McCary Fluted Point Survey^®

Photograph of Clovis points taken at an early meeting of the Archeological Society of Virginia (ASV). It is signed by E. B. Sacrey (October 29, 1941), who was the first ASV Secretary. This Folsom/Clovis interest would eventually become the McCary Fluted Point Survey of Virginia.

Ben McCary operated the Survey for approximately 30 years. He turned the Survey over to Michael Johnson and Joyce Pearsall who operated the Survey during the 1990s. They turned the Survey over to Jack Hranicky who runs the Survey. The count is 1000+ fluted paleopoints.

Introduction

In 1982, Louis Brennan compiled a fluted point list for the Eastern States Archeological Federation (ESAF) member societies. It was called the Archaeology of Eastern North America (AENA) Project that compiled 5820 Clovis points for the eastern seaboard. Since this compilation, the number of reported Clovis points has been ten-fold, and there is no way to estimate the number of fluted points in the so-called cigar box of points that granddad had. With appropriate publicity and selling the idea of recording fluted points, there are still a large number of fluted points to be recorded for archaeology’s knowledge base. While the basic definition of a fluted (Clovis) point differs among archaeologists, the classic one is Wormington (1957), the Clovis point is:

                    Fluted lanceolate points with parallel or slightly convex sides and concave bases. They range in length from one and a half to five inches but are usually some three inches or more in length and fairly heavy. The flutes sometimes extend almost the full length of the point but usually they extend no more than half way from the base to the tip. Normally, one face will have a longer flute than the other. The fluting was generally produced by the removal of multiple flakes. In most instances the edges of the basal portion show evidence of smoothing by grinding. Certain fluted points found in the eastern United States resemble the Clovis type, but they have a constriction at the base which produces a fish-tailed effect. These have sometimes been called Ohio points or Cumberland points. Many of these tend to be somewhat narrower relative to their length than other fluted points.

The earliest published Clovis (see drawing b) point in Virginia is Holmes (1897).

Surveys have, if only for this reason, proven that Clovis technology originated in the Southeast and that Mason’s (1962) paper argument was correct:

            … fluted points of every description except Folsom are far more numerous in the East, particularly in the Southeastern United States … and this area has produced the greatest diversification in fluted point styles.

 Brennan’s AENA Project set forth to prove Mason’s Eastern Argument and, in doing so, clearly amplified the need to record Clovis points on a state-by-state basis. He does note: The fluted point is, at the moment, without a parent. This model for a survey is a continuation of the AENA Project’s basic goal – recording Clovis points.

A survey is an excellent example of archaeology without artifacts in that archaeology is a science for the accumulation of knowledge, not a science for the accumulation of artifacts. Naturally, artifacts and all their masses are part of archaeology – the evidences of the past, but their purpose is to produce data and information about the antiquity of humans. A survey simply records data from a specialized resource in prehistory. These data are then translated, reconfigured, compiled, etc. into histories. The artifacts loan their physical presence to the survey for recordation, then go home to whomever owns them. A survey is then not a short-term curation process for these specimens; it is a long-term curation for the data that these artifacts contain. A survey contributes to the philosophy for knowledge in the study of antiquities.

 Lhile use of and the operation of a fluted point survey varies nationally, a survey’s justification generally includes an archaeological perspective of:

 A survey is an information producing enterprise with roots in the old days of Indian artifact collecting (Figure 1). Several of the older surveys were stated simply as bragging rights for counting individual ownership’s points within amateur societies. As surveys (and societies) matured, the scientific enterprise became the guidelines, and progress has moved the concept of the survey into what can be called the database of history. Hranicky (2003a) provides an overview and justification for a fluted point survey, but noted several years ago by Hranicky (1989), there is a tremendous amateur and collector involvement in recording Clovis points. And a survey must recognize and approach the collector and art worlds of antiquity ownerships – or, simply, go where the points are.

Figure 1 – McCary’s 1947 of Virginia Fluted Point Number 221.

