16. August 2018 · Comments Off on A Crowd Sourced User Survey for the Digital Archive of Huhugam Archaeology (DAHA) · Categories: Uncategorized · Tags: , , , ,

By Keith Kintigh and Mary Whelan

In October, 2017 the DAHA team designed a survey to assess the relevant information-related needs of the Digital Archive of Huhugam Archaeology’s key user communities:  archaeologists and others working in cultural heritage management who are concerned with Huhugam archaeology. We wanted to distribute the survey to as many Huhugam archaeologists as possible so we sought the help of the 177 members of the Arizona Archaeological Council (AAC). This is the professional organization of archaeologists working in Arizona. Although most AAC members are not Huhugam archaeology specialists, we thought this group contained much of the audience we were targeting.  We also contacted an additional 28 Huhugam archaeologists not affiliated with AAC. Most individuals received an initial email request to participate (containing the link to the survey) and at least one email reminder.

Between 18 October and 30 November 2017, we received 49 anonymous responses. We were encouraged by the 24% response rate, especially given that the distribution included a substantial number of individuals for whom the survey was not relevant.  The survey was designed to elicit a reasonable number of responses from the community of Huhugam archaeologists and it was successful in that regard; it was not designed to obtain a statistically representative sample.

We published the full DAHA User Survey Report in the “Reports in Digital Archaeology Publication Series.”  Reports in Digital Archaeology is an online publication series devoted to issues regarding research and practice in digital archiving of archaeological materials and archaeologically related data. Below are some of the survey highlights.

Analysis of the Results

Because the goal of the survey was to provide feedback from Huhugam archaeologists for use in developing the DAHA archive, the questions were focused primarily on two areas:  what research questions are of most interest to the user communities, and what IT tools and technological support would enhance and expand the user experience with the DAHA digital library in tDAR.

The results confirmed our beliefs that there is a perceived need for DAHA and that the archive will be heavily used by Huhugam archaeologists. The survey’s responses on how archaeologists use reports and what features they want to see in DAHA indicate that we should focus development on features that facilitate efficient discovery of the desired documents and that allow users to find or extract specific types of information they are looking for within reports.  The results are helpful in both prioritizing the kinds of resources to add to DAHA, and for the development of natural language processing (NLP) tools.

Table 1. What do you see as the three most important questions in Huhugam Archaeology?

Count Subject
21 Understanding the End of Classic/Huhugam Collapse
16 Huhugam Connections to Descendent Communities
14 Huhugam Organization
11 Preclassic/Classic Transition
10 Internal Hohokam Interaction
9 Adaptation to Environment
7 Identity/Ethnicity/Ideology
7 Modeling/Refinement of Population
6 Methods Issues
5 Water Management/Irrigation/River Flow
5 Relevance to today
5 Subsistence & Production
4 Chronology Refinement
4 Early Agricultural to Pioneer Period
4 External Interaction – Including with Mesoamerica & Pueblo areas
3 Nature of Classic Period
3 Huhugam Origins
3 Resilience of Huhugam

Several survey questions provided valuable information concerning the research topics of most interest to the user communities (Table 1).  Those results will likely be of interest to many Hohokam archaeologists, and will help structure the organization of the final DAHA archive, as well as provide guidelines for decisions about the most important documents to include in the archive.

Table 2.  What features would help you in using grey literature reports to advance knowledge of Huhugam society?

Count Feature
13 Keyword Search/Index to reports [already implemented]
12 Full Text Search [already implemented]
4 Good Abstracts/Summaries of Scope & Results
3 Master (Annotated) Bibliography of Huhugam Reports
3 Spatial Search [already implemented]
2 Extract Tables as Spreadsheets
2 Organization Search Output to Facilitate Selection
2 Topic Search
1 List of Analysis Types Reported
1 Indication if Full Text is Available in Search Result
1 Indication if Report is Peer Reviewed or Agency Approved
1 Abstract preview before download [already implemented]
1 Quick Response Time
1 Partial Download
1 Connect Tabulated Data with Associated Text
1 Integrate with AZSite
1 Voice Search

A later question (Table 2) was most useful in directing the development of natural language processing tools and adding or enhancing tDAR search and access features. The two most common requests shown in Table 2, keyword and full-text search, are core features built into tDAR from its beginning.  The report abstracts are generally extracted and made available on the metadata pages as the document summary.  Like full text and keyword search, spatial search is a core feature of tDAR available from the beginning.  Being able to extract document tables as spreadsheets is a challenging request that we are considering.

