[HN Gopher] A raw dump of companies from all over the world by L...
___________________________________________________________________
A raw dump of companies from all over the world by LinkedIn handle
Author : mfrye0
Score : 165 points
Date : 2023-05-17 15:50 UTC (7 hours ago)
(HTM) web link (blog.bigpicture.io)
(TXT) w3m dump (blog.bigpicture.io)
| wg0 wrote:
| What I am curious to know about is - what company buys from whom
| and the whole dependency graph to visualise how complex our
| modern economy is.
|
| But not sure that kind of information is in there.
| byyll wrote:
| Closest I can think of: https://www.importyeti.com
| yolo3000 wrote:
| That sort of data is normally not public
| sam_lowry_ wrote:
| Individual countries know this, and even share rather
| successfully across unions.
|
| EU exchanges VAT information which is exactly about who buys
| from whom... down to transactions of 120EUR and more if I am
| not mistaken.
|
| Commercial databases are more limited, but even those can
| trace ownership of companies to ultimate beneficial owners.
| Orbis from Bureau Van Dijk is probably the biggest of such
| databases.
| paxys wrote:
| You use "open source" multiple times in the post, HN title, HN
| comments, but:
|
| 1. The source code for the project isn't shared anywhere.
|
| 2. The data isn't shared under any standard open source license.
|
| 3. The terms of your site explicitly prohibit commercial use of
| this data.
|
| So what exactly makes this "open source in the broadest sense"?
| nxqs wrote:
| "It's 'open source'"... https://youtu.be/dTRKCXC0JFg?t=6
| mfrye0 wrote:
| Fair points. I agree the wording could be better.
|
| No, the source code is not available. This dataset is a subset
| of the raw data our system collects. Our final product made
| available via the API does a variety of processing steps on the
| raw data (dedupes, joins, ML predictions, etc). The final,
| processed data is the piece that is proprietary / subject to
| the terms.
|
| We will update the site terms to reference this dataset, as we
| aim to continue releasing an updated version each quarter. I'll
| have to double check with the lawyers, but it will most likely
| be MIT licensed.
| slabity wrote:
| What exactly does "open-source" mean to you? Because it
| sounds like there's absolutely nothing open about this other
| than a small scraping of LinkedIn data (which you should
| probably ask your lawyers if you're even allowed to license
| out).
|
| The wording isn't just misleading, it's a complete lie.
|
| EDIT: Nevermind, the title has been updated to accurately
| reflect this being a small datadump.
| time_to_smile wrote:
| It's open source in the sense of OSINT [0]. Clearly confusing
| on a site like Hacker News, but this has been standard usage of
| the term for that community for a long time now.
|
| 0. https://en.wikipedia.org/wiki/Open-source_intelligence
| companydataguy wrote:
| This is Duedil + Company Check + Open Corporates.
|
| Duedil and CC were (mostly) powered by Creditsafe data which is
| much better in Europe at least than D&B
|
| Open Corporates sold their data to Creditsafe for low 5 figures.
|
| Interesting point re DnB in Eu it's mostly a license if the brand
| name and owns little of the data or the business.
| mfrye0 wrote:
| Hey HN, we're thrilled to announce our latest project - the
| World's Largest Open Source Company Dataset. Our team has been
| working hard on this product for the past few months, and we're
| excited to finally share it with you all.
|
| We started off years ago trying to build a B2B app, but getting
| basic company data at scale was a huge barrier for us. This 15M+
| record dataset attempts to solve that and has all the key company
| fields like name, industry, size, location, LinkedIn handle, etc.
| We aim to update it quarterly to ensure that you always have the
| most up-to-date information.
|
| Disclaimer: Okay, we have to admit, we didn't exactly comb
| through every dataset out there to verify that ours is the
| world's largest, but we did our research, and we're pretty sure
| it might be. Whether or not that's true, we believe this dataset
| is a robust and invaluable resource for anyone interested in
| company data.