Label has the same information that was published by the Survey in the

Quarterly Bulletin of the Archeological Society of Virginia.

A survey is a record-and-publish operation. Private vs. public ownership of antiquities is not a crusading ideology for any survey. A survey must recognize that the artifact world is divided into collections: those inside and those outside archaeology. And, furthermore, a survey is neither an artifact traffic cop to stop illegal looting and selling of artifacts nor an artifact banker to set monetary values on points. However, in a humoristic perspective, a survey should avoid the Clovis Police in attempting scientific studies from collected data.

Nomenclature and Terminology

 Standardized nomenclature and terminology are basic requirements for recording and documenting survey points. Nomenclature is, of course, part of the classification process which, by its vocabulary, conveys meaning and results to other archaeological researchers. Hranicky (2004) provides a guide for standards in archaeology.

 For example, the term “Clovis” has numerous definitions in the literature; in fact, most archaeologists create their personal definitions when writing research results. For this publication, Clovis is used generically for all Paleoindian points, fluted or unfluted. Hranicky and Johnson (2004) provide photographs of approximately 400 McCary Survey points. These points show a wide range of styles, manufacturing methods, lithic materials, and functional uses. When viewing the total paleopoint population, there is Clovis and there is not Clovis. Thus, a Clovis absolute definition is never achievable in archaeology; but most points have enough attributes and traits to make themselves recognizable.

Basic Modeling

 There are many archaeological modeling techniques, and selecting or building a model for paleopoint surveys involves understanding their operations and purposes in prehistory. A state-wide survey is an enormous task involving recording, recordkeeping, and reporting point data. This model and publication is based on the operation of the McCary Fluted Point Survey^® of Virginia. It can be used freely to design, establish, and implement paleopoint surveys in other states.

 The principal factors in setting up a fluted point survey are determining membership and chronological range for paleopoints. Questions to be asked: Is it solely Clovis, open to any fluted point, and what standards are applied in determining classification for these categories? Basic references, such as Justice (1989), Perino (1985 and 1991), Hranicky (2003), and Hranicky and Johnson (2004), offer insights for making these determinations, but as suggested, written criteria for standards and acceptance policy offer the best way to ensure database validity and credibility. If the survey is not used for all paleopoints, then classification and nomenclatures should be written and implemented regarding point inclusions. Figure 2 shows basic archaeological relationships for a point in a survey.

 While counting numbers of fluted points found in a state may be an interesting past time, this practice offers little data for the study of Paleoindian technology in the U.S. Most archaeologists would concur that all data be collected from discovered fluted points and maintaining these data for access to all scholars is a high priority in archaeology. However, the type of discovery still causes concern in the professional community. The only argument is: valid data produce valid information. This model offers survey architecture, provides a basic survey operation, and presents practical factors needed to make a survey work. The survey database should comply to standard industry designs, for example Fleming and von Halle (1989).

Figure 2 – Establishing Basics for Recording Paleopoints in a Survey

 Regional and national surveys provide massive amounts of point data. Unless searchable, these data can be overwhelming to researchers. Their major faults lie in finding, updating and validating point data from various surveys. The ideal location is the state-level institution where access and maintenance can be controlled and monitored by both the amateur and professional archaeological communities. As described below, data collecting requires strict methodologies to ensure that data are valid and trustworthy.

 This survey model’s focus requires recording data, storing data, and reporting data that are available to anyone who requests survey data for scholarly research. This model does not suggest that a survey become involved in the acquisition and storage of Clovis materials. The survey is intended to present interpretations of its data files or maintain records so as to suggest some type of organization that reflects culture histories. A survey provides data freely to scholars who create their interpretations based on their research philosophies and methods. If available, the survey should make casts of the points that are given survey numbers. Surveys should always photograph points using digital and film techniques.

