About The Khipu Field Guide

The Khipu Field Guide Affiliates

This site started in early 2020 as a way of escaping the tedium of Covid-19. In late 2020, khipu scholar and historian Manuel Medrano joined me while he was finishing his first stint at Harvard. Then Kylie Quave, another trained khipu scholar, joined our efforts and brought in the Andean scholar Di Hu. This year we became 5!, with the wonderful addition of Australian data scientist Karen Thompson.

I am indebted to these four scholars who have aided in the creation of this Field Guide and whom I now call teammates:

  • Manuel Medrano who has helped guide me along this journey, and whom I now call “Khumpay”.
    Kusami kanki Manny. Añay.
  • Kylie Quave who has provided help, feedback, khipus!!, and connections when needed most. Añaypas.
  • Di Hu who has asked the right questions, at the right time, and taught me so much about Andean history. Añaypas.
  • Karen Thompson who has diligently and brilliantly reworked much of the Ascher khipu data, and the Hugo Peyrera data to bring the original Harvard KDB data in sync with Marcia and Robert Ascher’s original databooks and Peyrera’s original sources.

I am also indebted to:

  • Sabine Hyland who has so inspired me so much, and who has been unquestioningly generous with her wisdom and support, and for her khipus! Añaypas Yachachiq.
  • Jon Clindaniel who was one of the first archaeologists/computational anthropologists to use modern data science techniques on khipus. Jon’s support has been invaluable in the production of this field guide.

About the Field Guide

Inka khipus remain one of the world’s last undeciphered historical mediums. Are they writing? or just record-keeping? What do they mean? We admire the Arabs who brought us the concepts of 0 and base 10, and replaced Roman mathematics. The Inkas did that also. We admire the Romans who conquered a continent. The Inkas did that also. I could keep going but you get the idea. As an American immigrant, I am painfully aware, how notably blind “western civilization” is to the accomplishments of our South American neighbors.

The Inka’s unique approach to communication, using cloth as a medium, has fascinated me for much of my adult life. As a child I loved to read books about scripts and symbols’s - I reveled in Herman Hesse’s The Glass Bead Game, and could easily transport myself into the role of a novitiate monk - building universes on symbols represented by glass beads. The patterns of chess became my first “glass bead game.” and then the delightful inventions of algebra and calculus. As a young unemployed architect, I read with fascination, and a little bit of envy, the story of British architect Michael Ventris. Ventris built on the work of Alice Kober to decipher the Mycenaean Greek script Linear B. As an adult, I have been amazed at how rapidly 2000 years of Mayan writing have became understood in a mere 50 years. It is an incredibly moving thing to hear Linda Schele recite the history of a people from a thousand years ago, in their own language.

In high school, I picked up Ascher’s Mathematics of the Incas - Code of the Quipu in a Berkeley California bookstore. After a quick read, it sat on my bookshelf waiting to inspire me again. For the last thirty years I have worked in the field of Natural Language Processing (NLP). We used to call it Computational Linguistics, but frankly we were never very good linguists, and Natural Language Processing is a humbler and more accurate term. We’re the idiot savants that provide the 21st century equivalent of the secretarial pool. Every once in a while, I’d think, gee - could I apply everything I’m learning in NLP to khipu decipherment? Then a few years ago I met a professor in Ecuador, and I started learning Quechua, and before I knew it … I had become a knot-head.

In the last 70 years, decipherment has become a community activity. Everyone contributes some little tiny thing, and then all of a sudden - !!!WHAM!!! a key synthesis emerges from all those little things. Any language dreamer dreams that they might be The One, who after enough hard work, gains an insight that changes directions. But the truth is, we dreamers… (yes, I’m one)…, we dreamers are content if we are able to contribute one tiny thing. This, perhaps, is my one tiny thing (or two… or three…).

Project Phases

This is a large project. As such it is divided into three phases:

Phase 1 - Reading and Writing (Completed)

In phase 1 a basic understanding of khipu was achieved. This involves five steps.

