lakillo / archaeology-machine-learning

machine learning resources for archaeology

hi, I'm Lucy 👋

🔭 I'm currently ...

• an AHRC-funded PhD researcher at the University of Glasgow (Archaeology + Computing Science) and Historic Environment Scotland
• researching the impacts of machine learning and computer vision on workflows for archaeological survey (aka finding archaeological objects in remote sensing data + in the field)

🌱 I'm learning ...

• how to design + build machine learning systems

⚡ I'm looking to collaborate on ...

• machine learning tools for archaeology and geospatial

📫 how to reach me ...

archaeology-machine-learning's Issues

release the MVP

make a section explaining acronyms + techniques

separate from the README, a page or wiki?

add 10 example listings to repo for remote sensing application area

🗺️ ROADMAP

📖 introduction to the project

Machine learning (ML) methods present new ways of approaching archaeological research questions and interest in applying these methods continues to grow.

This repository collects resources relating to the application of ML methods to archaeological data, aiming to:

• provide an overview of the ways ML is being applied in archaeology
• spark new ideas whilst reducing duplication of work
• encourage the sharing of code, data, and other resources
• make resources more FAIR (Findable, Accessible, Interoperable, and Reuseable)

By doing this, we hope to support practitioners to learn about, critically apply, or contribute to conversations about, ML in archaeology.

🗺️ project roadmap

The roadmap for this project is divided up into milestones: specific moments we're working towards to move the project forwards. Within milestones there will be issues that need completing to reach the milestone.

Click on the milestone names below to browse our open issues, or check out the progress of issues across all milestones on our 🚦 project kanban board.

Milestone (2): 🗺️ project vision and roadmap

• make a plan for contributor engagement channels
• make a plan for a first release and archiving
• make a plan for adding new application areas

Milestone (3): 💬 feedback on MVP

• share the repo with the community
• get feedback on usability

🌟 completed milestones

Milestone (1): 🐣 minimum viable product: completed 2024-02-09 😸

🙌 contributing

check out our ✅ contributor guidelines to find out how to contribute!

🙏 acknowledgements

This project was kicked off as part of Open Seeds cohort 8, and was inspired by these great projects: satellite-image-deep-learning, Rchaeology, open-phytoliths, AncientMetagenomeDir, and open-archaeo.

test repo design with potential contributors and users

• complile list of potential contributors / users
• design questions / feedback channels
• share prototype repo with list
• report back findings in this issue

create a plan for adding new data types (e.g. text, artefacts, etc) and formalise as a new milestone

I've started the repo off off with a small scope, listing examples which use remote sensing data only.

There are other applications for machine learning in archaeology such as text or artefacts, so new sections on the README should be created to cover these data types and list examples.

set a finish line for content which means the MVP is ready

create contributor guidelines

👋 community introductions

A place for new particpants to say hi and introduce yourself!

share the repo with the community

make a plan for contributor engagement channels

make a plan for adding new application areas

note any feedback from the community

make a plan for a first release and archiving