 A survey should (must) have written policies, practices, and standards in place so that survey operation can be consistent, reliable, and maintainable. The survey is not a short-term activity; thus, plans should be made for staffing, funding, and storing files. As a precaution, surveys are often questioned as to why certain points were included and, of course, why certain points were excluded. Survey operating documents can often answer the question and influence satisfied answers for future questions. McCary Survey policies, procedures, and standards are found in Hranicky and Johnson (2004) and can be used freely in organizing a survey.

 A survey must determine its policy should a fake point get into the database. Once a survey point number is issued and published, it is very difficult to correct the mistake. The recommendation is remove the flake data and leave the point number empty in the database. An explanation is needed. However, removing the record and its number is also a possibility but is a major problem, especially for statistical studies. There is no easy answer for this problem. Survey personnel should – when in the slightest doubt do not record the point.

 Basically archaeological data, namely site-oriented data, are what constitutes contemporary archaeology. However, as with the McCary Survey, most artifact data that are collected come from surface finds, and in far too many cases, artifacts are hand-me downs that do not have specific provenances. This database and other survey databases when viewed collectively are enormous resources which are largely ungoverned, have somewhat credibility, and are difficult to find. Additionally, they tend to be state-centric and have a variety of formats. While commonplace in the business world, archaeology has not developed what is called a data warehouse (Figure 3). It is as an axiom:

A collection of integrated, subject-oriented data which was collected in order to support decisionmaking in a particular activity or enterprise. Each unit in the warehouse is tested, relevant, and replicative. Data conform to established standards and operating principles.

The McCary Survey fits this axiom nicely; it can be used for all archaeological investigations and prehistoric interpretations. What are needed here and archaeology in general, are data warehouse accesses. By this nature, archaeological research should be forced to find new ways of examining data, as Kantardzic (2003) suggests:

Thus, there is currently a paradigm shift from classical modeling and analyses based on first principles to developing models and the corresponding analyses directly from data.

This axiom is a process of collecting data from scientific observations and analyzing them, such as, comparing these data to Clovis benchmarks (attributes). The analysis from this process has always involved typical measures of central tendency, including mean, medium, mode, variance, and deviation. These factors tend to fall short of modern functional/structural analyses – they are simply ole-tyme ways of manipulating data. What remains from them are new ways to interpret data – such as forecasting methods, artificial intelligence (AI) methods, and numerous techniques.

Collecting survey data is (and will be) one of the fun processes in archaeology. It allows hands-on examination and always presents something new – the basic romance of archaeology. While Clovis points are more-or-less the same; they each tell a different story from the past. From its recording operations, the McCary Survey has built a database from which more information about Paleoindian technology can be deduced than in any other state. The following analytical techniques are possible:

 1 – Classification: creates groups of data in predetermined classes.

2 – Regression: maps data into real-time predictive variables.

3 – Clustering: identifies finite sets of data for descriptive methods.

4 – Summarizing: provides generalities for datasets.

5 – Change: measures movement (differences) in variables, attributes, or types.

6 – Deviation: measures change in variables, attributes, or types.

7 – Modeling: creates local (or broad-range) circumstances for data analysis.

8 – Boundaries: provides restrictive ranges (distribution) for data accumulation and analysis.

9 – Prediction: provides strategies for identifying unknown data.

10 – Networking: uses artificial intelligence to recognize patterns (behavior) in data.

 Other techniques are available and certainly new techniques will be invented. In one form or another, many of the techniques are used Hranicky and McCary (1995) and Hranicky and Johnson (2004) and provide suggestions for future research. By placing Paleoindian data in a national data warehouse, this universe will be available for world-wide research. While Clovis is uniquely American, its appeal and fascination reach beyond our borders.

Defining a Model

 A model is a tentative description of a system with a theory of the organization of its properties. It is a hypothetical picture of the past that is based on a theoretical orientation and field-laboratory collected data. A model can be a numeric, graphic, or semantic presentation. Further for archaeology, a model represents a proposed (hypothetical) picture of live (valid) data that was scientifically collected.

