reply to u/atomicnotes at https://www.reddit.com/r/Zettelkasten/comments/16njtfx/comment/k1tuc9c/?utm_source=reddit&utm_medium=web2x&context=3

u/atomicnotes, this is an excellent question. (Though I'd still like to come to terms with people who don't think it acts as a knowledge management system, there's obviously something I'm missing.)

Some of your distinction comes down to how one is using their zettelkasten and what sorts of questions are being asked of it. One of the earliest descriptions I've seen that begins to get at the difference is the description by Beatrice Webb of her notes (appendix C) in My Apprenticeship. As she describes what she's doing, I get the feeling that she's taking the same broad sort of notes we're all used to, but it's obvious from her discussion that she's also using her slips as a traditional database, but is lacking modern vocabulary to describe it as such.

Early efforts like the OED, TLL, the Wb, and even Gertrud Bauer's Coptic linguistic zettelkasten of the late 1970s were narrow enough in scope and data collected to make them almost dead simple to define, organize and use as databases on paper. Of course how they were used to compile their ultimate reference books was a bit more complex in form than the basic data from which they stemmed.

The Mundaneum had a much more complex flavor because it required a standardized system for everyone to work in concert against much more freeform as well as more complex forms of collected data and still be able to search for the answers to specific questions. While still somewhat database flavored, it was dramatically different from the others because of it scope and the much broader sorts of questions one could ask of it. I think that if you ask yourself what sorts of affordances you get from the two different groups (databases and word processors (or even their typewriter precursors) you find even more answers.

Typewriters and word processors allowed one to get words down on paper quicker by a magnitude of order or two faster, and in combination with reproduction equipment, made it easier to spin off copies of the document for small scale and local mass distribution a lot easier. They do allow a few affordances like higher readability (compared with less standardized and slower handwriting), quick search (at least in the digital era), and moving pieces of text around (also in digital). Much beyond this, they aren't tremendously helpful as a composition tool. As a thinking tool, typewriters and word processors aren't significantly better than their analog predecessors, so you don't gain a huge amount of leverage by using them.

On the other hand, databases and their spreadsheet brethren offer a lot more, particularly in digital realms. Data collection and collation become much easier. One can also form a massive variety of queries on such collected data, not to mention making calculations on those data or subjecting them to statistical analyses. Searching, sorting, and making direct comparisons also become far easier and quicker to do once you've amassed the data you need. Here again, Beatrice Webb's early experience and descriptions are very helpful as are Hollerinth's early work with punch cards and census data and the speed with which the results could be used.

Now if you compare the affordances by each of these in the digital era and plot their shifts against increasing computer processing power, you'll see that the value of the word processor stays relatively flat while the database shows much more significant movement.

Surely there is a lot more at play, particularly at scale and when taking network effects into account, but perhaps this quick sketch may explain to you a bit of the difference you've described.

Another difference you may be seeing/feeling is that of contextualization. Databases usually have much smaller and more discrete amounts of data cross-indexed (for example: a subject's name versus weight with a value in pounds or kilograms.) As a result the amount of context required to use them is dramatically lower compared to the sorts of data you might keep in an average atomic/evergreen note, which may need to be more heavily recontextualized for you when you need to use it in conjunction with other similar notes which may also need you to recontextualize them and then use them against or with one another.

Some of this is why the cards in the Thesaurus Linguae Latinae are easier to use and understand out of the box (presuming you know Latin) than those you might find in the Mundaneum. They'll also be far easier to use than a stranger's notes which will require even larger contextualization for you, especially when you haven't spent the time scaffolding the related and often unstated knowledge around them. This is why others' zettelkasten will be more difficult (but not wholly impossible) for a stranger to use. You might apply the analogy of context gaps between children and adults for a typical Disney animated movie to the situation. If you're using someone else's zettelkasten, you'll potentially be able to follow a base level story the way a child would view a Disney cartoon. Compare this to the zettelkasten's creator who will not only see that same story, but will have a much higher level of associative memory at play to see and understand a huge level of in-jokes, cultural references, and other associations that an adult watching the Disney movie will understand that the child would completely miss.

I'm curious to hear your thoughts on how this all plays out for your way of conceptualizing it.

