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Provenance information is crucial for consistent maintenance of metadata schemas over time. The purpose of this paper is to propose a provenance model named DSP-PROV to keep track of structural changes of metadata schemas.

The DSP-PROV model is developed through applying the general provenance description standard PROV of the World Wide Web Consortium to the Dublin Core Application Profile. Metadata Application Profile of Digital Public Library of America is selected as a case study to apply the DSP-PROV model. Finally, this paper evaluates the proposed model by comparison between formal provenance description in DSP-PROV and semi-formal change log description in English.

Formal provenance description in the DSP-PROV model has advantages over semi-formal provenance description in English to keep metadata schemas consistent over time.

The DSP-PROV model is applicable to keep track of the structural changes of metadata schema over time. Provenance description of other features of metadata schema such as vocabulary and encoding syntax are not covered.

This study proposes a simple model for provenance description of structural features of metadata schemas based on a few standards widely accepted on the Web and shows the advantage of the proposed model to conventional semi-formal provenance description.

In the open data context, the shared data could come through many transformation processes, originating from many sources, which exposes the risk of non-authentic data. Moreover, each data set has different properties, shared under various licenses, which means the updated data could change its characteristics and related policies. This paper aims to introduce an effective and elastic solution to keep track of data changes and manage their characteristics within the open data platform. These changes have to be immutable to avoid violated modification and could be used as the certified provenance to improve the quality of data.

This paper will propose a pragmatic solution that focuses on the combination of comprehensive knowledge archive network – the broadest used open data platform and hyperledger fabric blockchain to ensure all the changes are immutable and transparent. As using smart contracts plus a standard provenance data format, all processes are running automatically and could be extended to integrate with other provenance systems and so the introduced solution is quite flexible to be used in different open data ecosystems and real-world application domains.

The research involves some related studies about the provenance system. This study finds out that most of the studies are focused on the commercial sector or applicable to a specific domain and not relevant for the open-data section. To show that the proposed solution is a logical and feasible direction, this paper conducts an experimental sample to validate the result. The testing model is running successfully with an elastic system architect and promising overall performance.

Open data is the future of many businesses but still does not receive enough attention from the research community. The paper contributes a novel approach to protect the provenance of open data.

The EarthCube Technology and Architecture Committee working groups needed current information on the development of existing EarthCube-funded projects (e.g. building blocks, conceptual designs, and research coordination networks) to fulfill the goals of the working groups (e.g. gap analysis, use cases, standards bodies and testbed). The aims of this study include a compilation of planned outcomes, an assessment of current work and an investigation of interests in research collaboration among select EarthCube-funded projects.

Twenty-four principal investigators of 24 different EarthCube projects completed the Funded Projects Questionnaire composed of 35 questions in March and April 2015.

The survey response rate was 100 per cent and included a diversity of results ranging from planning stages to early development to final development. The funded projects in this study received awards in 2013 and 2014.

The results are EarthCube-specific and are not generalizable. Suggestions for future research include integration of crosscutting disciplines and perspectives, best practices, guidelines and standards for broader impact.

This study identified potential collaboration opportunities, use cases and gaps (e.g. unmet architectural, functional, operational, organizational and/or technical needs).

The impact on society include an improved understanding of the various EarthCube-funded projects and potential for collaboration within and across multiple disciplines.

This study contributed to the development of select outputs for EarthCube-funded projects’ presentations, Tech Hands Meeting, 2015 All Hands Meeting, select working groups’ outcomes and EarthCube Strategic Technology Plan and is of value to stakeholders, scientists and users.

Exploring diverse knowledge organization systems and metadata schemes in linked data, aiming to promote vocabulary usability and high-quality linked data creation within the LIS field.

We used content analysis to select 77 articles from 13 library and information science journals around our research theme. We identified four dimensions: vocabularies participation, reuse, functions, and naming variations in linked data.