 In archaeology, modeling has become a useful tool for site predictions, settlement patterns, and general cultural presentations. It has not become a regular tool in lithic technology because of the nature of lithic investigations which usually have a high level of diversity.

 According to Clarke (1968):

            Models may be involved in two different kinds of situations. In one category it is suggested that a certain model fits the archaeological situation under investigation and the aim is therefore to test the model for adequate fit or to obtain predictive information from it. Whereas, in the second category, the analyst has an archaeological system with a large amount of observed data and wishes to build a model to simulate the archaeological black box "behaviour".

 According to Clarke (1968): Three general models or frameworks are suggested as potentially useful in developing archaeological theory:

 1 - Model for archaeological procedure - illustrating the three main spheres of archaeology as a discipline and setting out their procedure.

 2 - Model for archaeological entities - the polythetic model as opposed to the tacit monothetic model of archaeological entities.

 3 - Model for archaeological processes - archaeological entities changing with time as special kinds of dynamic systems susceptible to analysis in terms of general systems theory.

 A survey model conforms to a set of preestablished rules, such as the scientific method. Also, it is proposition based on logic, observations, constructive statements, data analyses, and offers predictions about certain data-set conditions. A model is an interpretation of a system from which we can define axioms based on observation, analysis, and study of that system. If the axioms are correct, the interpretation of the system must be correct. Changes in axioms or if axioms are found to be false (contradicted) causes a new model to be postulated. This also applies to premises; set of premises which, when taken together, are true. Model can also be used as a construct for a hypothesis. Basic models in lithic technology are:

 1 - Settlement patterns

2 - Material procurement and tool construction

3 - Behavioral activities, such as hunting, etc.

 Scientific models usually have the following organizations:

 1 - Iconic model - it is a scaled or coded isomorphic record of observations which are presented as maps, graphs, or histograms. It is basically a reconstruction of data collected from an archaeological investigation; generalizing observations. The model is an excellent approach to displaying state-wide overviews of survey data.

 2 - Analog model - it is the formulation of historic, anthropological (archaeological) data collected from empirical observations. It usually involves a time line and use of computational devices. The model is an excellent approach to define point morphologies and constructing classification standards.

 3 - Symbolic model - it is a mathematical (statistical) presentation of numeric data collected from specific inquiries; for example, sampling excavated data. Probably the most common, this model allows data computations and comparisons to other survey data.

 4 - Canonical model - logical presentations based on mathematical consequences of sampling; it proposes to approximate reality by the solution of a problem. It provides data for functional analyses. This model is ideal for testing hypothesis about database constructs which represents actual cultural situations in prehistory. This model follows a systems approach to organizing archaeological data.

 These models are ideal candidates for using Model Views which are presented later. Obviously, there are numerous ways to model paleopoint data. However, the key is database availability and “all ready” having data in an electronic form

Data Organization

 A survey is its database, which is a collection of interrelated data that is organized to meet the needs of archaeology and contribute to the Paleoindian knowledge base. It can be used by one or more persons and applied to numerous research categories and designs. Data organization always assumes that there are relationships among the data and that combining these data, information can be produced.

 For most survey organizers, the question arises – should the database be a standalone database or should it be configured with other institutional or agency databases?  As long as the survey database is shareable, then it should be a standalone database which operates on a dedicated computer (or server).

 A survey’s data is stored in a Database Management System (DBMS), such as Excel, Access, SQL, or Oracle. By complying to industry standards, a DBMS database can be moved to any new platform. Basically, a DBMS has:

 The DBMS is a standard operating system in archaeology and its mechanics are not discussed (see Larson 1995 and Turban and Aronson 2001 for overviews). With today’s computer system, storage space is not a concern. However, numerous database backups must be maintained. Always run virus-checking software on the database’s PC.

 A DBMS is typically coupled with modeling software for statistical, mathematical, morphological object comparisons, extracting historical data, maintaining point locations, and numerous task-related computer operations. There are three typical DBMS structures: relational, hierarchical, and network. McFadden et al. (1999) offers an overview of DBMS design and operation.

