BIM semantic-enrichment for built heritage representation

In the built heritage context, BIM has shown difficulties in representing and managing the large and complex knowledge related to non-geometrical aspects of the heritage. Within this scope, this paper focuses on a domain-specific semantic-enrichment of BIM methodology, aimed at fulfilling semantic representation requirements of built heritage through Semantic Web technologies. To develop this semantic-enriched BIM approach, this research relies on the integration of a BIM environment with a knowledge base created through information ontologies. The result is knowledge base system - and a prototypal platform - that enhances semantic representation capabilities of BIM application to architectural heritage processes. It solves the issue of knowledge formalization in cultural heritage informative models, favouring a deeper comprehension and interpretation of all the building aspects. Its open structure allows future research to customize, scale and adapt the knowledge base different typologies of artefacts and heritage activities

Semantic enrichment for enhancing LAM data and supporting digital humanities. Review article

With the rapid development of the digital humanities (DH) field, demands for historical and cultural heritage data have generated deep interest in the data provided by libraries, archives, and museums (LAMs). In order to enhance LAM data’s quality and discoverability while enabling a self-sustaining ecosystem, “semantic enrichment” becomes a strategy increasingly used by LAMs during recent years. This article introduces a number of semantic enrichment methods and efforts that can be applied to LAM data at various levels, aiming to support deeper and wider exploration and use of LAM data in DH research. The real cases, research projects, experiments, and pilot studies shared in this article demonstrate endless potential for LAM data, whether they are structured, semi-structured, or unstructured, regardless of what types of original artifacts carry the data. Following their roadmaps would encourage more effective initiatives and strengthen this effort to maximize LAM data’s discoverability, use- and reuse-ability, and their value in the mainstream of DH and Semantic Web

Producing Linked Open Dataset from Bibliographic Data with Integration of External Data Sources for Academic Libraries

This paper has focused on transformation of bibliographic data to linked open data (LOD) as RDF(Resource Description Framework) triple model with integration of external resources. Library & Information centres and knowledge centres deal with various types of databases like bibliographic databases, full text databases, archival databases, statistical databases, CD/DVD ROM databases and more. Presently, web technology changes storing, processing, and disseminating services rapidly. The semantic web technology is an advance technology of web platform which provides structured data on web for describing and retrieving by the organization or institutions. It may provide more information from other external resources to the users. The main objective of this paper is transformation of library bibliographic data, based on MARC21, to RDF triple format as LOD with enrichment of external LOD dataset. External resources like OpenLibrary, VIAF, Wikidata, DBpedia, GeoNames etc. We have proposed a Workflow model (Figure-1) to visualize details steps, activities, components for transforming bibliographic data to LOD dataset. The methodology of this work includes the various methods and steps for conducting such research work. Here we have used an open source tool OpenRefine (version 3.2), formally it is known as GoogleRefine. The OpenRefine tool is used for managing and organizing the messy data with different attribute like row-column manipulation, reconciliation manipulation, different format manipulation like XML, JSON, N-Triple, RDF etc. The OpenRefine tool has played the various roles for the research work such as insertion of URI column, link generation, reconciliation data for external sources, conversion of source format to RDF format etc. After conversion of whole bibliographic data into RDF triple format as considerable LOD dataset. At the production page we may find a RDF file of bibliographic data. This LOD dataset may further be used by the organizations or institutions for their advanced bibliographic service

Semantic enrichment for enhancing LAM data and supporting digital humanities. Review article

With the rapid development of the digital humanities (DH) field, demands for historical and cultural heritage data have generated deep interest the data provided by libraries, archives, and museums (LAMs). In order to enhance LAM data’s quality and discoverability while enabling a self-sustaining ecosystem, “semantic enrichment” becomes a strategy increasingly used by LAMs during recent years. This article introduces a number of semantic enrichment methods and efforts that can be applied to LAM data at various levels, aiming to support deeper and wider exploration and use of LAM data in DH research. The real cases, research projects, experiments, and pilot studies shared in this article demonstrate endless potential for LAM data, whether they are structured, semi-structured, or unstructured, regardless of what types of original artifacts carry the data. Following their roadmaps would encourage more effective initiatives and strengthen this effort to maximize LAM data’s discoverability, use- and reuse-ability, and their value in the mainstream of DH and Semantic Web

Still a Lot to Lose: The Role of Controlled Vocabulary in Keyword Searching

In their 2005 study, Gross and Taylor found that more than a third of records retrieved by keyword searches would be lost without subject headings. A review of the literature since then shows that numerous studies, in various disciplines, have found that a quarter to a third of records returned in a keyword search would be lost without controlled vocabulary. Other writers, though, have continued to suggest that controlled vocabulary be discontinued. Addressing criticisms of the Gross/Taylor study, this study replicates the search process in the same online catalog, but after the addition of automated enriched metadata such as tables of contents and summaries. The proportion of results that would be lost remains high

Exploring scholarly data with Rexplore.

Despite the large number and variety of tools and services available today for exploring scholarly data, current support is still very limited in the context of sensemaking tasks, which go beyond standard search and ranking of authors and publications, and focus instead on i) understanding the dynamics of research areas, ii) relating authors ‘semantically’ (e.g., in terms of common interests or shared academic trajectories), or iii) performing fine-grained academic expert search along multiple dimensions. To address this gap we have developed a novel tool, Rexplore, which integrates statistical analysis, semantic technologies, and visual analytics to provide effective support for exploring and making sense of scholarly data. Here, we describe the main innovative elements of the tool and we present the results from a task-centric empirical evaluation, which shows that Rexplore is highly effective at providing support for the aforementioned sensemaking tasks. In addition, these results are robust both with respect to the background of the users (i.e., expert analysts vs. ‘ordinary’ users) and also with respect to whether the tasks are selected by the evaluators or proposed by the users themselves

A semantic web approach for built heritage representation

In a built heritage process, meant as a structured system of activities aimed at the investigation, preservation, and management of architectural heritage, any task accomplished by the several actors involved in it is deeply influenced by the way the knowledge is represented and shared. In the current heritage practice, knowledge representation and management have shown several limitations due to the difficulty of dealing with large amount of extremely heterogeneous data. On this basis, this research aims at extending semantic web approaches and technologies to architectural heritage knowledge management in order to provide an integrated and multidisciplinary representation of the artifact and of the knowledge necessary to support any decision or any intervention and management activity. To this purpose, an ontology-based system, representing the knowledge related to the artifact and its contexts, has been developed through the formalization of domain-specific entities and relationships between them