Question by question and full text survey results are available in tDAR:

23. July 2018 · Comments Off on If you could apply Text Mining to your archaeological research, what would it look like? · Categories: Uncategorized · Tags: , , , ,

By Rachel Fernandez and Mary Whelan

Computer automated part-of-speech analysis of an English sentence.

If you Google “archaeology” and “text mining” you get a pretty small number of results. While both the Archaeology Data Service (ADS) in the UK and Open Context, the American open data and publication service, have worked on projects that apply text mining techniques to archaeological reports, it is probably safe to say that most archaeologists are unfamiliar with how text mining or data science can contribute to archaeological research. This isn’t surprising since most of us specialize in the analysis of some material culture product, not the analysis of written reports. But as McManamon et al. (2017) have pointed out, the volume of new archaeological articles, books, compliance reports and other documents is so large, and grows so quickly, that no one person can possibly read it all. Text mining offers automated approaches that help with this “data deluge.”

Illustration of the stages from binary computer code, to ASCII code, to an English language sentence.

This past April, the Digital Archive of Huhugam Archaeology (DAHA) team hosted an NEH-funded research workshop focused on Archaeology and Text Mining. Led by DAHA investigators Michael Simeone, Keith Kintigh and Adam Brin, we invited 9 panel experts including archaeologists, Native American scholars, and Digital Humanities researchers, to meet with the DAHA team for a day of discussion. We asked the panelists first to simply talk about how they use digital texts in their work, regardless of their discipline.

Working in small groups, the participants discussed the epistemology of research for their respective fields and quickly turned the conversation to the how text mining digital documents could benefit each field. Ideas such as pulling artifact counts and site descriptions from standardized CRM reports to demographic studies were mentioned. Professor David Abbott, a Huhugam Researcher in ASU’s School of Human Evolution and Social Change, brought up the potential for text mining to advance synthetic research.

Next, we wanted to hear their ideas about how we might make the DAHA digital text corpus more useful to a broad and diverse audience with text mining. Joshua MacFadyen, Assistant Professor of Environmental Humanities in the School of Historical, Philosophical, and Religious Studies, and the School of Sustainability at ASU, brought up this important question on user experience and how we are able to record and trace this impact of these tools on a diverse user group. In addition, David Martinez, member of the Gila River Indian Community and Associate Professor of American Indian Studies at ASU, hopes that this technology can potentially bridge the gap between community users and researchers and allow the users to interpret data in ways that interest these communities. Overall, text processing was thought to be most useful in aiding filtering and analysis of data, rather than providing direct insights.

Finally, we asked all the participants to reflect on what we accomplished and identify useful directions the DAHA team can take in using Text Mining tools and technology. Some of the possible features to come out from DAHA include: automated tools for the extraction of specific text sections, such as tables, references, or headings, use of ontologies to make documents more efficient, topic related searches, and the ability to gather set of reports and have the data linked to its various sources.

