While both ChatGPT and Gemini produced coherent summaries of Tacitus’ digital history, they also generated “phantom sources,” as Salvaggio (2025) and Tenzer et al. (2024) warn. This forced me to confront my own instinct to trust well-written text. AI’s polished language can disguise its lack of historical grounding, a problem Graham (2020) describes as “phantom authority.” Recognizing this made me more cautious about accepting digital outputs at face value.

inking atomic notes using wikilinks forced me to clarify conceptual relationships and avoid redundancy. My notes now reflect a networked understanding of digital history: an interconnected web of people, ideas, and technologies rather than a list of definitions. This structure mirrors the way historians themselves trace connections between events, actors, and sources—only now, the logic is embedded in digital architecture.

When I added YAML properties to my own notes, I began to understand that metadata is never neutral. A property like type or date might seem simple, but it decides how information is stored, sorted, and found. That small act of labeling defines what becomes visible in a database and what doesn’t. This connects to the idea of “dark data,” the information that stays invisible because it isn’t recorded within the system’s limits. Thinking through this process made me realize that data creation is interpretive work—it involves judgment, context, and responsibility.

Welcome to my Lab Notebook - Reloaded Welcome to my lab notebook, version 3.0. My original open lab notebooks began on the wiki platform OpenWetWare, moved to a personally hosted Wordpress platform, and now run on a Jekyll-powered platform (site-config), but the basic idea remains the same. For completeness, earlier entries from both platforms have been migrated here. Quoting from my original introduction to the Wordpress notebook: Disclaimer: Not a Blog Welcome to my open lab notebook. This is the active, permanent record of my scientific research, standing in place of the traditional paper bound lab notebook. The notebook is primarily a tool for me to do science, not communicate it. I write my entries with the hope that they are intelligible to my future self; and maybe my collaborators and experts in my field. Only the occasional entry will be written for a more general audience. […] In these pages you will find not only thoughts and ideas, but references to the literature I read, the codes or manuscripts I write, derivations I scribble and graphs I create and mistakes I make.  Why an open notebook? Is it working? My original introduction to the notebook from November 2010 dodged this question by suggesting the exercise was merely an experiment to see if any of the purported benefits or supposed risks were well-founded. Nearly three years in, can I draw any conclusions from this open notebook experiment? In that time, the notebook has seen six projects go from conception to publication, and a seventh founder on a null result (see #tribolium). Several more projects continue to unfold. I have often worked on several projects simultaneously, and some projects branch off while others merge, making it difficult to capture all the posts associated with a single paper into a single tag or category. Of course not all ideas make it into the paper, but they remain captured in the notebook. I often return to my earlier posts for my own reference, and frequently pass links to particular entries to collaborators or other colleagues. On occasion I have pointed reviewers of my papers to certain entries discussing why we did y instead of x, and so forth. Both close colleagues and researchers I’ve never met have emailed me to follow up on something they had read in my notebook. This evidence suggests that the practice of open notebook science can faciliate both the performance and dissemination of research while remaining compatible and even synergistic with academic publishing. I am both proud and nervous to know of a half dozen other researchers who have credited me for inspiring them to adopt open or partially open lab notebooks online. I am particularly grateful for the examples, interactions, and ideas from established practitioners of open notebook science in other fields. My collaborators have been largely been somewhere between favorable and agnostic towards the idea, with the occasional request for delayed or off-line notes. More often gaps arise from my own lapses in writing (or at least being intelligible), though the automated records from Github in particular, as well as Flickr (image log), Mendeley (reading log), and Twitter and the like help make up for some of the gaps. The Integrated Notebook becomes the Knitted Notebook In creating my wordpress lab notebook, I put forward the idea of an “Integrated Lab Notebook”, a somewhat convoluted scheme in which I would describe my ideas and analyses in Wordpress posts, embed figures from Flickr, and link them to code on Github. Knitr simplified all that. I can now write code, analysis, figures, equations, citations, etc, into a single Rmarkdown format and track it’s evolution through git version control. The knitr markdown format goes smoothly on Github, the lab notebook, and even into generating pdf or word documents for publication, never seperating the code from the results. For details, see “writing reproducibly in the open with knitr.” Navigating the Open Notebook You can page through the notebook chronologically just like any paper notebook using the “Next” and “Previous” buttons on the sidebar. The notebook also leverages all of the standard features of a blog: the ability to search, browse the archives by date, browse by tag or browse by category. follow the RSS feed add and share comments in Disqus I use categories as the electronic equivalent of separate paper notebooks, dividing out my ecological research projects, evolutionary research topics, my teaching notebook, and a few others. As such, each entry is (usually) made into exactly one category. I use tags for more flexible topics, usually refecting particular projects or methods, and entries can have zero or multiple tags. It can be difficult to get the big picture of a project by merely flipping through entries. The chronological flow of a notebook is a poor fit to the very nonlinear nature of research. Reproducing particular results frequently requires additional information (also data and software) that are not part of the daily entries. Github repositories have been the perfect answer to these challenges. (The real notebook is Github) My Github repositories offer a kind of inverted version of the lab notebook, grouped by project (tag) rather than chronology. Each of my research projects is now is given it’s own public Github repository. I work primarily in R because it is widely used by ecologists and statisicians, and has a strong emphasis on reproducible research. The “R package” structure turns out to be brilliantly designed for research projects, which specifies particular files for essential metadata (title, description, authors, software dependencies, etc), data, documentation, and source code (see my workflow for details). Rather than have each analysis described in full in my notebook, they live as seperate knitr markdown files in the inst/examples directory of the R package, where their history can be browsed on Github, complete with their commit logs. Long or frequently used blocks of code are written into functions with proper documentation in the package source-code directory /R, keeping the analysis files cleaner and consistent. The issues tracker connected to each Github repository provides a rich TO DO list for the project. Progress on any issue often takes the form of subsequent commits of a particular analysis file, and that commit log can automatically be appended to the issue. The social lab notebook When scripting analyses or writing papers, pretty much everything can be captured on Github. I have recently added a short script to Jekyll which will pull the relevant commit logs into that day’s post automatically. Other activities fit less neatly into this mold (reading, math, notes from seminars and conferences), so these things get traditional notebook entries. I’m exploring automated integration for other activities, such as pulling my current reading from Mendeley or my recent discussions from Twitter into the notebook as well. For now, feed for each of these appear at the top of my notebook homepage, with links to the associated sites.