Are we stretching too far by saying that AI are currently emergent? Isn't this like saying that card indexes of the early 20th century are computers. In reality they were data storage and the "computing" took place when humans did the actual data processing/thinking to come up with new results.

Emergence would seem to actually be the point which comes about when the AI takes its own output and continues processing (successfully) on it.

Of course spreadsheets are databases of information and one can easily and profitably put all these details into index cards which are just as easy (maybe even easier) to move around

Phyllis Diller's gag file was arranged alphabetically by subject and ranged from "accessories" to "world affairs".

Thanks Sascha for an excellent primer on the internal machinations of our favorite machines beyond the usual focus on the storage/memory and indexing portions of the process.

Said another way, a zettelkasten is part of a formal logic machine/process. Or alternately, as Markus Krajewski aptly demonstrates in Paper Machines (MIT Press, 2011), they are early analog storage devices in which the thinking and logic operations are done cerebrally (by way of direct analogy to brain and hand:manually) and subsequently noted down which thereby makes them computers.

Just as mathematicians try to break down and define discrete primitives or building blocks upon which they can then perform operations to come up with new results, one tries to find and develop the most interesting "atomic notes" from various sources which they can place into their zettelkasten in hopes of operating on them (usually by juxtaposition, negation, union, etc.) to derive, find, and prove new insights. If done well, these newly discovered ideas can be put back into the machine as inputs to create additional newer and more complex outputs continuously. While the complexity of Lie Algebras is glorious and seems magical, it obviously helps to first understand the base level logic before one builds up to it. The same holds true of zettelkasten.

Now if I could only get the printf portion to work the way I want...

p xxvi

Hutchins closes his preface to his grand project with Mortimer J. Adler by giving pride of place to Adler's Syntopicon.

Adler's Syntopicon isn't just an index compiled into two books which were volumes 2 and 3 of The Great Books of the Western World, it's physically a topically indexed card index of data (a grand zettelkasten surveying Western culture if you will). It's value to readers and users is immeasurable and it stands as a fascinating example of what a well-constructed card index might allow one to do even when they don't have their own yet.

Adler spoke of practicing syntopical reading, but anyone who compiles their own card index (in either analog or digital form) will realize the ultimate value in creating their own syntopical writing or what Robert Hutchins calls participating in "The Great Conversation" across twenty-five centuries of documented human communication.

See also: https://hypothes.is/a/WF4THtUNEe2dZTdlQCbmXw

The way Hutchins presents the idea of "Adler's achievement" here seems to indicate that Hutchins didn't have a direct hand in compiling or working on it directly.

source apparently from: “Apparition de la fiche et constitution des sciences humaines: encore une invention que les historiens célèbrent peu.” Michel Foucault, Surveillir et punir. Naissance de la prison (Paris: Gallimard, 1975), 287, referring to A. Bonneville, De la recidive (Paris, 1844), 92–93.

Note taking can also be done to create a database (a la Beatrice Webb's scientific note taking).

Memindex, Inc. of Rochester, NY manufactured a plastic "Phonedex" in the mid-20th century. It was made of Dow Chemical Styrene and sat underneath a standard rotary dial telephone and contained index cards with one's lists of phone numbers on them.

Basic statistics regarding the TLL: - ancient Latin vocabulary words: ca. 55,000 words - 10,000,000 slips - ca. 6,500 boxes - ca. 1,500 slips per box - library 32,000 volumes - contributors: 375 scholars from 20 different countries - 12 Indo-European specalists - 8 Romance specialists - 100 proof-readers - ca. 44,000 words published - published content: 70% of the entire vocabulary - print run: 1,350 - Publisher: consortium of 35 academies from 27 countries on 5 continents

Longest remaining words: - non / 37 boxes of ca 55,500 slips - qui, quae, quod / 65 boxes of ca. 96,000 slips - sum, esse, fui / 54.5 boxes of ca. 81,750 slips - ut / 35 boxes of ca 52,500 slips

Note that some of these words have individual zettelkasten for themselves approaching the size of some of the largest personal collections we know about!

[18:51]

https://aaew.bbaw.de/thesaurus-linguae-aegyptiae

The Wörterbuch der ägyptischen Sprache was an international collaborative zettelkasten project begun in 1897 and finally published as five volumes in 1926.

https://en.wikipedia.org/wiki/W%C3%B6rterbuch_der_%C3%A4gyptischen_Sprache

In the early twentieth century one might have created a card index to study a large textual corpus, but in the twenty first one is more likely to rely on a relational database instead.