| mfrye0 wrote:
| So this blew up today. Reviewing all the comments now.
|
| 1. Yes, this is scraped from public sources. 2. Yes, this is
| free to use / is open source in the broadest sense. Apologies
| for the confusion on the lack of a license and no mention about
| this in our TOS. We probably should update our TOS to be
| clearer here. 3. This is a raw dump of companies from all over
| the world by LinkedIn handle. The handles are deduped, but the
| website is not.
| justinclift wrote:
| > Yes, this is free to use ...
|
| Including for commercial purposes?
| mfrye0 wrote:
| Yes.
| tyingq wrote:
| Seems at odds with your tos. https://bigpicture.io/terms
| jsty wrote:
| What's the license the dataset is released under? I poked
| around the documentation a bit but couldn't find it - apologies
| if it's in there!
| conzept wrote:
| The data is not licensed as opensource (only non-commercial
| use): "The Service and its entire contents, features and
| functionality (including but not limited to all information,
| software, text, displays, images, video and audio, and the
| design, selection and arrangement thereof), are owned by the
| Company, its licensors or other providers of such material
| and are protected by United States and international
| copyright, trademark, patent, trade secret and other
| intellectual property or proprietary rights laws. You are
| permitted to use the Service for Your personal, non-
| commercial use, or legitimate business purposes related to
| Your role as a customer of BigPicture.io." -
| https://bigpicture.io/terms
| rickette wrote:
| Out of curiosity: Would you be willing to share how you
| acquired this data? Website scraping or other means?
| Atlas22 wrote:
| Data is very likely to be from LinkedIn if you look at the
| field descriptions and stats. The only field that is 100%
| available is the one based on the LinkedIn URL. I would guess
| scraping unless LinkedIn provides an API for this data that I
| can't find.
| jamesgill wrote:
| They (Microsoft) have APIs for app/website integration, but
| that's all I know about.
|
| https://developer.linkedin.com/
| yolo3000 wrote:
| Most likely from scraping (crunchbase, yahoo,etc), unless
| they bought it from somewhere. In most countries you can get
| it from the chamber of commerce. Dun and Bradstreet and other
| similar companies. Some of these data aggregators will have
| partnership with other companies, and you can also
| (illegally) scrape it from there.
| speedgoose wrote:
| The blog picture looks to be generated with dalle2. The quality
| was mind blowing less than a year ago, while it is now a mess of
| artefacts compared to dalle2.5 (Bing), adobe firefly, stable
| diffusion, and of course MidJourney.
| [deleted]
| simonw wrote:
| It's a 2.64GB CSV file with the following columns:
| handle type name website founded
| industry specialties size city
| state country_code
|
| 15,263,246 rows.
|
| I think the main listing for Google is this one (as an example):
|
| 10361050:company/google,Public Company,Google,goo.gle,,Software
| Development,"search, ads, mobile, android, online video, apps,
| machine learning, virtual reality, cloud, hardware, artificial
| intelligence, youtube, and software","10,001+",Mountain
| View,California,US
| mfrye0 wrote:
| How did you compute this? I just did another check to verify
| (wc -l) and it's coming to 15,980,531.
| rahimnathwani wrote:
| wc -l will count all newlines, even those that are escaped.
| Perhaps some company descriptions have newlines?
| simonw wrote:
| I used wc -l at first, but I've just imported into SQLite and
| the count(*) is 15,263,246 - updated my previous comment
| (which had said 15,263,251).
|
| I downloaded the CSV and ran: sqlite-utils
| insert companies.db company companies-
| dataset-2023-02-ckgENv.csv --csv sqlite-utils enable-
| fts companies.db company name specialties sqlite-
| utils analyze-tables --save companies.db
|
| This lets me run searches against the name and specialties
| columns, and gives me those aggregate stats too.
