KOS-based enrichment of archaeological fieldwork reports

Ceri Binding, Doug Tudhope*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Semantic enrichment techniques and tools based on knowledge organization systems (KOS) have an important role to play in supporting information discovery. This paper reports on work investigating and developing automatic indexing techniques (for final intellectual judgment) based on KOS. Within the UK, the OASIS online index of fieldwork events and their unpublished reports represent a major initiative to make archaeological fieldwork available to a wider public. OASIS is hosted by the Archaeology Data Service and is funded by Historic England and Historic Environment Scotland. A wide variety of organisations provide OASIS reports. Subject indexing is inconsistent and sometimes sparse, although use of standard KOS from the Forum on Information Standards in Heritage is encouraged. Results from a case study for an automatic (KOS-based) subject indexing recommendation system are reported. Findings include the need to extend the KOS entry vocabularies and the need for post-processing filters to prioritise subject indexing significant for the document in question. The paper reflects on the experience with future work in mind, including discussion of evaluation issues and positioning the approach within the context of previous work on subject indexing, automatic indexing for Name Authorities and Named Entity Recognition (NER). The techniques followed in the case study can be characterised as a hybrid approach. The purpose for which the indexing is applied is a key distinguishing feature. In this case, the purpose or indexing policy for OASIS goes beyond overall aboutness to request indexers to include significant objects or artefacts found during the project. Future work will investigate contextual patterns reflecting significance and incorporate those patterns in post-processing prioritisation measures.

Original languageEnglish
Pages (from-to)292 - 299
Number of pages8
JournalKnowledge Organization
Volume51
Issue number5
DOIs
Publication statusPublished - 12 Aug 2024

Keywords

  • automatic subject indexing
  • knowledge organization systems
  • named entity recognition

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