Illustration of the steps in Named Entity Recognition

The DAHA grant proposal focused specifically on Natural Language Processing applications for text analysis. But during the workshop, a number of more general Text Mining approaches were mentioned, including:

  • Corpus Statistics (Word frequencies across corpus)
  • Concordance
  • N-Grams
  • Advanced queries across multiple texts
  • Named Entity Recognition
  • Topic Modeling
  • Sentiment Analysis
  • Network Analysis
  • Text visualization options
  • GeoParsing (geographic information extraction)

If you are interested in applying text mining tools to a document corpus of importance to you, there are several good, open source toolkits that support one or more approaches:

  1. AntConc (http://www.laurenceanthony.net/software/antconc/ ) is an easy-to-use set of tools for analyzing any type of text corpus. AntConc provides tools to calculate word frequency, concordance, N-Grams, and corpus statistics.
  2. ConText (http://context.lis.illinois.edu/ ) is a package of tools that allow you to do topic modeling, sentiment analysis, parts-of-speech analysis, and visualization of a text corpus.
  3. MALLET (http://mallet.cs.umass.edu/index.php ) MAchine Learning for LanguagE Toolkit is a very popular topic modeling tool.
  4. Ora-Lite (http://www.casos.cs.cmu.edu/projects/ora/software.php ) is a software package that helps you identify and visualize networks (e.g., people who communicated with each other or places that are linked) in text data.
  5. Voyant (https://voyant-tools.org/docs/#!/guide/start ) is a free online service that supports a number of corpus analysis tools, including visualization.
    1 McManamon, Francis P., Keith W. Kintigh, Leigh Anne Ellison, and Adam Brin. 2017. “The Digital Archaeological Record (tDAR): An Archive – for 21st Century Digital Archaeology Curation” Advances in Archaeological Practice 5(3), pp. 238–249.
04. December 2017 · Comments Off on Natural Language Processing and the Digital Archive of Huhugam Archaeology – Part I · Categories: Uncategorized · Tags: , , , ,

By Keith Kintigh, Adam Brin, Michael Simeone and Mary Whelan

When people talk about the problems, and potential, of Big Data they are often referring to research or business output files that are gigantic. But an equally vexing Big Data problem involves wrangling thousands of small files, like PDFs. Addressing this problem is a key component of the NEH funded DAHA Project because we anticipate that the DAHA library will contain over 1,600 grey-literature archaeological reports, on the order of 400,000 pages of information-rich text. Our ultimate goal is not to sequester these documents in the archive, but to stimulate and enable new uses that advance scholarship. For efficient ways to search and analyze that many documents at once we turn to computer science and Digital Humanities, using Natural Language Processing (NLP) tools developed and applied in those disciplines.

Natural Language Processing tool kits that we compared for the DAHA project

Natural Language Processing tool kits that we compared for the DAHA project

Of course you can do a simple word search in the DAHA archive in tDAR now and get useful results. But word searches have limitations (spurious results, spelling variations missed, etc.) and ultimately what we would like to do is search the entire corpus using a complex query like “Find all the reports that describe 12th century excavated pit structures from New Mexico or Arizona that have a southern recess and are associated with above-ground pueblos with 10 or more rooms.” We aren’t there yet, but NLP approaches and tools are moving us closer to that goal.

For the DAHA project, we are focusing on the NLP branch known as Named Entity Recognition (NER). Working with this framework in tDAR will allow us to automatically extract standard who, what, where, and when references from each DAHA document, thus improving metadata records which will greatly improve a user’s query and discovery experience.

Preliminary workflow for DAHA Named Entity Extraction tasks

Preliminary workflow for DAHA Named Entity Extraction tasks

So far we have started to figure out a workflow, identified a test set of DAHA documents and asked a human to tag words and phrases in one document.  Our entity tags include Ceramic Type, Culture, Location, Person, Institution, Archaeological Site Name, Site Number and Date.  Next we experimented with three NER tool kits (Stanford’s NLP Toolkit, Apache’s Open NLP, and the University of Sheffield’s GATE) to see which one(s) worked best on our corpus.  We’ll describe our NLP comparison and results in detail in the “Natural Language Processing and the Digital Archive of Huhugam Archaeology – Part II” blog post.

