Objective #1: Develop a Common Logical Data Model for Cultural Resources
Three associated tasks addressed this objective:
- Model entities, spatial/non-spatial database links, and specify metadata
- Review model with partners and distribute model to outside reviewers
- Revise model based on comments
As mentioned in the introduction, all logical data modeling tasks were accomplished through a US Geological Survey grant to develop metadata and data content standards for cultural resources. This provided an opportunity to expand the collaboration to involve many more western states (and even some east of the Mississippi!) and generated considerable interest and support from federal land management agencies. Although the process of creating a formal data standard will involve several additional levels of review and take several years, we were able to create a solid foundation for current cultural resource GIS efforts at the New Mexico and Wyoming SHPOs. The preliminary report on the first FGDC workshop appears in Appendix 2 and is available on-line at:
Briefly, the FGDC workshop had three components. First, participants were introduced to the National Spatial Database Infrastructure concept and metadata documentation standards and tools. We were aided in this effort by the University of New Mexico, Earth Data Analysis Center. Second, the group focused on identifying basic cultural resource data entities and specifying key attribute (i.e., non-spatial) data for management. Finally and this was key to the success of this grant workshop participants developed a spatial data model for the major cultural resource data entities and identified key metadata items Owing to a widespread need to accommodate large amounts of highly variable legacy data in existing CRISs, this task might best be seen as a “best practices” guide rather than a data standard.
The following discussion briefly describes cultural resource data entities and their interrelationships as defined by the FGDC Workshop Best practices recommendations for spatial data representation and metadata are then presented.
Entity Definitions and Relationships
To minimize confusion, we have adopted National Register of Historic Places (NRHP) terms and definitions for historic property types:
“The National Register of Historic Places includes significant properties, classified as buildings, Sites, districts, Structures, or objects (NRHP Bulletin 15: p. 4).
Definitions for these five categories of historic properties are fully described in National Register Bulletin #15 and will not be repeated here Subsequent NRHP Bulletins have accommodated Historic and Cultural Landscapes (Bulletins 18, 30) and Traditional Cultural Properties (Bulletin 38), but these property types still fall within the original definitions provided in Bulletin 15.
To build a logical model it was necessary to focus on how historic property types are related to each other. The NRHP is not concerned with such relationships at a logical level. For example, buildings, sites, districts, structures, and objects are all considered as historic properties but districts had to be separated out from the other four historic property types to recognize and preserve the complex relationships that exist between districts and their constituent properties. to Only one additional major entity (Investigations) had to be added to the model to create a logical data model for cultural resource management.
Figure 1 illustrates a first order data model for cultural resources management. The model is built around three major data entities with geospatial references:
- Resource an individual building, structure, object, or site. A historic property constituting the smallest unit of management considered by the NRHP.
- Resource Aggregation a defined historic property consisting of a collection of two or more Resources related by proximity and/or a common theme An area, referred to as a district or landscape by NRHP, created to manage Resources contained within an explicitly defined area, or a set of dispersed but thematically related Resources; Resource aggregations may also be related to each other in a parent-child fashion, for example to link together historic districts associated with a common theme.
- Investigation: an event or activity resulting in the identification, documentation, restoration, rehabilitation or preservation of historic properties Investigations may, or may not (in the case of “negative” identification efforts), relate to one or more historic properties Common examples of investigations include inventory, excavation, documentation, and restoration activities.
- Visit: the observational record relating a specific Investigation with a specific Resource or Resource Aggregation. When linked to a Visit, date-stamped observations on resource condition, status, and boundary definitions allow long-term maintenance of property “histories.” Visits relate properties to investigations in a many-to-many fashion, a property may be the focus of more than one investigation, and a single investigation may involve multiple historic properties. Visits insure that the integrity of these relationships are maintained.
- Investigation Aggregation: a collection of two or more Investigations related through a common, usually management-related, undertaking. This entity provides a reliable means of relating multiple investigation events or phases (e g., overview, inventory, data recovery, etc. ) with a larger undertaking (e g, a federal project or permit, a long-term research project) Undertakings may also be linked to other undertakings through a parent-child relationship.
