Matching Items (3)
Description
This study evaluates five different hypotheses potentially accounting for the prehistoric movement of vesicular basalt during the Hohokam occupation of the Salt-Gila Basin (ca. A.D. 700-1450): 1) direct procurement; 2) direct exchange; 3) down-the-line exchange; 4) market exchange; and 5) elite-controlled exchange. The plausibility of each hypothesis is assessed by examining the relative frequency of different vesicular basalt source types at sites as related to the geographic distance from their source; intra-site variance in vesicular basalt source type diversity; inter-site variance in vesicular basalt source type diversity; and temporal specificity and continuity in source preference. The study sample is comprised of 484 vesicular basalt artifacts recovered from nine Hohokam sites: Casa Grande, Gila Crossing, the Hospital Site, La Plaza, Las Colinas, Los Hornos, Lower Santan, Pueblo Grande, and Upper Santan. Geographic provenance data for artifacts are generated by comparing their chemical composition to a geochemical reference database composed of more than 700 vesicular basalt raw material samples from 17 different source areas in the Salt-Gila Basin. Geochemical data for both artifact and raw material samples were collected using a portable X-ray fluorescence spectrometer and a newly developed sampling procedure that provides an efficient, reliable, and nondestructive means of analysis.
The results of the hypothesis testing found that direct procurement is a possible material provisioning practice for perhaps only a small number of households in the Salt-Gila Basin; specifically those located less than 10 km from a vesicular basalt outcrop. Direct exchange is also an unlikely explanation, though it cannot be rejected outright. The other exchange hypotheses, down-the-line, market, and elite-controlled exchange, as defined in this study, are all rejected as possible explanations. From these results, a new model of Hohokam vesicular basalt provisioning practices is developed for future testing. This model posits that vesicular basalt groundstone tools were produced by specialists in a handful of locations during both the Preclassic and Classic periods, and that finished tools were acquired through workshop procurement or local distributers. The implications of these findings for understanding the organization of Hohokam domestic and political economies are also discussed.
The results of the hypothesis testing found that direct procurement is a possible material provisioning practice for perhaps only a small number of households in the Salt-Gila Basin; specifically those located less than 10 km from a vesicular basalt outcrop. Direct exchange is also an unlikely explanation, though it cannot be rejected outright. The other exchange hypotheses, down-the-line, market, and elite-controlled exchange, as defined in this study, are all rejected as possible explanations. From these results, a new model of Hohokam vesicular basalt provisioning practices is developed for future testing. This model posits that vesicular basalt groundstone tools were produced by specialists in a handful of locations during both the Preclassic and Classic periods, and that finished tools were acquired through workshop procurement or local distributers. The implications of these findings for understanding the organization of Hohokam domestic and political economies are also discussed.
ContributorsFertelmes, Craig M (Author) / Abbott, David R. (Thesis advisor) / Simon, Arleyn W (Thesis advisor) / Darling, J Andrew (Committee member) / Arizona State University (Publisher)
Created2014
Description
A statement appearing in social media provides a very significant challenge for determining the provenance of the statement. Provenance describes the origin, custody, and ownership of something. Most statements appearing in social media are not published with corresponding provenance data. However, the same characteristics that make the social media environment challenging, including the massive amounts of data available, large numbers of users, and a highly dynamic environment, provide unique and untapped opportunities for solving the provenance problem for social media. Current approaches for tracking provenance data do not scale for online social media and consequently there is a gap in provenance methodologies and technologies providing exciting research opportunities. The guiding vision is the use of social media information itself to realize a useful amount of provenance data for information in social media. This departs from traditional approaches for data provenance which rely on a central store of provenance information. The contemporary online social media environment is an enormous and constantly updated "central store" that can be mined for provenance information that is not readily made available to the average social media user. This research introduces an approach and builds a foundation aimed at realizing a provenance data capability for social media users that is not accessible today.
ContributorsBarbier, Geoffrey P (Author) / Liu, Huan (Thesis advisor) / Bell, Herbert (Committee member) / Li, Baoxin (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
When scientific software is written to specify processes, it takes the form of a workflow, and is often written in an ad-hoc manner in a dynamic programming language. There is a proliferation of legacy workflows implemented by non-expert programmers due to the accessibility of dynamic languages. Unfortunately, ad-hoc workflows lack a structured description as provided by specialized management systems, making ad-hoc workflow maintenance and reuse difficult, and motivating the need for analysis methods. The analysis of ad-hoc workflows using compiler techniques does not address dynamic languages - a program has so few constrains that its behavior cannot be predicted. In contrast, workflow provenance tracking has had success using run-time techniques to record data. The aim of this work is to develop a new analysis method for extracting workflow structure at run-time, thus avoiding issues with dynamics.
The method captures the dataflow of an ad-hoc workflow through its execution and abstracts it with a process for simplifying repetition. An instrumentation system first processes the workflow to produce an instrumented version, capable of logging events, which is then executed on an input to produce a trace. The trace undergoes dataflow construction to produce a provenance graph. The dataflow is examined for equivalent regions, which are collected into a single unit. The workflow is thus characterized in terms of its treatment of an input. Unlike other methods, a run-time approach characterizes the workflow's actual behavior; including elements which static analysis cannot predict (for example, code dynamically evaluated based on input parameters). This also enables the characterization of dataflow through external tools.
The contributions of this work are: a run-time method for recording a provenance graph from an ad-hoc Python workflow, and a method to analyze the structure of a workflow from provenance. Methods are implemented in Python and are demonstrated on real world Python workflows. These contributions enable users to derive graph structure from workflows. Empowered by a graphical view, users can better understand a legacy workflow. This makes the wealth of legacy ad-hoc workflows accessible, enabling workflow reuse instead of investing time and resources into creating a workflow.
The method captures the dataflow of an ad-hoc workflow through its execution and abstracts it with a process for simplifying repetition. An instrumentation system first processes the workflow to produce an instrumented version, capable of logging events, which is then executed on an input to produce a trace. The trace undergoes dataflow construction to produce a provenance graph. The dataflow is examined for equivalent regions, which are collected into a single unit. The workflow is thus characterized in terms of its treatment of an input. Unlike other methods, a run-time approach characterizes the workflow's actual behavior; including elements which static analysis cannot predict (for example, code dynamically evaluated based on input parameters). This also enables the characterization of dataflow through external tools.
The contributions of this work are: a run-time method for recording a provenance graph from an ad-hoc Python workflow, and a method to analyze the structure of a workflow from provenance. Methods are implemented in Python and are demonstrated on real world Python workflows. These contributions enable users to derive graph structure from workflows. Empowered by a graphical view, users can better understand a legacy workflow. This makes the wealth of legacy ad-hoc workflows accessible, enabling workflow reuse instead of investing time and resources into creating a workflow.
ContributorsAcűna, Ruben (Author) / Bazzi, Rida (Thesis advisor) / Lacroix, Zoé (Thesis advisor) / Candan, Kasim (Committee member) / Arizona State University (Publisher)
Created2015