The vocabulary comprises seven main categories and their corresponding 126 vocabularies, which participate in linked data in single, two, and multiple dimensions. These vocabularies are used in the eight LIS subfields. Reusing vocabularies has become integral to linked data publishing, with six categories and their corresponding 66 vocabularies being reused. Ontologies are the most engaged and widely reused category of vocabulary in linked data practice. The mutual support among the three major categories and seven subfunctions of vocabulary promotes the sustainable development of linked data. Under a combination of factors, the phenomenon of terminology name changes and cross-usage between “vocabulary” and “ontology.”

This study has limitations. Although 77 articles on the topic of vocabularies applied in linked data were analyzed and presented with quantitative statistics and visualizations, the exploration of the topic tends to be a practical activity, with limited presence in scholarly articles. Moreover, this study’s analysis of the practical applications of linked data is relatively limited, and the sample literature focused on articles published in English, which may have affected the diversity and inclusiveness of the research sample.

Practically, this study does not confine the application of content analysis solely to the traditional exploration of knowledge organization topics, development trends, or course content. Instead, it integrates the dual perspectives of linked data and vocabularies, employing content analysis to analyze and objectively reveal the application issues of vocabularies in linked data. The conclusions can provide specific guidelines for future applications of vocabularies in the LIS subfields and contribute to promoting interoperability of vocabularies.

This research explores the relationship between linked data and vocabularies, highlighting the diverse manifestations and challenges of vocabularies in linked data. It provides theoretical references for the construction and further development of vocabularies considering technologies such as linked data, drawing attention to the potential and existing issues associated with linked open data vocabularies.

This study extends the application of content analysis to exploring vocabularies, especially Knowledge Organization Systems and metadata schemes in the LIS field linked data, highlighting the mutually beneficial interactions between linked data and vocabularies. It provides guidance for future vocabularies applications in the LIS field and offers insights into vocabularies construction and the healthy development of linked data ecosystems in the era of information technology.

The purpose of this study is to develop a conceptual model, ProvKOS, for tracking the provenance of change activities in a knowledge organization system (KOS). By extending current provenance practices, this model represents dynamic changes in a KOS more effectively.

We take a five-step approach to develop the conceptual model, including content analysis of KOS editorial data, environmental scan of existing provenance models, development of persona-specific provenance questions and a participatory design with stakeholders to ensure the model’s utility.

We introduce (1) a taxonomy of editorial activities for a KOS; (2) a conceptual model ProvKOS, which extends existing models PROV and Simple Knowledge Organization Systems (SKOS). We also provide detailed data dictionaries for the entities, activities and warrants classes proposed in the model. A use case on “gender dysphoria” in Dewey Decimal Classifications (DDCs) is provided to illustrate the implementation of ProvKOS. This shows ProvKOS’s ability to capture KOS changes effectively and to link external resources relating to the changes.

Further validation may be needed to implement the ProvKOS model across various types of KOSs.

ProvKOS can help improve machine readability, querying and analysis of a KOS. Especially within the linked data environment, the enhanced provenance documentation through ProvKOS can enable a network of KOSs, which will then inform better linked data or knowledge graph designs.

By facilitating better tracking of changes within a KOS and across KOSs, ProvKOS can enhance the accessibility and usability of knowledge bases across different cultural and social contexts, thus better supporting inclusive information practices.

The proposed model is novel in two ways: one, its ability to represent dynamic change activities in a KOS, which has not been discussed anywhere else; two, it supports the interconnectivity across KOSs by providing a “warrant” class to substantiate the context of changes.

Linked data is gaining great interest in the cultural heritage domain as a new way for publishing, sharing and consuming data. The paper aims to provide a detailed method and MARiMbA a tool for publishing linked data out of library catalogues in the MARC 21 format, along with their application to the catalogue of the National Library of Spain in the datos.bne.es project.

First, the background of the case study is introduced. Second, the method and process of its application are described. Third, each of the activities and tasks are defined and a discussion of their application to the case study is provided.

The paper shows that the FRBR model can be applied to MARC 21 records following linked data best practices, librarians can successfully participate in the process of linked data generation following a systematic method, and data sources quality can be improved as a result of the process.

The paper proposes a detailed method for publishing and linking linked data from MARC 21 records, provides practical examples, and discusses the main issues found in the application to a real case. Also, it proposes the integration of a data curation activity and the participation of librarians in the linked data generation process.