  1. Yak Shaving - All data science projects start by yak-shaving, the affectionate name for the process of cleaning data, checking for integrity, etc. This project was no different - Sadly, integrity checks led to a loss of one-sixth of the khipus from the database. After removing the khipus that failed integrity checks, the Harvard Khipu Database SQL tables were transformed into CSV spreadsheets capable of being viewed in a variety of applications. The current database, now the largest and most accurate khipu database in the world, has taken over 4 years to build.

  2. Exploratory Data Analysis - What kinds of knots are there, how are knots, cords, cord colors and groups distributed. What are likely spreadsheet khipus, and what are possibly something else such as a narrative khipu? What things do we want to emphasize in rendering?

  3. Class Building - Simple Python functions and the Python Pandas Dataframe library will not easily provide the type of functionality and interface we need to draw khipus and do more sophisticated data analysis. A Python class object has been built built for each Khipu component, knot, cord, cord color, cord group, primary cord etc. This class library then supports the rendering of Khipu and of more tailored types of data inquiry and output.

  4. Khipu Rendering - Many khipu scholars regard khipu as a “tactile medium” (think of khipu reading as a kind of braille for example). Understanding them from CSV tables, is the farthest thing from tactile. Rendering is needed. Producing the code to satisfactorily render khipu has taken many, many months. As the Russians say, “It’s not a miracle the bear dances well. It’s a miracle the bear dances at all.”

Phase 2 - Reproduction of Existing Studies (Completed)

Phase 2 of this project was an exploration of existing work in khipu analysis. In this phase, I attempted to identify, reproduce, and occasionally extend, studies of existing khipu, such as:

This journey will provide the smorgasboard of analyses types and analytical tools needed to do more decipherment.

Phase 3 - Using Data Science and Natural Language Processing (NLP) Techniques (Ongoing)

In Phase 3 modern Data Science and NLP techniques are being applied to Khipu.

The great bird educator and ornithologist, Roger Tory Peterson, produced the first bird “field-guide” of the modern age. Rather than simply showing a picture of a duck, Peterson had arrows that pointed out key features of a particular duck to look for in identification. The increased curve (the 2nd derivative in mathematical terms) of a bill of an avocet allowed you to identify it as female or male; the presence of a white rump patch allowed you to confirm that the raptor was in fact a northern harrier, etc. Now known as Fieldmarks, these key identification traits will be the outcome of Phase 3.

What types of Fieldmarks will we look for? As examples, we can examine verso/recto cord attachments, or the presence of Z vs S knots (i.e. Urton’s studies), or we could look for color and patterns (i.e. Sabine Hyland’s work), or cord distribution and summation patterns (i.e. Marcia Ascher’s detailed studies). Whenever I see something intriguing (as in it stands out), and at a higher level than a simple knot or cord characteristic, it will be noted as a potential Fieldmark. The goal of Phase 3 then, is to finish with a set of Fieldmarks that allow us to categorize khipu by “Family” - hence the name of this site - the Khipu Field Guide.

There is an old joke. Stupid scientist does an experiment with a frog.
    Jump Froggy! he says. Frog jumps. Stupid scientist cuts off one leg.
    Jump Froggy! Jump he says. Frog jumps. Another leg. Another jump.

    Finally he cuts off the last leg.
    Jump Froggy! Jump! Nothing happens. He yells louder
    JUMP FROGGY!!!! JUMP!!!! Nothing happens.

He writes in his lab notebook, “After cutting off fourth leg, frog became deaf.

So it is with khipu analysis. The decoding of unknown “languages” is fraught with stupid science. The goal is to use modern data science to tease out more information about khipus. Like Pygmalion, I want khipus to speak. I suspect, however, at the end of the day, I will be ecstatic, if I simply get them to mumble, squeak, or even make the sound of a punctured balloon.