Boolean Logic

The article describes and explains Boolean logic (or Boolean algebra) in its two principal forms: that of truth-values and the Boolean connectives and, or, and not, and that of set membership and the set operations of intersection, union and complement. The main application areas of Boolean logic to know­ledge organization, namely post-coordinate indexing and search, are introduced and discussed. Some wider application areas are briefly mentioned, such as: propositional logic, the Shannon-style approach to electrical switching and logic gates, computer programming languages, probability theory, and database queries. An analysis is offered of shortcomings that Boolean logic has in terms of potential uses in know­ledge organization.

Knowledge Big Graph Fusing Ontology with Property Graph: A Case Study of Financial Ownership Network

The scale of know­ledge is growing rapidly in the big data environment, and traditional know­ledge organization and services have faced the dilemma of semantic inaccuracy and untimeliness. From a know­ledge fusion perspective-combining the precise semantic superiority of traditional ontology with the large-scale graph processing power and the predicate attribute expression ability of property graph-this paper presents an ontology and property graph fusion framework (OPGFF). The fusion process is divided into content layer fusion and constraint layer fusion. The result of the fusion, that is, the know­ledge representation model is called know­ledge big graph. In addition, this paper applies the know­ledge big graph model to the ownership network in the China’s financial field and builds a financial ownership know­ledge big graph. Furthermore, this paper designs and implements six consistency inference algorithms for finding contradictory data and filling in missing data in the financial ownership know­ledge big graph, five of which are completely domain agnostic. The correctness and validity of the algorithms have been experimentally verified with actual data. The fusion OPGFF framework and the implementation method of the know­ledge big graph could provide technical reference for big data know­ledge organization and services.

Representation and Display of Digital Images of Cultural Heritage: A Semantic Enrichment Approach

Digital images of cultural heritage (CH) contain rich semantic information. However, today’s semantic representations of CH images fail to fully reveal the content entities and context within these vital surrogates. This paper draws on the fields of image research and digital humanities to propose a systematic methodology and a technical route for semantic enrichment of CH digital images. This new methodology systematically applies a series of procedures including: semantic annotation, entity-based enrichment, establishing internal relations, event-centric enrichment, defining hierarchy relations between properties text annotation, and finally, named entity recognition in order to ultimately provide fine-grained contextual semantic content disclosure. The feasibility and advantages of the proposed semantic enrichment methods for semantic representation are demonstrated via a visual display platform for digital images of CH built to represent the Wutai Mountain Map, a typical Dunhuang mural. This study proves that semantic enrichment offers a promising new model for exposing content at a fine-grained level, and establishing a rich semantic network centered on the content of digital images of CH.

Confronting and Addressing Historical Discriminations through KOS: A Case Study of Terminology in the Becker-Eisenmann Collection

While historical cultural materials inform users of the past, they may also contain language that perpetuates long-entrenched patterns of discrimination. In organizing and providing access to such materials, cultural heritage institutions must negotiate historical language and context with the comprehension and perspectives of modern audiences. Excerpted from a larger project exploring representation and access around historical terminology and personal identity, the present work offers insight into how knowl­edge organization systems may be used to help modern users confront and make sense of past, discriminatory language in the archive. Using keywords drawn from the titles of 19th and 20th sideshow performer photographs, this work details the construction of a mapping dictionary that brings together corresponding terminology from several vocabulary sources along with annotations designed to explain historical terms to modern audiences. The development of this dictionary revealed several major types of problematic and potentially discriminatory language including historical euphemisms, misnomers, outdated terms, and sensationalist monikers. The finished dictionary offers opportunities to address these through explanatory annotations and to provide a richer, multi-perspective approach to subject analysis for these and other historical materials.

Data Documents

This article presents and discusses different kinds of data documents, including data sets, data studies, data papers and data journals. It provides descriptive and bibliometric data on different kinds of data documents and discusses the theoretical and philosophical problems by classifying documents according to the DIKW model (data documents, information documents, knowl­edge documents and wisdom documents). Data documents are, on the one hand, an established category today, even with its own data citation index (DCI). On the other hand, data documents have blurred boundaries in relation to other kinds of documents and seem sometimes to be understood from the problematic philosophical assumption that a datum can be understood as “a single, fixed truth, valid for everyone, everywhere, at all times”