Open science is a broad term for various efforts to make both the process and products of scientific research accessible to society at large. This encompasses both "open access" -- the lowering of economic barriers for the accessing of scientific publications and results -- and "open research" -- exposing the process of research to view, not just its traditional products. In the latter category, "open notebook science" aims to place notes, calculations, protocols, and evaluation of interim results into public view in order to allow scientists and the community at large to evaluate not just conclusions, but every step of the process. "Reproducible research" covers efforts to bundle publication of results with the raw data, software algorithms, and calculations needed to reconstruct the published results. My commitment to open science began with open access, and attempts to ensure that my written output was -- to the extent possible -- available online in freely downloadable format. This is always a work in progress, because older publications are often unavailable given paywalls or commercial licenses by academic publishers. To the extent possible, I will always make versions of publications available online, and I will attempt to choose journals with permissive preprint/postprint policies. I am slowly attempting to reconstruct PDF versions of older conference papers, many of which I have only in print files, which will need to be scanned. But by far the more important aspect of open science is an open process, and reproducible results. To that end, I have been exploring the use of wikis and blogs to record interim thinking on research topics, and this is the second iteration of an online "lab notebook" that goes beyond occasional blog posting. My first digital lab notebook was a local installation of the Instiki wiki, synchronized with Dropbox. This was useful for doing my own work wherever I happened to be, but was not truly "open" in the sense of public access. I have been migrating some of those reading notes, and topical notebooks to this current iteration, and that process is ongoing. My first "online open notebook" was hosted by Wikispaces, but I found that the lack of offline access was difficult for me, given travel and limited internet access where I live and work. This current iteration began when I stumbled onto Jekyll and Github Pages, and then learned of Carl Boettiger's sophisticated efforts at open notebook science using these components. My own notebook and reproducible notes are not nearly as advanced as Carl's workflow, but he continues to provide the paradigm toward which I believe many of us are striving. The community seems to be developing a taxonomy of "open notebook science" efforts, which allows readers to understand what they can expect from an online lab notebook. ONSclaims has two dimensions to its claims classification: completeness and immediacy. "All Content Immediate" indicates a lab notebook, for example, in which the scientist has the entirety of their notes, calculations, and data available immediately as generated. Such a state indicates that "if it isn't in the notebook, others can assume you haven't done it." This is a laudable goal, but since my process and the site are still evolving, I'm claiming a lesser classification, indicated by the icon here: Selected Content Immediate. Some of my manuscripts (including my dissertation text) are outside the online notebook format, and not all of my analyses are yet pipelined in such a way as to make them easy to post, but I'm evolving towards that. Unless otherwise noted (i.e., on a draft manuscript), notes posted here is made available under the Creative Commons NonCommercial-Attribution-ShareAlike license. This means you are free to make use of it, change it, use it for any non-commercial purposes, as long as you acknowledge the source. Journal manuscripts under development here are often NOT covered by this Creative Commons license, because they will eventually be subject to whatever license the target journal requires. Thus, drafts are readable in their posted form, but all rights are reserved beyond viewing (and, of course, having your own ideas with respect to the material). Software and tools I write for generating scientific results will always have a free, open-source version available for use by scholars, students, and the community. I'm not saying that I don't write commercial software, or that I won't take research results and find ways to create products. I am saying, however, that if I work on a piece of research, and communicate those results to the community, members of the community need a way to see what I've done, replicate it if desired, refute my claims if I turn out to be wrong, and use those tools and software in their own work to do something better.