The purpose of this paper is to identify the concepts, component parts and relationships between vocabularies, linked data and knowledge graphs (KGs) from the perspectives of data and knowledge transitions.

This paper uses conceptual analysis methods. This study focuses on distinguishing concepts and analyzing composition and intercorrelations to explore data and knowledge transitions.

Vocabularies are the cornerstone for accurately building understanding of the meaning of data. Vocabularies provide for a data-sharing model and play an important role in supporting the semantic expression of linked data and defining the schema layer; they are also used for entity recognition, alignment and linkage for KGs. KGs, which consist of a schema layer and a data layer, are presented as cubes that organically combine vocabularies, linked data and big data.

This paper first describes the composition of vocabularies, linked data and KGs. More importantly, this paper innovatively analyzes and summarizes the interrelatedness of these factors, which comes from frequent interactions between data and knowledge. The three factors empower each other and can ultimately empower the Semantic Web.

Satellite images can be a powerful source of data for analyses of conflict dynamics and social movements, but sociology has been slow to develop methods and metadata standards for transforming those images into data. We ask: How can satellite images become useful data? What are the key methodological and ethical considerations for incorporating high-resolution satellite images into conflict research? Why are metadata important in this work? We begin with a review of recent developments in satellite-based social scientific work on conflict, then discuss the technical and epistemological issues raised by machine processing of satellite information into user-ready images. We argue that high-resolution images can be useful analytical tools provided they are used with full awareness of their ethical and technical parameters. To support our analysis, we draw on two novel studies of satellite data research practices during the Syrian war. We conclude with a discussion of specific methodological procedures tried and tested in our ongoing work.

The need for inclusive and logically consistent representation of diverse and even confronting viewpoints on the domain knowledge has been widely discussed in the literature in the past decade. The purpose of this paper is to propose a generic model for building an open coherent diversified knowledge organization system (KOS).

The proposed model incorporates a generic epistemological component, the validity scope type, assigned to each statement in the constructed KOS. Statements are clustered by their association with various validity scope types into internally coherent subsystems. These subsystems form a knowledge organization network connected through the universal (consensual) subsystems with more than one validity scope type. The model extends the Galili’s Cultural Content Representation paradigm, which divides the knowledge content of a scientific theory into two confronting parts: body and periphery.

The knowledge organization network model makes it possible to comparatively examine similarities and differences among various viewpoints and theories on the domain knowledge. The presented approach conforms with the principle of Open Knowledge Network initiative for creation of open accessible knowledge.

The proposed model can be used for ontological reasoning by a variety of information services, such as ontology-based decision-support and learning systems, diversified search and customer management applications.

The model enables explicit representation of social and cultural minority voices and historical knowledge in the KOS.

The main contribution of the proposed model is that it generalizes and enhances various previously proposed representations of epistemological aspects of KOS and allows for multiple inter-linked subsystems to coherently co-exist as part of the extensible network.

The purpose of this paper is to review ontologies and data models currently in use for augmented reality (AR) applications, in the cultural heritage (CH) domain, specifically in an urban environment. The aim is to see the current trends in ontologies and data models used and investigate their applications in real world scenarios. Some special cases of applications or ontologies are also discussed, as being interesting enough to merit special consideration.

A search using Google Scholar, Scopus, ScienceDirect and IEEE Xplore was done in order to find articles that describe ontologies and data models in AR CH applications. The authors identified the articles that analyze the use of ontologies and/or data models, as well as articles that were deemed to be of special interest.

This review found that CIDOC-CRM is the most popular ontology closely followed by Historical Context Ontology (HiCO). Also, a combination of current ontologies seems to be the most complete way to fully describe a CH object or site. A layered ontology model is suggested, which can be expanded according to the specific project.

This study provides an overview of ontologies and data models for AR CH applications in urban environments. There are several ontologies currently in use in the CH domain, with none having been universally adopted, while new ontologies or extensions to existing ones are being created, in the attempt to fully describe a CH object or site. Also, this study suggests a combination of popular ontologies in a multi-layer model.