Find> Find Notes = Metal Returned 100+ results: 100+ RRAD, 100+ LEAP, 27 OASIS Find Notes = Metal > Within Context > Context Type = Hearth Returned = 6 results: 5 LEAP, 1 OASIS
Closer examination shows that 2 of the 6 LEAP results are in fact samples, rather than finds and misattributed in the STAR data extraction. It was not realised that LEAP samples are held within the general finds table in the dataset and indicated as samples by a code in the table. This illustrates the complexity of mapping/extracting data to the CRM; it is not simply a matter of mapping database tables or columns to ontology elements – see further discussion in section 4.2, where a solution is outlined.
Searching the Notes field as free text tends to be less reliable than searching Types (although it can yield results otherwise not found). Employing concept-based search:
Find type = Metalworking debris Returned 94 results: 42 LEAP, 52 MoLA ROP Find Type = Metalworking debris > within context> Context type = Hearth: debris Returned = 1 LEAP
- an ash layer of hearth [3681] used for possible production of nails.
Broadening the search to industrial working more generally,
Context Find = Slag Returned 47 results: 25 OASIS, 7 LEAP, 11 MoLA ROP , 4 RRAD Context Find = Slag > within Context > Context Type = hearth Returned 7 results: 7 OASIS
We see that results are returned across the various datasets and that seven grey literature results associate evidence of slag with hearths. While these results show the potential of searching on controlled types, the current semantic search does not perform the query expansion that might associate hearth with hearth: debris, assuming they were semantically connected in any underlying thesaurus (further discussed in section 4.4).
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| File last updated: Mon July 18 2011