Open science is a broad term for various efforts to make both the process and products of scientific research accessible to society at large. This encompasses both "open access" -- the lowering of economic barriers for the accessing of scientific publications and results -- and "open research" -- exposing the process of research to view, not just its traditional products. In the latter category, "open notebook science" aims to place notes, calculations, protocols, and evaluation of interim results into public view in order to allow scientists and the community at large to evaluate not just conclusions, but every step of the process. "Reproducible research" covers efforts to bundle publication of results with the raw data, software algorithms, and calculations needed to reconstruct the published results. My commitment to open science began with open access, and attempts to ensure that my written output was -- to the extent possible -- available online in freely downloadable format. This is always a work in progress, because older publications are often unavailable given paywalls or commercial licenses by academic publishers. To the extent possible, I will always make versions of publications available online, and I will attempt to choose journals with permissive preprint/postprint policies. I am slowly attempting to reconstruct PDF versions of older conference papers, many of which I have only in print files, which will need to be scanned. But by far the more important aspect of open science is an open process, and reproducible results. To that end, I have been exploring the use of wikis and blogs to record interim thinking on research topics, and this is the second iteration of an online "lab notebook" that goes beyond occasional blog posting. My first digital lab notebook was a local installation of the Instiki wiki, synchronized with Dropbox. This was useful for doing my own work wherever I happened to be, but was not truly "open" in the sense of public access. I have been migrating some of those reading notes, and topical notebooks to this current iteration, and that process is ongoing. My first "online open notebook" was hosted by Wikispaces, but I found that the lack of offline access was difficult for me, given travel and limited internet access where I live and work. This current iteration began when I stumbled onto Jekyll and Github Pages, and then learned of Carl Boettiger's sophisticated efforts at open notebook science using these components. My own notebook and reproducible notes are not nearly as advanced as Carl's workflow, but he continues to provide the paradigm toward which I believe many of us are striving. The community seems to be developing a taxonomy of "open notebook science" efforts, which allows readers to understand what they can expect from an online lab notebook. ONSclaims has two dimensions to its claims classification: completeness and immediacy. "All Content Immediate" indicates a lab notebook, for example, in which the scientist has the entirety of their notes, calculations, and data available immediately as generated. Such a state indicates that "if it isn't in the notebook, others can assume you haven't done it." This is a laudable goal, but since my process and the site are still evolving, I'm claiming a lesser classification, indicated by the icon here: Selected Content Immediate. Some of my manuscripts (including my dissertation text) are outside the online notebook format, and not all of my analyses are yet pipelined in such a way as to make them easy to post, but I'm evolving towards that. Unless otherwise noted (i.e., on a draft manuscript), notes posted here is made available under the Creative Commons NonCommercial-Attribution-ShareAlike license. This means you are free to make use of it, change it, use it for any non-commercial purposes, as long as you acknowledge the source. Journal manuscripts under development here are often NOT covered by this Creative Commons license, because they will eventually be subject to whatever license the target journal requires. Thus, drafts are readable in their posted form, but all rights are reserved beyond viewing (and, of course, having your own ideas with respect to the material). Software and tools I write for generating scientific results will always have a free, open-source version available for use by scholars, students, and the community. I'm not saying that I don't write commercial software, or that I won't take research results and find ways to create products. I am saying, however, that if I work on a piece of research, and communicate those results to the community, members of the community need a way to see what I've done, replicate it if desired, refute my claims if I turn out to be wrong, and use those tools and software in their own work to do something better.

