## 4 Expansion of previous work  
### Dataset derived metadata - feature metadata  
Attribute data have the potential for considerable contribution towards automated documentation given their role in explicating the discrete features that constitute a dataset; tapping this potential is nevertheless complicated by the variety of ways in which attributes may be ordered and encoded. One option is to index commonly occurring values from those semi-structured attribute fields not conforming to specific data standards; as the data are encoded in an inconsistent fashion however, any extraction routine run will necessitate human mediation of each candidate metadata value returned. Spatial data standards impose a predictable structure on attribute schema and can thus address this need for constant review, but their diversity complicates selection even prior to contemplating interoperability-related concerns [38] and the bloat their verbosity can add to data preparation and upkeep. A more concise alternative for enforcing predictable attribute structure is proposed, one that allows for the association of a metadata schema with the features of each dataset - and in turn, address concerns articulated by [PERSON] [39] and [PERSON] _et al._[40] relating to the depiction of geometric primitives. Accordingly, the approach allows for the consistent referencing of member fields whilst providing a mechanism for tracking a dataset's atomic features. Distinct from conventional theme-driven standards, the proposed feature metadata approach was designed to be:  
* domain-independent, compatible with existing standard-based techniques and yet easily extensible to permit flexible adoption
* associated specifically with the geometric component of a dataset, thereby disengaging feature metadata from potentially inter-changeable theme-based data and enabling its persistence
* straightforward to apply to existing data models, with potential for automated completion at the point of survey of new geographic features
* capable of contributing towards automating metadata creation at the dataset level without complicating data creation and maintenanceWhile a review of existing (published) feature metadata strategies did present a number of pre-existing alternatives (most notably the State of Maine's GIS Feature Metadata Recommendation 20002), none met all of the above conditions. As a consequence the current paper elaborates a course more closely aligned with ISO-based practices, heeding the stated developments in the standards community. Footnote 2: [[http://apollo.ogis.state.me.us/standards/flmeta/fmrecommend.htm](http://apollo.ogis.state.me.us/standards/flmeta/fmrecommend.htm)]([http://apollo.ogis.state.me.us/standards/flmeta/fmrecommend.htm](http://apollo.ogis.state.me.us/standards/flmeta/fmrecommend.htm))  
ISO 19115:2005 Geographic Information - Metadata [41] for instance details a content schema for the documentation of geospatial data, but its focus lies with the depiction of geospatial resources at the dataset, and to a lesser degree, dataset series level. Metadata at the sub-dataset level are presented within a metadata hierarchy, but suggested implementations only include definitions at these levels when exceptions occur. Further, as metadata conforming to ISO 19115 are held discrete from the resources they describe by convention - regardless of its granularity - this treatment for metadata is on its own insufficient when reviewed for the current purpose. The ISO 19109:2005 Geographic Information - Rules for Application Schema standard meanwhile allows for the definition of conceptual data models that define the logical structure of an application's data [42]. Geographic feature types are classified based on a structure defined by the General Feature Model (GFM); feature type definitions (detailing feature attributes, operations and association roles) may be elaborated in feature catalogues.