Enabling European Archaeological Research: The ARIADNE E-Infrastructure

In the last 20 years, e-infrastructures have become ever more important for the conduct and progress of research in all branches of scientific enterprise. Increasingly collaborative, distributed and data-intensive research requires the sharing of resources (data, tools, computing facilities) via e-infrastructure as well as support for effective co-operation among research groups (ESF 2011; ESFRI 2016). Moreover there is the expectation that with large datasets ('big data'), e-infrastructure and advanced computing techniques, new scientific questions can be tackled. The archaeological research community has been an early adopter of various digital methods and tools for data acquisition, organisation, analysis and presentation of research results of individual projects. The provision of e-infrastructure and services for data sharing, discovery, access and re-use for the heritage sector is, however, lagging behind other research fields, such as the natural and life sciences. The consequence is a high level of fragmentation of archaeological data and limited capability for collaborative research across institutional and national as well as disciplinary boundaries (Aspöck and Geser 2014). This situation is being addressed by ARIADNE: the Advanced Research Infrastructure for Archaeological Dataset Networking in Europe. This e-infrastructure initiative is being promoted by a consortium of archaeological institutes, data archives and technology developers, and funded under the European Commission's Seventh Framework Programme (ARIADNE 2014a; Niccolucci and Richards 2013). ARIADNE enables archaeological data providers, large and small, to register and connect their resources (datasets, collections) to the e-infrastructure, and a data portal provides search, access and other services across the integrated resources. The portal puts into operation a proof of concept exemplar first developed under the ARENA (Archaeological Records of Europe Networked Access) project (Kenny and Richards 2005; Kilbride 2004), itself inspired by a proposal made by Hansen (1993). ARIADNE integrates resource discovery metadata using various controlled vocabularies, e.g. the W3C Data Catalogue Vocabulary (adapted for describing archaeological datasets), subject thesauri, gazetteers, chronologies, and the CIDOC Conceptual Reference Model (CRM). Based on this integration the data portal offers several ways to search and access resources made available by data providers located in different countries. ARIADNE thus acts as a broker between data providers and users and offers additional web services for products such as high-resolution images, Reflectance Transformation Imaging (RTI), 3D objects and landscapes. Employing such services in research projects or for content deposited in digital archives will greatly enhance the ability of researchers to publish, access and study archaeological content online. ARIADNE therefore represents a substantial advance for archaeology; in particular it provides a common platform where dispersed data resources can be uniformly described, discovered and accessed. It is also an essential step towards the even more ambitious goal of offering archaeologists integrated data, tools and computing resources for web-based research that creates new knowledge (e-archaeology). The next section describes the current landscape of data repositories and services for archaeologists in Europe, and the issues that make interoperability between them difficult to realise. The results of the ARIADNE user surveys undertaken to match expectations and requirements for the e-infrastructure and data portal services are then presented. The main part of the article describes ARIADNE's overall architecture, core services (data registration, discovery and access) and other extant or experimental services. A further section presents the on-going evaluation of the data integration and set of services. Finally, the article summarises some lessons already learned in the integration of data resources and services, and considers the prospects for the wider engagement of the archaeological research community in sharing data through the ARIADNE e-infrastructure and portal

Reflections on Excavating Archaeological Grey Literature: and on the Challenges in Information Extraction

The largely unpublished reports generated by commercial or “rescue” archaeology, commonly known as “grey literature” contain a great deal of untapped information, highly relevant to the research and analysis of archaeological evidence. The presentation unfolds experiences and challenges in using Natural Language Processing techniques for "unlocking" and surfacing information from unstructured textual input, delivering structured outputs which enable new information access methods, based on linking worded representations to ontological definitions and formalisations for the purposes of information retrieval from heterogeneous data sources. The role of Named Entity Recognition, Relation Extraction, Negation Detection, and Word-Sense Disambiguation is presentedin connection to a semantic annotation and automatic metadata generation endeavour, which spanned over ten years and two research projects, focusing on English, Dutch and Swedish grey literature

Information Extraction Techniques for the Purposes of Semantic Indexing of Archaeological Resources