Open science is a broad term for various efforts to make both the process and products of scientific research accessible to society at large. This encompasses both "open access" -- the lowering of economic barriers for the accessing of scientific publications and results -- and "open research" -- exposing the process of research to view, not just its traditional products. In the latter category, "open notebook science" aims to place notes, calculations, protocols, and evaluation of interim results into public view in order to allow scientists and the community at large to evaluate not just conclusions, but every step of the process. "Reproducible research" covers efforts to bundle publication of results with the raw data, software algorithms, and calculations needed to reconstruct the published results. My commitment to open science began with open access, and attempts to ensure that my written output was -- to the extent possible -- available online in freely downloadable format. This is always a work in progress, because older publications are often unavailable given paywalls or commercial licenses by academic publishers. To the extent possible, I will always make versions of publications available online, and I will attempt to choose journals with permissive preprint/postprint policies. I am slowly attempting to reconstruct PDF versions of older conference papers, many of which I have only in print files, which will need to be scanned. But by far the more important aspect of open science is an open process, and reproducible results. To that end, I have been exploring the use of wikis and blogs to record interim thinking on research topics, and this is the second iteration of an online "lab notebook" that goes beyond occasional blog posting. My first digital lab notebook was a local installation of the Instiki wiki, synchronized with Dropbox. This was useful for doing my own work wherever I happened to be, but was not truly "open" in the sense of public access. I have been migrating some of those reading notes, and topical notebooks to this current iteration, and that process is ongoing. My first "online open notebook" was hosted by Wikispaces, but I found that the lack of offline access was difficult for me, given travel and limited internet access where I live and work. This current iteration began when I stumbled onto Jekyll and Github Pages, and then learned of Carl Boettiger's sophisticated efforts at open notebook science using these components. My own notebook and reproducible notes are not nearly as advanced as Carl's workflow, but he continues to provide the paradigm toward which I believe many of us are striving. The community seems to be developing a taxonomy of "open notebook science" efforts, which allows readers to understand what they can expect from an online lab notebook. ONSclaims has two dimensions to its claims classification: completeness and immediacy. "All Content Immediate" indicates a lab notebook, for example, in which the scientist has the entirety of their notes, calculations, and data available immediately as generated. Such a state indicates that "if it isn't in the notebook, others can assume you haven't done it." This is a laudable goal, but since my process and the site are still evolving, I'm claiming a lesser classification, indicated by the icon here: Selected Content Immediate. Some of my manuscripts (including my dissertation text) are outside the online notebook format, and not all of my analyses are yet pipelined in such a way as to make them easy to post, but I'm evolving towards that. Unless otherwise noted (i.e., on a draft manuscript), notes posted here is made available under the Creative Commons NonCommercial-Attribution-ShareAlike license. This means you are free to make use of it, change it, use it for any non-commercial purposes, as long as you acknowledge the source. Journal manuscripts under development here are often NOT covered by this Creative Commons license, because they will eventually be subject to whatever license the target journal requires. Thus, drafts are readable in their posted form, but all rights are reserved beyond viewing (and, of course, having your own ideas with respect to the material). Software and tools I write for generating scientific results will always have a free, open-source version available for use by scholars, students, and the community. I'm not saying that I don't write commercial software, or that I won't take research results and find ways to create products. I am saying, however, that if I work on a piece of research, and communicate those results to the community, members of the community need a way to see what I've done, replicate it if desired, refute my claims if I turn out to be wrong, and use those tools and software in their own work to do something better.

We live in a current moment where, to get things done, we have to deploy terms in ways that capture the imagination of decision makers and the public in ways that affect change

While tempting to store meaningful information in formatting like color codes or bolded text, this is a very bad idea. Formatting gets easily broken between software versions and applications.

There’s no perfect format choice that applies to every project, but there are some trade offs to keep in mind.

When working with legacy data, or even on your own large projects, you’ll need to begin by gathering many datasets into a harmonious collection

data can’t ever truly be “raw”(Gitelman 2013)

These layers represent an accretion of practices, decisions, and compromises by a host of different agents, by no means all archaeological, many of whom will be unaware of each other.

he digital 'cognitive artefacts' that archaeologists use – for example, digital cameras, total stations, laser scanners, proton magnetometers, X-ray fluorescence machines, and their ilk – all encapsulate in various ways a mixture of techniques, calculations, and interventions that they employ on our behalf to explore, reveal, capture, and characterise archaeological objects

Cognitive artifacts are … important to study, not only because they make us more powerful and versatile thinkers, but also because they shape and transform our cognitive system and cognitive practices

what makes an object relevant and useful in relation to the production of scientific knowledge … is not just the object itself, but the knowledge involved in recognizing an object for what it is and how it can be used

the tools we create, adopt, refine and employ have the effect of augmenting and scaffolding our thought and analysis