I love the fact that the image for "Research & History" here is a six drawer card index!

Lustig, Jason. “‘Mere Chips from His Workshop’: Gotthard Deutsch’s Monumental Card Index of Jewish History.” History of the Human Sciences, vol. 32, no. 3, July 2019, pp. 49–75. SAGE Journals, https://doi.org/10.1177/0952695119830900

Cross reference preliminary notes from https://journals.sagepub.com/doi/abs/10.1177/0952695119830900

Finished reading 2023-02-21 13:04:00

urn:x-pdf:6053dd751da0fa870cad9a71a28882ba

A digitized version of Gertrud Bauer's zettelkasten has been available online since 2015.

https://refubium.fu-berlin.de/handle/fub188/24570

Some interesting programming and structured data with relationship to the Gertrud Bauer Zettelkasten Online.

Richter, Tonio Sebastian. “Whatever in the Coptic Language Is Not Greek, Can Wholly Be Considered Ancient Egyptian”: Recent Approaches towards an Integrated View of the Egyptian-Coptic Lexicon.” Journal of the Canadian Society for Coptic Studies. Journal de La Société Canadienne Pour Les Études Coptes 9 (2017): 9–32. https://doi.org/10.11588/propylaeumdok.00004673.

Skimmed for the specifics I was looking for with respect to Gertrud Bauer's zettelkasten.

As a complete aside I can't help but wonder if Tami Gottschalk is related to Louis R. Gottschalk, the historian who wrote Understanding history; a primer of historical method?

61 Available online at http://research.uni-leipzig.de/ddglc/bauerindex.html. The Work on this parergon to the lexicographical labors of the DDGLC project was funded by the Gertrud-und Alexander Böhlig-Stiftung. The digitization of the original card index was conducted by temporary collaborators and volunteers in the DDGLC project: Jenny Böttinger, Claudia Gamma, Tami Gottschalk, Josephine Hensel, Katrin John, Mariana Jung, Christina Katsikadeli, and Elen Saif. The IT concept and programming were carried out by Katrin John and Maximilian Moller.

Digitization of Gertrud Bauer's zettelkasten was underway in 2017 to put the data into a MySQL database with the intention of offering it as an online user interface sometime in 2017.

After browsing through a variety of the cards in Gertrud Bauer's Zettelkasten Online it becomes obvious that the collection was created specifically as a paper-based database for search, retrieval, and research. The examples and data within it are much more narrowly circumscribed for a specific use than those of other researchers like Niklas Luhmann whose collection spanned a much broader variety of topics and areas of knowledge.

This particular use case makes the database nature of zettelkasten more apparent than some others, particularly in modern (post-2013 zettelkasten of a more personal nature).

I'm reminded here of the use case(s) described by Beatrice Webb in My Apprenticeship for scientific note taking, by which she more broadly meant database creation and use.

In the 1990s Professor Alexander Böhlig of the University of Tuebingen gave Gertrud Bauer's zettelkasten to Professor Peter Nagel of Bonn. He in turn forwardd the seven cardboard boxes of slips to the Database and Dictionary of Greek Loanwords in Coptic (DDGLC) office for their use.

The Database and Dictionary of Greek Loanwords in Coptic (DDGLC) has scanned and placed the original slips from Gertrud Bauer's zettelkasten into a database for scholarly use. The database allows the replication of the hierarchical structure of Bauer's original compilation.

Goitein's index cards provided a database not only for his own work, but for those who studied documentary Geniza after him.

Goitein accumulated more than 27,000 index cards in his research work over the span of 35 years. (Approximately 2.1 cards per day.)

His collection can broadly be broken up into two broad categories: 1. Approximately 20,000 cards are notes covering individual topics generally making of the form of a commonplace book using index cards rather than books or notebooks. 2. Over 7,000 cards which contain descriptions of a single fragment from the Cairo Geniza.