| mfrye0 wrote:
| Ok. I'm not sure how this happened, but I think the dataset
| was somehow mislabeled. It appears that this dataset is the
| Q1 version, not the latest Q2. Can you please try re-
| downloading it?
|
| We're probably going to have to make an public announcement
| about this...
| simonw wrote:
| OK, that one has 15,948,996 rows.
|
| Here's what I got from running the same "sqlite-utils
| analyze-tables companies2.db company" command against it:
| company.handle: (1/10) Total rows:
| 15948996 Null rows: 0 Blank rows: 0
| Distinct values: 15948996 company.type:
| (2/10) Total rows: 15948996 Null
| rows: 0 Blank rows: 5253878
| Distinct values: 92 Most common:
| 5311279: Privately Held 5253878:
| 1290064: Self-Owned 1055857: Partnership
| 987045: Public Company 828643: Self-Employed
| 799655: Nonprofit 334552: Educational
| 87681: Government Agency 35: De financiacion
| privada company.name: (3/10)
| Total rows: 15948996 Null rows: 0
| Blank rows: 1591 Distinct values: 15549439
| Most common: 1591: 1098: .
| 277: A 246: - 164: None
| 155: X 142: N/A 132: ...
| 128: x 122: 1 company.website:
| (4/10) Total rows: 15948996 Null
| rows: 0 Blank rows: 3249552
| Distinct values: 11272926 Most common:
| 3249552: 86957: facebook.com
| 57769: instagram.com 46404: business.site
| 31397: linktr.ee 27882: indiamart.com
| 21852: wixsite.com 19008: negocio.site
| 17366: linkedin.com 13224: yelp.com
| company.founded: (5/10) Total rows:
| 15948996 Null rows: 0 Blank rows:
| 8040264 Distinct values: 1561
| Most common: 8040264: 524236:
| 2020 451742: 2017 441748: 2018
| 426575: 2019 418318: 2021 411391:
| 2016 389487: 2015 339212: 2014
| 299038: 2013 company.industry: (6/10)
| Total rows: 15948996 Null rows: 0
| Blank rows: 1334901 Distinct values: 421
| Most common: 1334901: 820156: IT
| Services and IT Consulting 651746:
| Construction 651557: Advertising Services
| 465857: Software Development 455111: Business
| Consulting and Services 447922: Real Estate
| 435151: Retail 355049: Financial Services
| 312937: Wellness and Fitness Services
| company.size: (7/10) Total rows: 15948996
| Null rows: 0 Blank rows: 2655086
| Distinct values: 123 Most common:
| 6646929: 2-10 3584483: 11-50
| 2655086: 1197530: 51-200
| 1091094: 1 employee 421595: 201-500
| 150053: 501-1,000 129373: 1,001-5,000
| 44755: 10,001+ 27742: 5,001-10,000
| company.city: (8/10) Total rows: 15948996
| Null rows: 0 Blank rows: 3155391
| Distinct values: 410985 Most common:
| 3155391: 269708: London 124059:
| Paris 113135: New York 99314: Sao
| Paulo 75428: Los Angeles 69691:
| Madrid 67328: Toronto 63738:
| Dubai 63456: New Delhi
| company.state: (9/10) Total rows: 15948996
| Null rows: 0 Blank rows: 4524015
| Distinct values: 58563 Most common:
| 4524015: 691167: England 584141:
| California 329584: Texas 291639:
| New York 286723: Florida 222552:
| Sao Paulo 185925: Maharashtra
| 171885: Ontario 171657: Ile-de-France
| company.country_code: (10/10) Total rows:
| 15948996 Null rows: 0 Blank rows:
| 2961064 Distinct values: 272
| Most common: 4059985: US 2961064:
| 1232403: GB 885302: IN 756411: FR
| 664235: BR 467501: DE 414433: NL
| 410372: ES 389535: CA
| simonw wrote:
| The thing I find most interesting is this:
| 269708: London 124059: Paris
| 113135: New York 99314: Sao Paulo
| 75428: Los Angeles 69691: Madrid
| 67328: Toronto 63738: Dubai
| 63456: New Delhi
|
| I would not have expected Sao Paulo to come fourth in
| this list, after New York but in front of Los Angeles. I
| just learned it's the 4th largest city in the world
| https://en.wikipedia.org/wiki/List_of_largest_cities -
| after Tokyo, Delhi, Shanghai - but I guess it has much
| more of a representation on LinkedIn than those other
| cities.