 Without going into the “nuts and bolts,” a data warehouse system is needed for American archaeology. Far too much data and reports are stored in state-centric libraries which are impossible to locate and access. Thus, in many cases, archaeological wheel is re-invented time and again. At least, there are efforts to nationalize fluted point data (see Hranicky and Johnson 2004 for a discussion). For the federal government and large-corporated business world, this process is evolving into Enterprise Architectures (EAs). Again, this topic is too complex for this publication. However, the basics are:

 A topic that has received little attention in archaeological databases is virtual reality modeling (VRM). With the use of webpages, VRM allows displays of Clovis point in a form that is only available to the giants of networking. VRM is easily a decade away in archaeology. VRM can also be called object-oriented simulation.

 Related to VRM, simulation modeling allows the database to be used for conducting what-if experiments and analyses. Like VRM, simulation is a descriptive process that has no optimal solution. Once values, metrics, data, events, processes are assembled, the best among several alternatives can be selected. The controlling factor in creating VRMs and simulations is complexity, such as too many variables, formulations are too large, or simply a model cannot be constructed with any degree of success.

 In the past, factor analysis (as in: Blalock 1972), and currently, multivariate statistics (as in Tabachnick and Fidell 2001), and discriminate analysis (as in Klecka 1980) were a common method for analyzing artifact data, but their adherence to mathematical relationships did not adequately explain changes. Relationships among variables, traits, and attributes were restricted to a pre-determined hierarchy that while mechanistic, did not identify a cause-effect relationship among point factors, namely material, fluting, and dimensional variables. Overall, the total survey point population is not presented as a change process. Thus, a researcher simply could not measure change processes, such as adaptation, material changes, or regional dispersions of style. The Survey has, and will always have, chronology problems with its data. However, if analyses are modeled to look for cause-effect factors, a structural model of Virginia points can be built up using existing data. The Survey comes the closest to baselining Clovis points than any other large-scale Clovis technology investigations.

Model Organization

 Figure 4 provides the high-level architectural framework for this model which is broken down into views. Each view cell (called a node) in the model has a title, and its affected inputs, outputs, controls, and constraints. Occasionally, a node contains an output constraint, such as Best Practices, as shown in the example. This framework shows the inputs, controls, constraints, and outputs as they apply to the McCary Survey. They may vary in other surveys, but they generally offer the philosophy of a survey operation. These factors are further defined, illustrated, and discussed in the following paragraphs.

Figure 4 - Basic Survey Model Showing Inputs, Outputs, Controls, and Constraints

The model unit nodes, which reflect specific activities or processes in a survey, are:

N0 – Survey Model

N1 – Logic Flow of the Survey

N2 – Dataflow in a Survey

N3 – Artifact Flow in a Survey

N4 – Operational Flow in a Survey

N5 – Analytical Process in a Survey

N6 – Survey Process Control in a Survey.

Figure 5 shows the relationships of these nodes, and Table 1 provides the basic operationalization for each node. All nodes are controlled by written, in place, procedures, policies, and standards for the survey. All these documents can be grouped into a single document, such as Survey Operating Principles. But none-the-less, they should be written and open to the public access and inspection. The survey is a public realm operation for the advancement of science. The procedures are provided in Hranicky and Johnson (2004) and at: www.mccary-survey.com

Figure 5 – Survey Model showing All Nodes

General Survey Operations

Using this model, a survey can operate as an independent program whose basic goals are to record (and validate) all new/old found Clovis points found in its geographic area of responsibility. Generally, a survey has a director, database administrator, and a publication specialist, which is usually rolled up into one person. The point is always the input and initializes the recording process. Naturally, some form of data storage is required. The output is always the publication and allowing access to the survey’s database. With the advent of Webpages, record access is easier and opens the door for scholarly access. The general public also has the opportunity to browse the survey’s records.