A large number of cards in the commonplace book section were used in the production of his magnum opus, a six volume series about aspects of Jewish life in the Middle Ages, which were published as A Mediterranean Society: The Jewish communities of the Arab World as Portrayed in the Documents of the Cairo Geniza (1967–1993).

https://genizalab.princeton.edu/resources/goiteins-index-cards

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>u/Didactico</span> in Goitein's Index Cards : antinet (<time class='dt-published'>12/15/2022 23:12:33</time>)</cite></small>

Reference for UltraRecall (UR) being the most DEVONthink like Windows alternative. No mobile companion for UR. Look into this being paired with Obsidian

Natto https://natto.dev<br /> built by Paul Shen https://twitter.com/_paulshen

https://www.loom.com/share/a05f636661cb41628b9cb7061bd749ae

Synopsis: Maggie Delano looks at some of the affordances supplied by Tana (compared to Roam Research) in terms of providing better block-based user interface for note type creation, search, and filtering.

These sorts of tools and programmable note implementations remind me of Beatrice Webb's idea of scientific note taking or using her note cards like a database to sort and search for data to analyze it and create new results and insight.

It would seem that many of these note taking tools like Roam and Tana are using blocks and sub blocks as a means of defining atomic notes or database-like data in a way in which sub-blocks are linked to or "filed underneath" their parent blocks. In reality it would seem that they're still using a broadly defined index card type system as used in the late 1800s/early 1900s to implement a set up that otherwise would be a traditional database in the Microsoft Excel or MySQL sort of fashion, the major difference being that the user interface is cognitively easier to understand for most people.

These allow people to take a form of structured textual notes to which might be attached other smaller data or meta data chunks that can be easily searched, sorted, and filtered to allow for quicker or easier use.

Ostensibly from a mathematical (or set theoretic and even topological) point of view there should be a variety of one-to-one and onto relationships (some might even extend these to "links") between these sorts of notes and database representations such that one should be able to implement their note taking system in Excel or MySQL and do all of these sorts of things.

Cascading Idea Sheets or Cascading Idea Relationships

One might analogize these sorts of note taking interfaces to Cascading Style Sheets (CSS). While there is the perennial question about whether or not CSS is a programming language, if we presume that it is (and it is), then we can apply the same sorts of class, id, and inheritance structures to our notes and their meta data. Thus one could have an incredibly atomic word, phrase, or even number(s) which inherits a set of semantic relationships to those ideas which it sits below. These links and relationships then more clearly define and contextualize them with respect to other similar ideas that may be situated outside of or adjacent to them. Once one has done this then there is a variety of Boolean operations which might be applied to various similar sets and classes of ideas.

If one wanted to go an additional level of abstraction further, then one could apply the ideas of category theory to one's notes to generate new ideas and structures. This may allow using abstractions in one field of academic research to others much further afield.

The user interface then becomes the key differentiator when bringing these ideas to the masses. Developers and designers should be endeavoring to allow the power of complex searches, sorts, and filtering while minimizing the sorts of advanced search queries that an average person would be expected to execute for themselves while also allowing some reasonable flexibility in the sorts of ways that users might (most easily for them) add data and meta data to their ideas.

Jupyter programmable notebooks are of this sort, but do they have the same sort of hierarchical "card" type (or atomic note type) implementation?

Gotthard Deutsch (1859-1921) had a card index of 70,000 items relating to Jewish history.

There is a difference between various modes of note taking and their ultimate outcomes. Some is done for learning about an area and absorbing it into one's own source of general knowledge. Others are done to collect and generate new sorts of knowledge. But some may be done for raw data collection and analysis. Beatrice Webb called this "scientific note taking".

Historian Jacques Goutor talks about research preparation for this sort of data collecting and analysis though he doesn't give it a particular name. He recommends reading papers in related areas to prepare for the sort of data acquisition one may likely require so that one can plan out some of one's needs in advance. This will allow the researcher, especially in areas like history or sociology, the ability to preplan some of the sorts of data and notes they'll need to take from their historical sources or subjects in order to carry out their planned goals. (p8)

C. Wright Mills mentions (On Intellectual Craftsmanship, 1952) similar research planning whereby he writes out potential longer research methods even when he is not able to spend the time, effort, energy, or other (financial) resources to carry out such plans. He felt that just the thought experiments and exercise of doing such unfulfilled research often bore fruit in his other sociological endeavors.