| GirishSharma643 wrote:
| I don't have any work email. Can anyone please share some other
| source to download?
| jehb wrote:
| Not an answer to your question, but I did find their
| justification for why they require a work email address
| intriguing.
|
| https://blog.bigpicture.io/how-we-stopped-spam-signups/
|
| I've been working through this issue a lot lately. There tend
| to be two camps, the "Make the experience good for the person
| trying to access the data, because good relationships are
| more important than the ability to contact someone" versus
| "Why should I give someone something for free when there is
| zero chance I can ever make a sale to that person?"
| simonw wrote:
| Ran https://sqlite-utils.datasette.io/en/stable/cli.html#cli-
| ana... to figure out the most common values in each column:
| company.type: (2/22) Total rows: 15263246
| Null rows: 0 Blank rows: 5032965
| Distinct values: 189 Most common:
| 5128934: Privately Held 5032965:
| 1202598: Self-Owned 1007806: Partnership
| 952111: Public Company 763992: Nonprofit
| 749117: Self-Employed 319885: Educational
| 84829: Government Agency 2423: De financiacion
| privada company.website: (4/22)
| Total rows: 15263246 Null rows: 0 Blank
| rows: 3043640 Distinct values: 10675220
| Most common: 3043640: 81214:
| facebook.com 50174: instagram.com
| 41050: business.site 27134: linktr.ee
| 24024: indiamart.com 19683: wixsite.com
| 16546: negocio.site 15864: linkedin.com
| 13201: yelp.com company.founded: (5/22)
| Total rows: 15263246 Null rows: 0 Blank
| rows: 7626823 Distinct values: 1551
| Most common: 7626823: 488964: 2020
| 438343: 2017 417847: 2018 404720: 2016
| 398489: 2019 386049: 2015 383686: 2021
| 338120: 2014 298768: 2013
| company.industry: (6/22) Total rows: 15263246
| Null rows: 0 Blank rows: 1274455
| Distinct values: 2591 Most common:
| 1274455: 793016: IT Services and IT Consulting
| 626267: Advertising Services 623184: Construction
| 424481: Real Estate 417648: Business Consulting and
| Services 416398: Software Development
| 401791: Retail 337914: Financial Services
| 305029: Wellness and Fitness Services
| company.specialties: (7/22) Total rows: 15263246
| Null rows: 0 Blank rows: 9681220
| Distinct values: 5226043 Most common:
| 9681220: 1678: Real Estate 1353:
| Education 557: Software Development
| 537: real estate 516: Recruitment 456:
| Marketing 420: Property Management 396:
| Digital Marketing 393: Hospitality
| company.size: (8/22) Total rows: 15263246
| Null rows: 0 Blank rows: 2531526
| Distinct values: 226 Most common:
| 6317189: 2-10 3459571: 11-50 2531526:
| 1170922: 51-200 730818: 1 employee
| 417504: 201-500 262702: 1 149520:
| 501-1,000 130678: 1,001-5,000 43399:
| 10,001+ company.city: (9/22) Total
| rows: 15263246 Null rows: 0 Blank rows:
| 3039470 Distinct values: 393107
| Most common: 3039470: 262475: London
| 116915: Paris 110220: New York 96914:
| Sao Paulo 72455: Los Angeles 66837:
| Madrid 65075: Toronto 59321: New Delhi
| 58151: Dubai company.state: (10/22)
| Total rows: 15263246 Null rows: 0 Blank
| rows: 4326168 Distinct values: 55773
| Most common: 4326168: 670232: England
| 567647: California 318576: Texas
| 283576: New York 276783: Florida
| 215523: Sao Paulo 172516: Maharashtra
| 164761: Ontario 161408: Ile-de-France
| company.country_code: (11/22) Total rows:
| 15263246 Null rows: 0 Blank rows: 2858360
| Distinct values: 272 Most common:
| 3943846: US 2858360: 1204699: GB
| 816378: IN 691296: FR 638895: BR
| 443326: DE 401268: NL 386207: ES
| 373460: CA company_fts.specialties: (13/22)
| Total rows: 15263246 Null rows: 0 Blank
| rows: 9681220 Distinct values: 5226043
| Most common: 9681220: 1678: Real
| Estate 1353: Education 557: Software
| Development 537: real estate 516:
| Recruitment 456: Marketing 420:
| Property Management 396: Digital Marketing
| 393: Hospitality
| tacker2000 wrote:
| Very interesting, thanks!