Recording points is a one-on-one operation, namely recording individual point traits. Whereas, a survey is a collection of traits and contributes them to attributes of a class or type, in this case Clovis. Traits are always variables, but still conform to a parsimonious way (fewest dimensional variations) of a type. A Clovis point has landmarks which make it a member of a type. Landmarks are based on benchmarks in a collective database. Recording point data is a empirical process based on (controlled by) the point’s properties. These point properties have variation, but are limited to the scope of “Whay would be called Clovis.”

The initializing event for the survey is a request to enter a point in the survey. A survey data collection form is used. All data entries match fields in the database. This form can be competed by hand or data can be entered directly into a PC which is used to transfer the record to the database. Continuous review ensures that data are not lost. Also, a technical review is performed, which may reject the point early in the recording process. The survey must set policies as to what level and kind of missing data are acceptable. Tentative point number assignment is not recommended; the point is either acceptable with complete data or it is not and must be recorded at another time.

Inputs and Outputs

The basic model operates on two physical operations, which are:

      ·         Inputs

·         Outputs.

 Inputs are the initializing operation on which the model processes. Input can be data transfer from written documents or by electronic inputs from scanners or other digital equipment.

 Outputs are the finalizing operation on which the model generates from its processing. Output can be in the form of paper reports or digital files.

Constraints and Controls

This model provides the means to classify and coordinate (incorporate) factors which affect the survey. While most are not officially part of a survey, they do “regulate” the survey’s operation so that its credibility remains unquestioned.They are grouped as:

·         Constraints

·         Controls.

 Constraints on the survey are state legal obligations and ethical practices for controlling and accessing the database. Constraints are basically technological, but user information availability, as mentioned, is a factor. They are factors that are usually outside of the survey’s operation. The model contains numerous constraints in the acquisition of Clovis point data that must be incorporated in the survey’s processes. As especially noted, the survey should maintain written procedures, policies, and practices which include point verification and validation methods (Figure 16).

Figure 16 – The Clovis Recording Process

Controls, like constraints, affect the survey’s operation. The controls are the data validation methods and general processing methods. There are restrictions that are identified and incorporated into the survey’s written procedures, practices, policies, and standards. They are based on or taken from the professional archaeological community, but also conform factors such as Native American concern and rights.

Model Regulations

Paperwork, now computerwork, is a way of the so-called modern world. A successful survey is one that has written and proven regulations for its operation. They provide consistency and continuous credibility for the survey. These regulations are used to cite reason, ethics, and generally operations of the survey for the public and the scientific community. Table 2 provides these documents which are available in Hranicky and Johnson (2004). A guide for terminology and concepts for these documents is available in Hranicky (2004).

These documents are:

► Processes – a set of operational methods for studying paleopoints.

► Standards – a set of terms, concepts, and measurements for studying paleopoints

► Practices – a set of activities on studying paleopoints; includes ethics

► Procedures – a set of physical (scientific) ways recording paleopoints.

This model presents general practices for operation (Figure 7). The survey is basically:

·         Records

·         A database

·         And, publications.

Figure 7 – Basic Survey Operations

For practical as well as scientific reasons, there should be only one survey in a state. And, the survey should have a review process for accepting and numbering points. For example, North Carolina has two surveys; a duplication of effort? Pennsylvania has an open survey where anyone can contribute a point for inclusion in the survey; credibility of the survey’s database? And, the survey needs sanctioning from a state’s archaeological community; survey legitimacy recognition? A basic requirement for the survey: the owner of a submitted point must allow its publication.

Survey Host

The survey should remain independent from state/federal agencies because in possible conflicts of interest that may arise during the survey’s operation. Academic and state archaeological societies make ideal candidates for hosting or ownership of the survey. While all survey data should be part of the public domain, the survey itself must be protected, such as intellectual property rights, copyrights for artwork, and general operations. Basically, the survey should be incorporated in the state where it resides. By issuing corporate shares, the survey can easily have host-to-host and director-to-transfers – simply be vote. The corporation should be nonprofit, and all labor should be voluntary.

