• DARIAH EU
• 2012-2021close
• Other literature type close
• European Commission close
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The article presents a method for automatic semantic indexing of archaeological grey‐literature reports using empirical (rule‐based) Information Extraction techniques in combination with domain‐specific knowledge organization systems. The semantic annotation system (OPTIMA) performs the tasks of Named Entity Recognition, Relation Extraction, Negation Detection, and Word‐Sense Disambiguation using hand‐crafted rules and terminological resources for associating contextual abstractions with classes of the standard ontology CIDOC Conceptual Reference Model (CRM) for cultural heritage and its archaeological extension, CRM‐EH.Relation Extraction (RE) performance benefits from a syntactic‐based definition of RE patterns derived from domain oriented corpus analysis. The evaluation also shows clear benefit in the use of assistive natural language processing (NLP) modules relating to Word‐Sense Disambiguation, Negation Detection, and Noun Phrase Validation, together with controlled thesaurus expansion.The semantic indexing results demonstrate the capacity of rule‐based Information Extraction techniques to deliver interoperable semantic abstractions (semantic annotations) with respect to the CIDOC CRM and archaeological thesauri. Major contributions include recognition of relevant entities using shallow parsing NLP techniques driven by a complimentary use of ontological and terminological domain resources and empirical derivation of context‐driven RE rules for the recognition of semantic relationships from phrases of unstructured text.

Abstract. Formal ontologies such as CIDOC CRM (Conceptual Reference Model) form part of the central strategy for the medium and longterm integration of cultural heritage data to allow for its greater valorization and dissemination. Despite this, uptake of CIDOC CRM at the ground level of Cultural Heriage (CH) practice is limited. Part of the reason behind this lack of uptake lies in the fact that ontologies are considered too complicated and abstract for application in real life scenarios. This paper presents the rationale behind and the design of a CIDOC CRM game, the intent of which is to provide a learning mechanism to allow learners of wide backgrounds and interests to approach CIDOC CRM in a hands-on and interactive fashion. The CIDOC CRM game consist of decks of cards and game boards that allow players to engage with the concepts of a formal ontology in relation to real data in an entertaining and informative way. It is argued that the CIDOC CRM Game can form an important part of introducing the basic elements of formal ontology and this standard to a wider audience in order to aid wider understanding and adoption of the same.

Abstract The solid geometry of archaeological deposits is fundamental to the interpretation of their chronological sequence. However, such stratigraphic sequences are generally viewed as static two-dimensional diagrammatic representations which are difficult to manipulate or to relate to real layers. The ADS 3D Viewer is a web-based resource for the management and analysis of archaeological data. The viewer was developed to take advantage of recent developments in web technology, namely the adoption of WebGL (Web Graphics Library) by current web browsers. The ADS 3D Viewer combines the potential of the 3D Heritage Online Presenter (3DHOP), a software package for the web-based visualization of 3D geometries, with the infrastructure of the Archaeology Data Service (ADS) repository, in the attempt to create a platform for the visualization and analysis of 3D data archived by the ADS. Two versions of the viewer have been developed to answer the needs of different users. The first version, the Object Level 3D Viewer , was implemented to extend the browsing capability of ADS project archives by enabling the visualization of single 3D models. The second version, the Stratigraphy 3D Viewer , is an extension which allows the exploration of a specific kind of aggregated data: the multiple layers of an archaeological stratigraphic sequence. This allows those unable to participate directly in the fieldwork to access, analyse and re-interpret the archaeological context remotely. This has the potential to transform the discipline, allowing inter-disciplinary, cross-border and ‘at-distance’ collaborative workflows, and enabling easier access to and analysis of archaeological data.

Purpose – The purpose of this paper is to present the role and contribution of natural language processing techniques, in particular negation detection and word sense disambiguation in the process of Semantic Annotation of Archaeological Grey Literature. Archaeological reports contain a great deal of information that conveys facts and findings in different ways. This kind of information is highly relevant to the research and analysis of archaeological evidence but at the same time can be a hindrance for the accurate indexing of documents with respect to positive assertions. Design/methodology/approach – The paper presents a method for adapting the biomedicine oriented negation algorithm NegEx to the context of archaeology and discusses the evaluation results of the new modified negation detection module. A particular form of polysemy, which is inflicted by the definition of ontology classes and concerning the semantics of small finds in archaeology, is addressed by a domain specific word-sense disambiguation module. Findings – The performance of the negation dection module is compared against a “Gold Standard” that consists of 300 manually annotated pages of archaeological excavation and evaluation reports. The evaluation results are encouraging, delivering overall 89 per cent precision, 80 per cent recall and 83 per cent F-measure scores. The paper addresses limitations and future improvements of the current work and highlights the need for ontological modelling to accommodate negative assertions. Originality/value – The discussed NLP modules contribute to the aims of the OPTIMA pipeline delivering an innovative application of such methods in the context of archaeological reports for the semantic annotation of archaeological grey literature with respect to the CIDOC-CRM ontology.

The CENDARI infrastructure is a research-supporting platform designed to provide tools for transnational historical research, focusing on two topics: medieval culture and World War I. It exposes to the end users modern Web-based tools relying on a sophisticated infrastructure to collect, enrich, annotate, and search through large document corpora. Supporting researchers in their daily work is a novel concern for infrastructures. We describe how we gathered requirements through multiple methods to understand historians' needs and derive an abstract workflow to support them. We then outline the tools that we have built, tying their technical descriptions to the user requirements. The main tools are the note-taking environment and its faceted search capabilities; the data integration platform including the Data API, supporting semantic enrichment through entity recognition; and the environment supporting the software development processes throughout the project to keep both technical partners and researchers in the loop. The outcomes are technical together with new resources developed and gathered, and the research workflow that has been described and documented. International audience