Kintigh, Keith
2015. “Extracting Information from Archaeological Texts.” Open Archaeology 1: 96–101.
DOI: https://doi.org/10.1515/opar-2015-0004

15. November 2017 · Comments Off on DAHA Regional Subareas Map · Categories: Uncategorized

by David Abbott, Keith Kintigh, and Mary Whelan

The DAHA Project is underway.  Funded by the National Endowment for the Humanities, the goal of the Digital Archive of Huhugam Archaeology (DAHA) is to create a comprehensive library of archaeological reports focused on the Huhugam (Hohokam). As we collect new documents from various people and organizations we would ideally like to automatically add as much metadata to the digital files as possible. One widget already in place in tDAR (the digital repository that holds the DAHA collection) is a map feature that lets contributors click on the map to identify the location the document refers to.  One click on the map automatically generates geographic key words such as state or province name, country name, and other landmarks where the click intersects.  For DAHA purposes, we want to add Huhugam geographic subareas to the tDAR map to generate additional key words (subarea names) for this project. This additional metadata enhances and improves searching.

Huhugam sites are found throughout central and southern Arizona, most located in the river valleys that helped make agriculture sustainable in an otherwise challenging desert environment. Archaeologists conceptualize Huhugam “culture” as a set of geographically separate but interacting communities spread across a large territory and integrated with one another through the exchange of goods and services (Abbott et al. 2007). The regional extent of Huhugam culture is impressive, over 80,000 km2  (31,000 mi2) at its maximum.

Map of central and southern Arizona showing archaeological site containing ballcourts across the Huhugam region

Archaeological sites with ballcourts in the Huhugam region

Regional integration was both facilitated by, and is illustrated through, the construction and use of ballcourts – large, oval excavated features that were likely used for a ritual ballgame inspired by similar Mesoamerican practices to the south. Periodic marketplaces, timed to coincide with the ballgames, may have been instrumental for moving high volumes of goods throughout the Hohokam territory. Mapping the extent of sites containing ballcourts is one way to delimit the Huhugam regional system boundaries (map above).

Scholars working in the Huhugam region often refer to smaller subareas named for location (e.g., Phoenix Basin, Tucson Basin) or watershed (e.g., Lower Verde River, Santa Cruz River) (see Craig 2001, Wilcox and Sternberg 1983, Abbott et al. 2007). For the DAHA project we need to delineate these subareas so that we can create a map that will support the automatic metadata creation in tDAR.

Map of central and southern Arizona showing USGS Hydrologic Unit Code 12 areas that correspond with Huhugam geographic subareas

USGS drainage basins (HUC 12) as templates for Huhugam subareas

We are aware that there is no consensus on the exact location of the edges of each subarea, and intend our boundaries to be “fuzzy” – conveying a general sense of place only.  To help in delineating the subarea boundaries we looked at the Hydrologic Units mapped at various scales by the USGS (HUC = Hydrologic Unit Code).  We merged adjacent HUC 12 drainage basins, smoothed the edges, and used these to outline each of the sub-areas (map above).

The Huhugam regional system also includes large tracts that are not in a major river basin, and are not part of a named subarea, but are nevertheless important areas that were traversed and utilized in a variety of ways.  We’ve designated these as Interstitial Areas and together with the geographic subareas, they provide a geographic framework for the DAHA project (map below).

Map of central and southern Arizona showing bounded geographic subareas and interstitial areas for the Huhugam region

Map of the Huhugam geographic subareas and Interstitial areas

David R. Abbott, Alexa M. Smith, and Emiliano Gallaga
2007. Ballcourts and Ceramics: The Case for Hohokam Marketplaces in the Arizona Desert. American Antiquity, 72(3), 2007, pp. 461-484.

Craig, Douglas B. (ed.)
2001. The Grewe Archaeological Research Project, vol. 1: Project Background and Feature Descriptions. Anthropological Papers No. 99-1, Northland Research, Inc. Tempe, AZ.

Wilcox, David R. and Charles Sternberg
1983. Hohokam Ballcourts and their Interpretation.  Cultural Resource Management Division, Arizona State Museum, University of Arizona.  Tucson, AZ.