The paper describes the use of Information Extraction (IE), a Natural Language Processing (NLP) technique to assist ‘rich’ semantic indexing of diverse archaeological text resources. Such unpublished online documents are often referred to as ‘Grey Literature’. Established document indexing techniques are not sufficient to satisfy user information needs that expand beyond the limits of a simple term matching search. The focus of the research is to direct a semantic-aware 'rich' indexing of diverse natural language resources with properties capable of satisfying information retrieval from on-line publications and datasets associated with the Semantic Technologies for Archaeological Resources (STAR) project in the UoG Hypermedia Research Unit. The study proposes the use of knowledge resources and conceptual models to assist an Information Extraction process able to provide ‘rich’ semantic indexing of archaeological documents capable of resolving linguistic ambiguities of indexed terms. CRM CIDOC-EH, a standard core ontology in cultural heritage, and the English Heritage (EH) Thesauri for archaeological concepts are employed to drive the Information Extraction process and to support the aims of a semantic framework in which indexed terms are capable of supporting semantic-aware access to on-line resources. The paper describes the process of semantic indexing of archaeological concepts (periods and finds) in a corpus of 535 grey literature documents using a rule based Information Extraction technique facilitated by the General Architecture of Text Engineering (GATE) toolkit and expressed by Java Annotation Pattern Engine (JAPE) rules. Illustrative examples demonstrate the different stages of the process. Initial results suggest that the combination of information extraction with knowledge resources and standard core conceptual models is capable of supporting semantic aware and linguistically disambiguate term indexing

Knowledge-Based Named Entity Recognition of Archaeological Concepts in Dutch

The advancement of Natural Language Processing (NLP) allows the process of deriving information from large volumes of text to be automated, making text-based resources more discoverable and useful. The attention is turned to one of the most important, but traditionally difficult to access resources in archaeology; the largely unpublished reports generated by commercial or “rescue” archaeology, commonly known as “grey literature”. The paper presents the development and evaluation of a Named Entity Recognition system of Dutch archaeological grey literature targeted at extracting mentions of artefacts, archaeological features, materials, places and time entities. The role of domain vocabulary is discussed for the development of a KOS-driven NLP pipeline which is evaluated against a Gold Standard, human-annotated corpus

Natural Language Processing for Under-resourced Languages: Developing a Welsh Natural Language Toolkit

Language technology is becoming increasingly important across a variety of application domains which have become common place in large, well-resourced languages. However, there is a danger that small, under-resourced languages are being increasingly pushed to the technological margins. Under-resourced languages face significant challenges in delivering the underlying language resources necessary to support such applications. This paper describes the development of a natural language processing toolkit for an under-resourced language, Cymraeg (Welsh). Rather than creating the Welsh Natural Language Toolkit (WNLT) from scratch, the approach involved adapting and enhancing the language processing functionality provided for other languages within an existing framework and making use of external language resources where available. This paper begins by introducing the GATE NLP framework, which was used as the development platform for the WNLT. It then describes each of the core modules of the WNLT in turn, detailing the extensions and adaptations required for Welsh language processing. An evaluation of the WNLT is then reported. Following this, two demonstration applications are presented. The first is a simple text mining application that analyses wedding announcements. The second describes the development of a Twitter NLP application, which extends the core WNLT pipeline. As a relatively small-scale project, the WNLT makes use of existing external language resources where possible, rather than creating new resources. This approach of adaptation and reuse can provide a practical and achievable route to developing language resources for under-resourced languages

Digital R&D Fund for the Arts in Wales

The Digital Research & Development Fund for the Arts in Wales is a partnership between Arts Council of Wales, the Arts & Humanities Research Council (AHRC) and Nesta. The Fund’s overarching purpose is “to enable the use of digital technologies in the arts sector to engage audiences in new ways and to create opportunities for new business models”. The Digital Research & Development Fund for the Arts in Wales has worked by encouraging arts organisations to connect with digital technology in order to undertake investigations from which the whole arts sector in Wales might learn. It has provided up to £400,000 in total to arts and cultural organisations during the period 2013/14 and 2014/15

Named Entity Recognition for early-modern textual sources: a review of capabilities and challenges with strategies for the future