| r3trohack3r wrote:
| This is awesome and in the ballpark of something I'm working on
| right now.
|
| I currently have a list of developer handles, their associated
| aliases, and their associated email addresses - trying to map
| that set to employment history.
|
| Do folks know of any good data sets for this?
| tomalaci wrote:
| How hard is it to scrape LinkedIn for all its public profile
| data? Do you need special developer access? Do you need to sign
| some contract with MSFT for anything nontrivial?
| Murrawhip wrote:
| On your home page you list Microsoft as being one of your
| clients. I'm pretty impressed that you managed to sell them what
| appears to be (mostly) their own data.
| mpeg wrote:
| We went through this in the ad world before GDPR existed.
| Companies were selling datasets for advertising and, I remember
| one of my clients (one of the largest ad agencies in the world)
| telling me they had over 100 sources of data they augmented
| their publisher data with but they tested and saw there was
| only about 20% uniqueness on average between sources.
|
| They were buying the same data again and again, recycled and
| repackaged.
| [deleted]
| [deleted]
| ricardo81 wrote:
| 'open source'
|
| scrape crunchbase
|
| scrape companies house
|
| scrape wherever else
|
| scrape linkedin
|
| frontier company... or maybe not.
| [deleted]
| tuukkah wrote:
| A simple Wikidata query can return same type of information in
| case you prefer open data: https://w.wiki/6ify
| gorbachev wrote:
| Is LinkedIn scraped data open source?
| photochemsyn wrote:
| "With over 15 million global companies included..."
|
| What distinguishes a global from a non-global company? Also, how
| many of these are anonymous Delaware/Nevada/South Dakota/etc-
| based shell companies, or are those excluded from the dataset
| somehow?
| Veen wrote:
| I suspect it means "15 million companies from around the
| world".
| chirau wrote:
| I think they meant 'from across the globe' as in not
| necessarily from the US only or other specific geographies.
| nologic01 wrote:
| Good luck with your launch! This reminded me of a similar
| project, the opencorporates database
| (https://opencorporates.com/), though the target use cases seem
| different.
| givemeethekeys wrote:
| Are the entries deduped? If one company owns another, is that
| represented as well?
| pimlottc wrote:
| I'm confused, most of what's in this dataset has nothing to do
| with RedHat.
| Wronnay wrote:
| I always get "Oops! We ran into an error. Contact us at
| support@bigpicture.io" when I try to sign-up
| 1024core wrote:
| What would be really interesting is to turn this into a graph
| based on, say, past experience of CEOs/big dealings with each
| other/etc.
| tomalaci wrote:
| The moment those graph connections will show negative view of
| some of those CEOs they will start screaming about privacy
| issues and/or sue the graph creator.
