in the CrossCult Knowledge Base,and a brief description of how the pilots’ digital resources can be viewed and access through three different front-end application

Semantic Data Management in Data Lakes

In recent years, data lakes emerged as away to manage large amounts of heterogeneous data for modern data analytics. One way to prevent data lakes from turning into inoperable data swamps is semantic data management. Some approaches propose the linkage of metadata to knowledge graphs based on the Linked Data principles to provide more meaning and semantics to the data in the lake. Such a semantic layer may be utilized not only for data management but also to tackle the problem of data integration from heterogeneous sources, in order to make data access more expressive and interoperable. In this survey, we review recent approaches with a specific focus on the application within data lake systems and scalability to Big Data. We classify the approaches into (i) basic semantic data management, (ii) semantic modeling approaches for enriching metadata in data lakes, and (iii) methods for ontologybased data access. In each category, we cover the main techniques and their background, and compare latest research. Finally, we point out challenges for future work in this research area, which needs a closer integration of Big Data and Semantic Web technologies

Using Semantic Web technologies in the development of data warehouses: A systematic mapping

The exploration and use of Semantic Web technologies have attracted considerable attention from researchers examining data warehouse (DW) development. However, the impact of this research and the maturity level of its results are still unclear. The objective of this study is to examine recently published research articles that take into account the use of Semantic Web technologies in the DW arena with the intention of summarizing their results, classifying their contributions to the field according to publication type, evaluating the maturity level of the results, and identifying future research challenges. Three main conclusions were derived from this study: (a) there is a major technological gap that inhibits the wide adoption of Semantic Web technologies in the business domain;(b) there is limited evidence that the results of the analyzed studies are applicable and transferable to industrial use; and (c) interest in researching the relationship between DWs and Semantic Web has decreased because new paradigms, such as linked open data, have attracted the interest of researchers.This study was supported by the Universidad de La Frontera, Chile, PROY. DI15-0020. Universidad de la Frontera, Chile, Grant Numbers: DI15-0020 and DI17-0043