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Dates, periods and timespans are described in archaeological datasets using a number of different textual patterns for which myriad variations exist, rendering direct automated comparison difficult. The issue can occur even within records from the same dataset and is further compounded when attempting to integrate multilingual data – particularly where dates may be expressed in words rather than numbers. The same problem can be found in temporal metadata, whether manually entered or generated via Natural Language Processing (NLP) techniques from reports and grey literature. Resolving and normalizing dates and periods to internationally agreed standard formats enables efficient data integration, interchange, search, comparison and visualization. This paper reports on the design and implementation of a tool to normalize temporal expressions to a numerical time axis and reflects on key issues. Textual patterns for seven categories of temporal expression have been normalized: Ordinal named or numbered centuries; Year spans; Single year (with tolerance); Decades; Century spans; Single year with prefix; Named periods. The following languages are currently supported: Dutch, English, French, German, Italian, Norwegian, Spanish, Swedish, Welsh. Methods are described together with an (open source) normalization tool developed in Python and four applications of the method are discussed, together with limitations and future work. Results are presented from diverse data sets and languages. The input is a temporal text string and a language code (ISO639-1). The output is a tab delimited text file with start/end years (in ISO 8601 format), relative to Common Era (CE). The normalized outputs are provided as additional attributes along with the original text expression for consuming software to employ in end-user applications.

This article discusses the outcomes of research undertaken by the Hypermedia Research Group at the University of South Wales in collaboration with the OASIS team at the Archaeology Data Service in the Linked Data for the Historic Environment (LD4HE) project. The new OASIS system allows stakeholders to record information/events accurately and consistently, using established heritage and spatial vocabularies, including those currently available via the Heritage Data platform. The LD4HE project explores one avenue of enhancing the potential re-use of information recorded by OASIS and making connections with other online data collections. LD4HE enables the creation and export of RDF from the new OASIS V system, a major step towards the production of Linked Data. The main outcomes comprise a conceptual mapping between mandatory OASIS fields and the standard CIDOC-CRM ontology, together with a template-based tool to convert records exported from OASIS to a corresponding RDF representation. A set of SPARQL queries demonstrates the outcomes of the data conversion. New specialised vocabularies required by OASIS have been published as linked data on the Heritage Data platform. The methods are described and illustrated with examples. Reflections on the case study and cost/benefit considerations for Linked Data conversion are discussed, together with possible strategies for reducing the costs of producing Linked Data.

Research e-infrastructures, digital archives and data services have become important pillars of scientific enterprise that in recent decades has become ever more collaborative, distributed and data-intensive. The archaeological research community has been an early adopter of digital tools for data acquisition, organisation, analysis and presentation of research results of individual projects. However, the provision of e-infrastructure and services for data sharing, discovery, access and re-use has lagged behind. This situation is being addressed by ARIADNE: the Advanced Research Infrastructure for Archaeological Dataset Networking in Europe. This EU-funded network has developed an e-infrastructure that enables data providers to register and provide access to their resources (datasets, collections) through the ARIADNE data portal, facilitating discovery, access and other services across the integrated resources. This article 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 surveys on users' expectations and requirements are also presented. The main section of the article describes the architecture of the e-infrastructure, core services (data registration, discovery and access) and various other extant or experimental services. The on-going evaluation of the data integration and services is also discussed. Finally, the article summarises lessons learned, and outlines the prospects for the wider engagement of the archaeological research community in sharing data through ARIADNE.

Differing terminology and database structure hinders meaningful cross search of excavation datasets. Matching free text grey literature reports with datasets poses yet more challenges. Conventional search techniques are unable to cross search between archaeological datasets and Web-based grey literature. Results are reported from two AHRC funded research projects that investigated the use of semantic techniques to link digital archive databases, vocabularies and associated grey literature. STAR (Semantic Technologies for Archaeological Resources) was a collaboration between the University of Glamorgan, Hypermedia Research Unit and English Heritage (EH). The main outcome is a research Demonstrator (available online), which cross searches over excavation datasets from different database schemas, including Raunds Roman, Raunds Prehistoric, Museum of London, Silchester Roman and Stanwick sampling. The system additionally cross searches over an extract of excavation reports from the OASIS index of grey literature, operated by the Archaeology Data Service (ADS). A conceptual framework provided by the CIDOC Conceptual Reference Model (CRM) integrates the different database structures and the metadata automatically generated from the OASIS reports by natural language processing techniques. The methods employed for extracting semantic RDF representations from the datasets and the information extraction from grey literature are described. The STELLAR project provides freely available tools to reduce the costs of mapping and extracting data to semantic search systems such as the Demonstrator and to linked data representation generally. Detailed use scenarios (and a screen capture video) provide a basis for a discussion of key issues, including cost-benefits, ontology modelling, mapping, terminology control, semantic implementation and information extraction issues. The scenarios show that semantic interoperability can be achieved by mapping and extracting different datasets and key concepts from OASIS reports to a central RDF based triple store. It is not necessary to expose the full detail of the ontological model; the Demonstrator shows that user interfaces for retrieval (or mapping) systems can be expressed using familiar archaeological concepts. Working with the CRM-EH archaeological extension of the CIDOC CRM ontology allows specific archaeological queries, while permitting interoperability at the more general CRM level, potentially extending to other areas of cultural heritage. The ability to connect published datasets with the hitherto under-utilised grey literature holds potential for meta studies, where aggregate patterns can be compared and hypotheses for future detailed investigation uncovered. Connecting the interpretation with the underlying context data via the semantic model facilitates the revisiting of previous interpretations by third parties, the possibility of juxtaposing parallel interpretations, or exposing the data to new research questions.