|
| With scraping LinkedIn alone it should already be possible to
| create such graphs. Not sure why I haven't seen any. Either
| scraping LinkedIn isn't as straightforward or such grap-
| creating attempts have been shut down due to potential for
| defaming someone.
| 1024core wrote:
| I would say that scraping LinkedIn is not easy.
| babblingfish wrote:
| It's funny how OP does not address where this data comes from
| even though it's obviously from LinkedIn. I see many people in
| the comments asking questions so I will add my two cents as
| someone who is currently employed by LinkedIn and has an interest
| in web scraping.
|
| This dataset was taken from scraping the company pages from
| LinkedIn. A company has to pay to have this page, so this
| certainly does not include all companies. If you have a premium
| account your search is not rate limited so you can iteratively
| scrape anything you want even though it's technically a violation
| of the terms of service.
|
| There are many companies that sell data scraped from LinkedIn as
| a product. LinkedIn won a court case against hiQ Labs for
| scraping member data and other things[1]. I am not trying to
| compare this court case to the OP's website, just something worth
| mentioning.
|
| In any case, web scraping is a sort of gray area of the law. In
| my opinion, this data set does not contain member data and is not
| being monetized so it feels kosher to me.
|
| (Opinions expressed are solely my own and do not express the
| views or opinions of my employer.)
|
| [1] https://www2.staffingindustry.com/Editorial/IT-Staffing-
| Repo...
| mcenedella wrote:
| LinkedIn lost the HiQ case. Your GC claiming it's a win doesn't
| change that you lost, repeatedly, in multiple courts of law:
| https://en.m.wikipedia.org/wiki/HiQ_Labs_v._LinkedIn
| henryfjordan wrote:
| Linkedin lost on the CFAA claims, there were others that they
| did not lose.
| noizejoy wrote:
| > LinkedIn lost the HiQ case. Your GC claiming it's a win
| doesn't change that you lost, repeatedly, in multiple courts
| of law
|
| That would appear to be false, since after appeals, there was
| a settlement wich would seem to make it pretty clear that hiQ
| lost:
|
| https://www.natlawreview.com/article/hiq-and-linkedin-
| reach-...
| foolswisdom wrote:
| According to that wiki page, the courts eventually did rule
| that HiQ violated LinkedIn's terms of service, and a
| settlement agreement was reached.
| prepend wrote:
| > In any case, web scraping is a sort of gray area of the law.
|
| I don't think it's grey. It seems to be legal as the data are
| made freely available and the only grey part is that companies
| don't want this to happen and would rather charge and not have
| people scrape.
| JohnFen wrote:
| It is a gray area (in the US) in the sense that there is no
| clear consensus about it in the courts. There have been court
| rulings in both directions.
| SnowHill9902 wrote:
| So it's not gray, it's melange.
| hallqv wrote:
| Multiple court reaffirms in favor of scraping, including
| by the SC, seems more like verdant to me..
| prepend wrote:
| What rulings have been against it?
|
| You don't need consensus to allow something, you need
| consensus to be against something, otherwise it's allowed.
|
| This "scraping is Grey" sounds like FUD to me. Legally, you
| can scrape anything publicly available as long as you
| damage the server. You understand that google is just a
| giant web scraper right?
|
| And all the other search engines spidering the web. Do you
| think they are risking their business being in the "grey?"
| tyingq wrote:
| There does seem to be some distinction if you log into
| and scrape:
|
| _" Only three claims remained for the final order - the
| violation of the CAN-SPAM Act, violation of the CFAA and
| California Penal Code.
|
| The district court then granted summary judgment to
| Facebook on all three of the remaining Facebook claims.
| The district court awarded statutory damages of
| $3,031,350"_
|
| https://en.wikipedia.org/wiki/Facebook,_Inc._v._Power_Ven
| tur....
