A Domain-Specific Formal Ontology for Archaeological Knowledge Sharing and Reusing

Zhang, Chunxia; Cao, Cungen; Fang, Gengfa; Si, Jing

doi:10.1007/3-540-36277-0_20

Cited by 8 publications

(5 citation statements)

References 7 publications

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“…Typologies and nomenclatures are frequently contested and vary among specialist communities and individual researchers. This makes the development of global schema to represent archaeological information critically important (Zhang et al, 2002). One temptation would be to create rigid classbased standards of recording, data organization, vocabularies, typologies, etc.…”

Section: Experimental Methods In Archaeological Disseminationmentioning

confidence: 99%

A community approach to data integration: Authorship and building meaningful links across diverse archaeological data sets

Kansa

2005

Geosphere

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The ability to link and compare diverse archaeological data sets will catalyze innovative research of great scope and analytic rigor. However, information heterogeneity and limited budgets and information technology skills challenge data dissemination initiatives. This paper argues for new methods of community-based data integration pioneered by the University of Chicago's Extensible Markup Language (XML) System for Textual and Archaeological Research project (XSTAR). With XSTAR, data integration takes place in two steps: (1) syntactic-schematic integration: Legacy data sets are migrated for representation in the data structures described by the Archaeological Markup Language (ArchaeoML), and (2) Semantic integration: Mappings must be established between related terms and classes in each source database. Because the nuances of meaning are often very subtle, human experts must classify related items in each data set. Initial syntacticschematic mapping of data into XSTAR is simple and fast but occurs at a relatively abstract level of meaning. Nevertheless, this initial step can accommodate diverse archaeological (and other) data sets, and will facilitate community-led development of more semantically specific data integration. XSTAR hopes to enable multiple semantic data integration schemas to develop and keep pace with changing research agendas. though rooted in archaeology, this paper discusses challenges faced by many disciplines in encouraging more powerful diachronic and regional syntheses. ArchaeoML's highly generalized data model has applicability outside archaeology, especially with subdisciplines of the earth sciences yet to develop formal ontologies. In addition, because this is a community driven approach, incentives for community participation must be explored. Intellectual property and professional rewards are key factors in determining the success of online dissemination systems across many disciplines.

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Section: Experimental Methods In Archaeological Disseminationmentioning

confidence: 99%

A community approach to data integration: Authorship and building meaningful links across diverse archaeological data sets

Kansa

2005

Geosphere

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“…Although, other proposals were put forward for the archaeological excavation domain (e.g. Kansa 2005;Zhang et al 2002), the broad uptake of the CIDOC CRM by the cultural heritage sector and its accreditation as an ISO (International Organization for Standardization) standard in 2006 eventually triggered its further development and penetration into domain-specific implementations or facets that extended its usability, with significant impact across important elements of documentation in the archaeological and cultural heritage domains, illustrated by the creation of CRMdig, CRMsci, CRMinf, CRMarchaeo, CRMba and CRMgeo .…”

Section: The Current State Of the Artmentioning

confidence: 99%

Semantic Modelling of Archaeological Excavation Data. A review of the current state of the art and a roadmap of activities

Katsianis,

Bruseker,

Nenova

et al. 2023

Internet Archaeol.

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Archaeological data repositories usually manage excavation data collections as project-level entities with restricted capacities to facilitate search or aggregation of excavation data at the sub-collection level (trenches, finds, season reports or excavation diaries etc.). More granular access to excavation data collections would enable layered querying across their informational content. In the past decade, several attempts to adapt CIDOC CRM in order to provide more explicit descriptions of the excavation universe have resulted in the use of domain-specific model extensions (e.g. CRMarchaeo, CRMsci, CRMba). Each focuses on corresponding aspects of the excavation research process, while their combined usage has potential to support expressive data mappings at the sub-collection level. As part of the ARIADNEplus project, several CIDOC CRM developers and domain experts have collaborated to undertake conceptual mapping exercises, to address the practicalities of bringing excavation data descriptions together and to link these to our overall aspirations in terms of excavation data discoverability and reusability. In this contribution, we discuss the current state and future directions of the field of semantic representation of archaeological excavation data and consider several issues that constrain the applicability of existing solutions. We identify five key enabling technologies or research areas (Conceptual models and semantic data structures, Conceptual modelling patterns, Data mapping workflows and tools, Learning technologies and Semantic queries) and assign readiness levels to assess their level of technological maturity. Our research demonstrates that while the existing models and domain-specific extensions are deemed adequate, there is a need for more user-friendly methods and tools to structure data in meaningful and interoperable ways. The next steps involve consolidating relevant semantic structures, improving modelling implementation guidance, adhering to consistent workflows, developing engaging curricula, and documenting real-case examples to demonstrate the benefits and results of semantic data integration.

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“…Ontology defines the characteristics of a formal, explicit specification for a shared and common understanding of various domains (Zhang et al , 2002). A unified knowledge base developed in a digital archiving project for the National Museum of Natural Science (NMNS), Taiwan acts as the kernel component to integrate content from exhibition, education and collection resources in a museum.…”

Section: Introductionmentioning

confidence: 99%

Knowledge‐based mobile learning framework for museums

Hsu

Yang

2006

The Electronic Library

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Purpose -The purpose of this study is to propose a knowledge-based mobile learning framework that integrates various types of museum-wide content, and supports ubiquitous, context-aware, personalized learning for museums. Design/methodology/approach -A unified knowledge base with multi-layer reusable content structures serves as the kernel component to integrate content from exhibitions for education and collection in a museum. The How-Net approach is adopted to build a unified natural and cultural ontology. The ontology functions as a common and sharable knowledge concept that denotes each knowledge element in the unified knowledge base, and associates each learner's learning context and usage with a content and usage profile respectively. Data mining algorithms, e.g. association mining and clustering, are applied to discover useful patterns for ubiquitous personalization from these content and usage profiles. Findings -A pilot project based on the proposed framework has been successfully implemented in the Life Science Hall of the National Museum of Natural Science (NMNS), Taiwan, demonstrating the feasibility of this framework. Originality/value -This study proposes a mobile learning framework that can be replicated in many museums. This framework improves learners' learning experiences with rich related content, and with ubiquitous, proactive and adaptive services. Museums can also benefit from implementing this framework through outreach services for educational, promoting and usability needs from combining mobile and Internet communication technologies and learning services.

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A Domain-Specific Formal Ontology for Archaeological Knowledge Sharing and Reusing

Cited by 8 publications

References 7 publications

A community approach to data integration: Authorship and building meaningful links across diverse archaeological data sets

A community approach to data integration: Authorship and building meaningful links across diverse archaeological data sets

Semantic Modelling of Archaeological Excavation Data. A review of the current state of the art and a roadmap of activities

Knowledge‐based mobile learning framework for museums

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