Model Overview

Regardless of its methodologies, the success of a survey depends on its contributors who come forward with their private finds or archeologically-sourced finds. Without a caution, a survey depends on the artifacts collectors and cooperation from professional archaeologists excavating Paleoindian sites. Both are the primary sources for point submissions. This survey model shows the factors and processes that comprise a survey’s operation. Survey constraints and controls are identified. All of these elements are discussed throughout the publication. Figure 8 provides a survey structure for physical operations; all of which are needed for a successful survey.

Figure 8 - Survey Model Overview (N0 Node)

Point recording is the primary focus of a survey and is essentially a short-term activity. But in terms of the total survey operation, recordation produces long-term point record maintenance; all of which leads to publications and additions to the archaeological database. Access to the survey database is generally free; however, due to hackers and other misfits on the Internet, access to the database should be limited to recognized scholars and sincere amateur archaeologists. Always backup survey databases with several copies with have been scanned with a virus checking software. Holographic methods are shown in the model. It will be a method of scanning a point to obtain its metrics, morphology, and lithic composition – a future of point recording.

Mechanics of the Model

This model is a combination of a data flow and survey process models that offer a total operation of a fluted point survey. It is based on the McCary Fluted Point Survey^® of Virginia which the author operates. This survey has over 50 years of contribution to the study of Virginia Paleoindian prehistory and has delivered 1000+ points to the archaeological world. McCary (1951) launched both the Williamson Paleoindian site and his survey in his classic workshop publication in American Antiquity. He started the Survey which was later named after him; and it is the oldest survey in the U.S.

Figure 9 – Logic Flow of a Survey Operation (N1 Node)

Logic Flow

The basic operation of a survey is a process of collecting the biography of a point, including its owner. This is often an oral history of the point and probably does not offer a specific provenance. Next is collecting the morphological properties of the point. All of which are entered into a survey database. Figure 9 shows the basics of a survey operation.

Data Flow

Data flow is a process that is based on the survey’s written procedures. There must be a process from collecting data to and maintaining the survey’s database. Figure 10 shows a typical process. For best practices, all survey points and data should be reviewed by a survey committee.

Data flow is the movement of initial data to some form of a collective output – or, an output that produces information. The final location for data is, of course, the survey database. A basic component of dataflow is to determine and ensure data validity. Data validation is determined by the survey’s policies and procedures – and compliance to sound archaeological practices and data collection methods.

Figure 10 – Data Flow in a Survey (N2 Node)

Survey as a Process

The survey offers a single-source investigation of Paleoindian points. It offers a coordinated effort within the archaeological community. Most members of this community are constantly searching for point owners and encouraging participation in recording paleopoints. The survey can be viewed as a credible activity for “chasing down” paleopoints and getting them recorded. This process often leads to the public informing the archaeological community of new sites.

Model Operations

The real justification for the survey is the point contributes to archaeology’s knowledge base. If for no other reason, the director of a survey should be a professional prehistoric archaeologist. This person would have the training and experience that is needed to support data acquisition as a public policy and avoid contributing to the relic underworld. Professional analytical skills and methods are a basic requirement; this is not to say that advanced amateurs cannot develop these skills and learn professional practices. Also, it is true that to get to and record valid Clovis points, the survey staff must participate and probably be an accepted member of the antiquity-oriented world of collectors.

Figure 11 shows the basic movement of most American artifacts including Clovis points. A survey becomes involved in the flow if the point is submitted for recording. If not, the survey has a second chance if the point eventually becomes the property of a public agency, institution, or museum. A problem for most surveys is a Native point found in a neighboring state which somehow transforms its find provenance to the host-survey’s provenance. Obviously, points found on or near another state’s boundaries might be justified as an inclusion in the survey. These are called and recorded as border points. This provenance-moving is especially a problem for surveys that do not have counter-partners in neighboring states.