Who is using these forms in practice? I'd love to see some examples.

This sort of set up could be used with some outlining functionality to streamline the content creation end of common note taking practices.

Is anyone using a spreadsheet program (Excel, Google Sheets) as the basis for their zettelkasten?

Link to examples of zettelkasten as database (Webb, Seignobos suggestions)

syndication link

Similar to the examples provided by Beatrice Webb in My Apprenticeship, the authors here are talking about a sort of scientific note taking method that is ostensibly similar to that of the use of a modern day computer database or spreadsheet function, but which had to be effected in index card form to do the sorting and compiling and analysis.

Do the authors here use the specific phrase scientific note taking? It appears that they do not.

Moreover

A zettelkasten type note taking method isn't only popular and useful for scholars by 1898, but is useful to "statisticians, financiers, and men of letters".

Note carefully the word "mechanically" here used in a pre-digital context. One can't easily keep large amounts of data in one's head at once to make sense of it, so having a physical and mechanical means of doing so would have been important. In 21st century contexts one would more likely use a spreadsheet or database for these types of manipulations at increasingly larger scales.

Beatrice Webb was using her custom note taking system in the lead up to the research that resulted in the publication of Industrial Democracy (1897).

Is there evidence that she was practicing this note taking/database practice earlier than this?

Mongoose Validation. This is essential.

Chawla, D. S. (2021). Hundreds of ‘predatory’ journals indexed on leading scholarly database. Nature. https://doi.org/10.1038/d41586-021-00239-0

Notice the order: this is printed last, after the outer (real) transaction is committed, not when the inner "transaction" block finishes without error.

important qualification: the outer transaction, the (only) real transaction

At least I think this is talking about this as limitation/problem.

The limitation/problem being that it's not good/useful for performing after-transaction code only for specific actions.

But the next sentence "This is beneficial..." seems contradictory, so I'm a bit confused/unclear of what the intention is...

Looking at this project more, it doesn't appear to solve the "after-transaction code only for specific actions" problem like I initially thought it did (and like https://github.com/grosser/ar_after_transaction does), so I believe I was mistaken. Still not sure what is meant by "instead of specific model actions". Are they claiming that "before_commit_on_create" for example is a "specific model action"? (hardly!) That seems almost identical to the (not specific enough) callbacks provided natively by Rails. Oh yeah, I guess they do point out that Rails 3 adds this functionality, so this gem is only needed for Rails 2.

https://github.com/lmichan/BioDBS

br:https://biopragmatics.github.io/bioregistry/curation/

br:http://bioregistry.io/registry/bko

wd:https://www.wikidata.org/wiki/Q111249934

This wrongly assumes that

• Permanent records are always desirable
• Accountability undermines corporations

Tyler Black, MD. (2022, January 4). /1 =-=-=-=-=-=-=- Thread: Mortality in 2020 and myths =-=-=-=-=-=-=- 2020, unsurprisingly, came with excess death. There was an 18% increase in overall mortality, year on year. But let’s dive in a little bit deeper. The @CDCgov has updated WONDER, its mortality database. Https://t.co/DbbvvbTAZQ [Tweet]. @tylerblack32. https://twitter.com/tylerblack32/status/1478501508132048901

Singh Chawla, D. (2022). Massive open index of scholarly papers launches. Nature. https://doi.org/10.1038/d41586-022-00138-y

Antivaccine activists use a government database on side effects to scare the public. (n.d.). Retrieved December 7, 2021, from https://www.science.org/content/article/antivaccine-activists-use-government-database-side-effects-scare-public

Dumpster diving in the VAERS database to find more COVID-19 vaccine-associated myocarditis in children | Science-Based Medicine. (n.d.). Retrieved September 14, 2021, from https://sciencebasedmedicine.org/dumpster-diving-in-vaers-doctors-fall-into-the-same-trap-as-antivaxxers/

See how age and illnesses change the risk of dying from covid-19 | The Economist. (n.d.). Retrieved June 29, 2021, from https://www.economist.com/graphic-detail/covid-pandemic-mortality-risk-estimator