Purpose: By mapping-out the capabilities, challenges and limitations of named-entity recognition (NER), this article aims to synthesise the state of the art of NER in the context of the early modern research field and to inform discussions about the kind of resources, methods and directions that may be pursued to enrich the application of the technique going forward. // Design/methodology/approach: Through an extensive literature review, this article maps out the current capabilities, challenges and limitations of NER and establishes the state of the art of the technique in the context of the early modern, digitally augmented research field. It also presents a new case study of NER research undertaken by Enlightenment Architectures: Sir Hans Sloane's Catalogues of his Collections (2016–2021), a Leverhulme funded research project and collaboration between the British Museum and University College London, with contributing expertise from the British Library and the Natural History Museum. // Findings: Currently, it is not possible to benchmark the capabilities of NER as applied to documents of the early modern period. The authors also draw attention to the situated nature of authority files, and current conceptualisations of NER, leading them to the conclusion that more robust reporting and critical analysis of NER approaches and findings is required. // Research limitations/implications: This article examines NER as applied to early modern textual sources, which are mostly studied by Humanists. As addressed in this article, detailed reporting of NER processes and outcomes is not necessarily valued by the disciplines of the Humanities, with the result that it can be difficult to locate relevant data and metrics in project outputs. The authors have tried to mitigate this by contacting projects discussed in this paper directly, to further verify the details they report here. // Practical implications: The authors suggest that a forum is needed where tools are evaluated according to community standards. Within the wider NER community, the MUC and ConLL corpora are used for such experimental set-ups and are accompanied by a conference series, and may be seen as a useful model for this. The ultimate nature of such a forum must be discussed with the whole research community of the early modern domain. // Social implications: NER is an algorithmic intervention that transforms data according to certain rules-, patterns- or training data and ultimately affects how the authors interpret the results. The creation, use and promotion of algorithmic technologies like NER is not a neutral process, and neither is their output A more critical understanding of the role and impact of NER on early modern documents and research and focalization of some of the data- and human-centric aspects of NER routines that are currently overlooked are called for in this paper. // Originality/value: This article presents a state of the art snapshot of NER, its applications and potential, in the context of early modern research. It also seeks to inform discussions about the kinds of resources, methods and directions that may be pursued to enrich the application of NER going forward. It draws attention to the situated nature of authority files, and current conceptualisations of NER, and concludes that more robust reporting of NER approaches and findings are urgently required. The Appendix sets out a comprehensive summary of digital tools and resources surveyed in this article

Using dates as contextual information for personalised cultural heritage experiences

We present semantics-based mechanisms that aim to promote reflection on cultural heritage by means of dates (historical events or annual commemorations), owing to their connections to a collection of items and to the visitors’ interests. We argue that links to specific dates can trigger curiosity, increase retention and guide visitors around the venue following new appealing narratives in subsequent visits. The proposal has been evaluated in a pilot study on the collection of the Archaeological Museum of Tripoli (Greece), for which a team of humanities experts wrote a set of diverse narratives about the exhibits. A year-round calendar was crafted so that certain narratives would be more or less relevant on any given day. Expanding on this calendar, personalised recommendations can be made by sorting out those relevant narratives according to personal events and interests recorded in the profiles of the target users. Evaluation of the associations by experts and potential museum visitors shows that the proposed approach can discover meaningful connections, while many others that are more incidental can still contribute to the intended cognitive phenomena

Semantic Representation and Location Provenance of Cultural Heritage Information: the National Gallery Collection in London

This paper describes a working example of semantically modelling cultural heritage information and data from the National Gallery collection in London. The paper discusses the process of semantically representing and enriching the available cultural heritage data, and reveals the challenges of semantically expressing interrelations and groupings among the physical items, the venue and the available digital resources. The paper also highlights the challenges in the creation of the conceptual model of the National Gallery as a Venue, which aims to i) describe and understand the correlation between the parts of a building and the whole; ii) to record and express the semantic relationships among the building components with the building as a whole; and iii) to be able to record the accurate location of objects within space and capture their provenance in terms of changes of location. The outcome of this research is the CrossCult venue ontology, a fully International Committee for Documentation Conceptual Reference Model (CIDOC-CRM) compliant structure developed in the context of the CrossCult project. The proposed ontology attempts to model the spatial arrangements of the different types of cultural heritage venues considered in the project: from small museums to open air archaeological sites and whole cities

D16.4: Final Report on Natural Language Processing

This document is a deliverable (D16.4) of the ARIADNE project (“Advanced Research Infrastructure for Archaeological Dataset Networking in Europe”), which is funded under the European Community's Seventh Framework Programme. It presents the final results of the work carried out in Tasks 16.2 “Natural Language Processing (NLP)”. The report presents one of the most important, but traditionally difficult to access resources in archaeology; the largely unpublished reports generated by commercial or “rescue” archaeology, commonly known as “grey literature”, exploring both rule-based and machine learning NLP methods, the use of archaeological thesauri in NLP, and various Information Extraction (IE) methods in their own language