rufuspollock

Exactly

You're absolutely right ... and this is more for a personal database (the way most people use Notion).

Strictly we could have titled this: the markdown database pattern for small personal databases.

The point was that for personal use e.g. keeping a list of projects, or books etc this is perfect. Or even for maintaining this list on a website.

It isn't for multiple simultaneous writes

I love astro content collections. Built https://markdowndb.com/ to have something system agnostic.

Yes it is markdown plus frontmatter that makes this work.

Point on comparison with other formats is really well taken. I think the main argument i would have is ubiquity of markdown and markdown tooling.

Cool Hadn't seen this before and will check it out - and add to the Way of Markdown

I really liked Logseq though i've ended up an Obsidian (and now mostly AI + markdown) user.

Super cool. I've been trying it out for publishing some of my own datasets.

Hi, i'm one of the co-creators. Let me know if you have any questions.

Totally! We're really love plain-text pkm.

We have this overall sense that "markdown is eating the world" in the sense that it is becoming a more and more ubiquitous and powerful format. What i would term "markdown plus" i.e. markdown plus extensions like frontmatter, wikilinks, typed backtick blocks you have something really pretty expressive - and add MDX and you have full JS(X) components.

At least, for reasonably small use cases (think under a 1000 items), this makes a collection of markdown files a great basis for a whole bunch of use cases from a document database to a PKM etc.

I take the point and perhaps one could think about what is useful to the "middle ground" of the uninitiated e.g. the policy-makers looking for some guidance, the journalists trying to make sense of the claims and counter-claims.

What we're trying to do here is set out the claims clearly (and atomically) and evaluate them in as transparent and honest a manner as possible. So far I've not seen this a lot on the internet despite the huge amount of material on this topic.

Hi, I'm one of the folks behind this project and happy to answer any questions.

If you want to know more about motivation and approach there is quite a bit of detail on https://web3.lifeitself.us/about

Could you reference some of the "real studies" you mention - this would help update and amend MacKay's work.

Just to flag that MacKay already estimated (in 2008) a Tesla at 15kwh per 100km (actually better than you have here). See Fig 20.22 on https://climate.lifeitself.us/without-hot-air/chap20/

> It showed how one should do a systems analysis for a country to understand how one can achieve the change required. I was astonished when I talked to several of the leading people responsible for energy policy in several political parties in my country, to find they really had no clue about what they where doing on a systems level.

Massive +1. And i agree that perhaps "reusing" the book would be useful. E.g. take the key factual approach and update analyses for particular technologies and then plug those together - which to some extent is what the pathway calculator did which is why it is worth trying to get the source for that https://github.com/life-itself/climate/issues/2

Thanks Niall - updating the book is exactly what we are hoping to do and still thinking the best form for that. Re that tool i've been in correspondence with one of the other creators re trying to understand the source code etc - see https://github.com/life-itself/climate/issues/2

Interesting. There have been a lot of attempts at "meta data portals" that search across portals. Most of them have struggled.

At Open Knowledge we built a really early one called opendatasearch.org in 2011/2012 - now defunct - and were involved in the first version of the pan EU open data portal. We also had the original https://ckan.net/ (and subsites) which is now https://datahub.io/ and has become much more focused on quality data and data deployment. [Disclosure: I was/am involved in many of these projects]

The challenge, as others have mentioned, is that data quality is very variable and searching for datasets is complicated (think of software as an analogy - searching for good code libraries is a bit of an art).

I imagine Google are trying this out before making datasets another "special type" of search result -- after all you can already search google for datasets. In addition, Google are already Google so including datasets will have a level of comprehensiveness and exposure you struggle with elsewhere (part of the power of monopoly in a sense!).

PS: for those looking for data gov sites https://dataportals.org/ has most of these.

Note Kaggle recently adopted the FrictionlessData.io Data Package specs: https://github.com/Kaggle/kaggle-api/wiki/Dataset-Metadata

Yes, state is still mediocre. Back in 2011 i did Chaos Computer Congress talk on "apt-get for Debian of Data". This itself came out of building the original data portal and open data catalog/hosting site in 2006 https://datahub.io/ (originally ckan.net).

The ideas there are now getting realised in Frictionless Data https://frictionlessdata.io/

This an initiative providing a simple way of "packaging" data like software plus an ecosystem of tools including a package manager etc - https://frictionlessdata.io/data-packages/.

Aims to be minimal, easy to adopt etc (e.g. based on CSV). It has got significant traction with integration and adoption into Pandas, OpenRefine etc.

https://datahub.io/ itself is entirely rebuilt around Data Packages and includes a package manager tool "data".

If you're interested to talk more please come chat on http://gitter.im/datahubio/chat

Suggest CSV plus a Table Schema in a nice little Data Package: https://frictionlessdata.io/data-packages/

There's a wide set of tooling for Tabular Data Packages, plus underlying data is CSV which anyone can use.

If you want this done automatically you can just publish your CSV to https://datahub.io/ and your Tabular Data Package is made automatically for you.