Li, X., Ostropolets, A., Makadia, R., Shoaibi, A., Rao, G., Sena, A. G., Martinez-Hernandez, E., Delmestri, A., Verhamme, K., Rijnbeek, P. R., Duarte-Salles, T., Suchard, M. A., Ryan, P. B., Hripcsak, G., & Prieto-Alhambra, D. (2021). Characterising the background incidence rates of adverse events of special interest for covid-19 vaccines in eight countries: Multinational network cohort study. BMJ, 373, n1435. https://doi.org/10.1136/bmj.n1435

Wadman, M. (2021). Antivaccine activists use a government database on side effects to scare the public. Science. https://doi.org/10.1126/science.abj6981

Early government intervention is key to reducing the spread of COVID-19. (2020, May 6). Science & Research News | Frontiers. https://blog.frontiersin.org/2020/05/06/early-government-intervention-is-key-to-reducing-the-spread-of-covid-19/

The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data. (2020, May 7). Opportunity Insights. https://opportunityinsights.org/paper/tracker/

Robert Colvile. (2021, February 16). The vaccine passports debate is a perfect illustration of my new working theory: That the most important part of modern government, and its most important limitation, is database management. Please stick with me on this—It’s much more interesting than it sounds. (1/?) [Tweet]. @rcolvile. https://twitter.com/rcolvile/status/1361673425140543490

COVID-19 Living Evidence. (2020, October 23). Weekly update of COAP As of 23.10.2020, we have indexed 80588 publications: 8902 pre-prints 71686 peer-reviewed publications Pre-prints: BioRxiv, MedRxiv Peer-reviewed: PubMed, EMBASE https://t.co/RaDy1Wm4Hq https://t.co/FYRaYPe8oG [Tweet]. @evidencelive. https://twitter.com/evidencelive/status/1319578431848353793

Else, H. (2020). How a torrent of COVID science changed research publishing—In seven charts. Nature, 588(7839), 553–553. https://doi.org/10.1038/d41586-020-03564-y

So do I.

Gen3 Data Commons overview/explained.

GDC purpose/summary: https://youtu.be/LY5SkHJplxc?t=118

every place has a history of different Time Zones because of the geographical, economical, political, religious reasons .These rules are present in IANA Time Zone database. Also it contains rules for Daylight Saving Time (DST) . Checkout the map on this page: https://en.wikipedia.org/wiki/Daylight_saving_time

Databases and filesystems are both systems which mediate the interaction between user and stable storage.

Often, the implicit aim of a database is to capture as much as they can about the structure of the data they store. The database is the all-knowing and exclusive arbiter of access to data.

If a user wants direct access to the data, a database isn't the right choice, but interacting directly with stable storage is too involved.

A Filesystem is a lightweight (container) abstraction in between a database and raw storage. Filesystems are opaque to the system (i.e. visible only to the user) and allow for a simple, hierarchical organizational structure of directories.

Impressed by this comment. It foreshadows what Roam would become:

• People think in terms of items belonging to multiple hierarchies
• If you allow users to describe items in a way that makes sense to them and allow them to search and browse by any of the terms they've used, you've solved many of the problems of existing file systems

What you need to build a complex information system is:

• Deep hierarchies for classifying things (overlapping hierarchies should be possible)
• Shallow hierarchies for noting relationships (Roam does this with a flat structure)
• Multi-values for every single field
• Controlled values (e.g. linking to other items when possible)

Wilkinson, Jack, Kellyn F. Arnold, Eleanor J. Murray, Maarten van Smeden, Kareem Carr, Rachel Sippy, Marc de Kamps, et al. ‘Time to Reality Check the Promises of Machine Learning-Powered Precision Medicine’. The Lancet Digital Health 0, no. 0 (16 September 2020). https://doi.org/10.1016/S2589-7500(20)30200-4.

COVID-19 reports. (n.d.). Imperial College London. Retrieved September 17, 2020, from http://www.imperial.ac.uk/medicine/departments/school-public-health/infectious-disease-epidemiology/mrc-global-infectious-disease-analysis/covid-19/covid-19-reports/

How much further would Bush have gone if he had known about graph theory? He is describing a graph database with nodes and edges and a graphical model itself is the key to the memex.

Outbreak Science Rapid PREreview • Dashboard. (n.d.). Retrieved September 11, 2020, from https://outbreaksci.prereview.org/dashboard?q=COVID-19&q=Coronavirus&q=SARS-CoV-2