Figure 11 – Artifact Flow (Modern Circumstances of the Clovis Point) (N3 Node)

At this place in this paper, and at horror to some archaeologists, all Clovis points have two types of value: 1) monetary and 2) knowledge. A survey must deal with both values. Anytime a Clovis point is added to a survey, its monetary value is greatly increased. And, the survey authenticates the artifact, all of which invites the relic world to participate in survey requests. Surveys should avoid getting into point appraisals and outright purchases, but the nature of the relic (nonarchaeological) world, namely museums and state agencies, sometimes requires expert advice and appraisals for which the survey is an ideal candidate. This is a consequence that is necessary for the public domain of Native American materials; not all will agree.

This value factor is really difficult to separate the rocks from the scientists. Clovis points are tools that served life times in the past; they were discarded when expended by Early Americans. Today, they are samples of prehistoric life times; they are only rocks that contain cultural information. They are not rocks having dollar signs attached to them. But for most, they cannot make the distinction between historic and monetary values. A few-to-many archaeologists see first the monetary values in their Paleoindian acquisitions, then settle down for serious … whatevers. There is no dollar value on knowledge; and more importantly, all knowledge must be part of the public domain. This is truly what separates collectors (and some amateurs) from professional archaeologists. Then again, bring up Clovis points at any meeting.

The survey process can be a disaster for a state’s inventory of Clovis points and records, as its director usually plays a role in point movement and usually influences the placement of points. Most Clovis points are single, occasional finds by people who do not have a direct role in the archaeology of a state. They come to or are referred to the survey director to assist them with finding out what they have, and most important to them, what is the value of the point. Here reference is made to the point’s historic value, but in some cases, the director has the persuasiveness to acquire the point. Over the years, the director can build a massive Clovis collection. As a recent case in this argument, the director dies leaving the collection to heirs who sell it, often for big bucks. This leaves a void in state collections that can never be justified by the survey. A survey has a moral and ethical requirement to perform recordation in a scientific manner and without personal interest or accessions. Personal collecting has no place in the operation of a survey – never.

The survey’s world is controlled by: 1) the points that are found, such as on public or private lands, 2) Native American rights, 3) legal exchanges of artifacts, 4) deeds of gift or bill of sales, and 5) numerous activities outside archaeology. The major control is the supply and availability of points, and of course market values. As with any high-value item, security is a major concern. For survey, point movement is best accomplished by hand-to-hand exchanges or, minimally, with insured public carriers. A survey should provide cautions and security practices for point owners. In some cases, owners are unaware of the security problem.

The analytical process is difficult to present because of its lengthy methodologies and procedures used to analyze points. The principal concerns are to study the point’s manufacture, lithic source, environmental situation, and provenance (Figure 12). Most surveys divide point recording into field and laboratory sources. Field collection is recording the point at the owner’s premises; whereas, laboratory recording is, obviously, the preferred method. While in the laboratory, the point can undergo nondestructive testing, such as patination analysis, refractive indexing, specific gravity analysis, or lithic identification; testing is generally an observational approach for recording point properties. Observations are based on experimental archaeology data and information. Comparative data learned for Native points also bring into play observations that are needed to analyze a point.

Figure 12 – Analytical Process (All Components of the Technical View) N5 Node)

The process flow is a system orientation that examines the entire recording process (Figure 13). It includes point origins (modern discovery), finder credibility, mechanics of recording the point, entering data, processing data, concern over the point’s home, and finally, publication. Each of these categories could be discussed separately, but these would vary from survey to survey, and there is no generic definition and description for them. Controls are getting the point, measuring it, recording its properties, and ensuring that it is properly curated. The point’s publication is a given for any survey. Constraints are found in learning the point’s modern ancestry, such as were it found on public land, does the owner have title to it, and then database restrictions, such as size, images, etc. This is the most volatile aspect in a survey operation. Point credibility, ownership, provenance, and attributes are all basic complicating considerations – there are no easy means to approach these factors.