- Publication: a report or other document describing a single investigation. This was determined to be a one-to-many relationship an investigation may produce multiple publications (or none), but a publication may describe only one investigation.
These three entities are considered minor because geospatial references were considered either optional (Visits) or not relevant (Investigation Aggregations and Publications) by workshop participants. Other entities relating to management processes were suggested during the workshop (e.g., Management Areas) but are not described here.
Non-spatial attributes for all major entities were considered at some length during the initial FGDC Workshop in Glorieta, NM, and then refined at a second meeting in Denver in February 1999. Given the primary emphasis of this project on spatial data models, we will refer readers to the on-line FGDC reports, rather than reproduce this information here.
As stated earlier, the need to accommodate legacy data necessitated a “best practices” approach. The problems of legacy data are perhaps most critical when spatial data are considered. Many important historic properties have been located without a great concern for source scale or positional accuracy. Maps have gotten better over the years and new technologies, such as the Global Positioning System, make spatial representation easier and more accurate. Management needs dictate that less accurate old data be utilized until updated locations can be obtained, so the accuracy and reliability of this data must be documented through metadata Our efforts were aimed at meeting these needs.
Best practices dictate that cultural resource entities be represented as follows:
- Minimal: centroids or line segments. This option is most appropriate for legacy data where information on size and/or shape is either unknown or unreliable. Also appropriate for very small cultural resources that cannot be represented accurately at the scale of the source graphics (e.g., largest resource dimension is less than National Map Accuracy Standards).
- Better: buffered points or lines. Resource boundaries are “calculated” by buffering a centroid or line segment with some estimate of resource size (e g., area, length, width).
- Even Better: minimum bounding rectangle. Resource boundaries are roughly approximated by a rectangle.
- Best: boundary polygon. Resource boundaries accurately represented by a polygon.
Best practices also indicate the need for a great deal of flexibility in how cultural resources are represented. To wit:
- cultural resources may overlap spatially.
- a single cultural resource entity may have multiple boundaries definitions relating to separate investigation events (e.g. , redefinitions of archeological site boundaries).
- a single cultural resource entity may be represented as the union of multiple objects and object types (i.e., points, lines, or polygons; e.g., an archeological inventory of an oil well pad and associated access road, a historic trail and associated buildings).
- a single cultural resource entity may have different types of boundaries (e.g., National Register vs. State Register boundaries; legal vs. traditional boundaries.
The implications of these facts for the design of a GIS or database are significant. Cultural resource location and configuration can be a complex matter and feature representation must take many factors into consideration. The most important decisions are related to how the information will be used. What are the data needs of CRIS system users? A national database of National Register Properties can probably rely on simple point and line locations at a fairly gross scale, but a state or local CRIS may need accurate property boundaries and large scale base maps to’ be able to make many planning decisions (e.g., “is this trench going to affect the county courthouse?”). Whatever level of accuracy is appropriate, the need for comprehensive spatial metadata is critical. When legacy data are involved, data should be maintained at the level of the individual feature (e.g., “cultural resource X was located using GPS its location is accurate to within 10 meters”).
Recommended locational methods and associated metadata are as follows:
- Minimal: map-derived coordinates based on UTM or State Plane coordinates, Latitude/Longitude, etc. Metadata source map identification, scale, date; Coordinate system zone, datum. (Note the Public Land Survey System (PLSS) is not a locational system, but some institutions use “Township/Range/Section/Aliquot units” to locate cultural resources –this is not recommended, but it is better than nothing! The PLSS Meridian must be included if this system is used).
- Better: Global Positioning System (GPS)-derived coordinatesbased on UTM or State Plane coordinates, Latitude/Longitude, etc. Metadata: estimate of positional accuracy (e g, Standard Deviation = ± >100, 10-lOOm, 1-lOm,
- Best: Cadastral survey or parcel map coordinates based on UTM or State Plane coordinates, Latitude/Longitude, etc Metadata estimate of positional accuracy.