| hallqv wrote:
| What rulings are you referring to? Been reaffirmed that
| scraping LinkedIn is legal multiple times, even by Supreme
| Court. https://techcrunch.com/2022/04/18/web-scraping-
| legal-court/
| JohnFen wrote:
| I believe that decision was that web scraping doesn't
| violate the CFAA unless there are access controls (such
| as the need to log in) to get to it, but they
| specifically said that the ruling doesn't comment about
| other possible claims against it.
|
| That's why I think it's still a gray area. But I could be
| wrong -- I haven't been following this stuff all that
| closely.
| dheera wrote:
| > In any case, web scraping is a sort of gray area of the law.
|
| I feel like it's also only a matter of time before we have
| decentralized web scrapers that can consume data and assemble
| datasets and store the results in a decentralized fashion in a
| way that is completely non-enforceable. LinkedIn data would be
| aggregated in all sorts of interesting ways, and there would be
| literally no name you could sue, no address you could serve
| papers to, it would be a hundred thousand bots in 100 countries
| that collectively assembled the dataset and put it on some IPFS
| or torrent.
|
| If data is visible with human eyes, it's visible by
| decentralized bots, the only missing piece is the technical and
| financial complexity of the current state of decentralized
| compute.
| simonw wrote:
| > A company has to pay to have this page, so this certainly
| does not include all companies.
|
| I found a listing in there for my old startup derived from the
| LinkedIn page, and we never paid for that LinkedIn listing.
| oldtownroad wrote:
| I have lots of LinkedIn pages for various companies (alive and
| dead). I've never had to pay: while there's limits on page
| creation for free _accounts_ (which appear to be prevent abuse)
| there's no direct payment required to create a company page.
|
| I'm not sure if you're accidentally leaking a new strategy that
| LinkedIn are about to launch or if you're mistaken but given
| you're claiming to work for LinkedIn, probably worth correcting
| your comment either way.
| babblingfish wrote:
| Definitely not the latter. I am referring to the former
| point.
| visarga wrote:
| I searched for a dataset like this for a long time, trying to use
| it to augment named entity recognition tasks for documents. But
| now that GPT is on the market, this works out of the box. It's
| still useful as reference for validation.
| decide1000 wrote:
| Not sure why you need an account. Download it here:
|
| https://bigpicture-datasets-public.s3.us-west-2.amazonaws.co...
| ttul wrote:
| Oh boy, DMCA request incoming...
| sundarurfriend wrote:
| There's a comment below saying it's a 2.64GB CSV file, while
| gzip shows the uncompressed size of this one to be 1.97GB.
| medvezhenok wrote:
| Presumably as lead generation for their main upsell, which is
| the enriched version of the same data set :)
| andylynch wrote:
| How do you plan to identify or differentiate between legal
| entities? Eg a big company like your Uber example will often
| numerous subsidiaries, in many jurisdictions. Do you plan on
| including well-known identifiers like LEIs in your model?
| vrglvrglvrgl wrote:
| [dead]
| dang wrote:
| The submitted title was "World's largest open source company
| dataset", but (1) "world's largest" is linkbait and the article
| walks it back, (2) "open source" could be worded better per
| https://news.ycombinator.com/item?id=35979581, and (3) the only
| thing left in the title after taking those out would be "company
| dataset", which is too generic to be a good title.
|
| I've therefore replaced the title above with what appears to be
| an accurate description from
| https://news.ycombinator.com/item?id=35978156.
| mfrye0 wrote:
| Hey dang. That's fair.
|
| To be frank, we went back and forth on this, but in the end,
| thought the original title was ok. The only other large, "open
| source" dataset we could find was 9M. So after researching, we
| came to the conclusion that it sounded clickbaity, but was
| likely accurate.
|
| And yes on "open source". We fully intend for this to be "open
| source" in the full meaning of the word, but it seems we were
| moving too fast and missed adding the formal license.
| [deleted]
| data_maan wrote:
| I looked at the attributes they say the dataset has. Not too many
| (e.g. number of people, location). The really interesting ones,
| like who is doing business with whom, are missing.
| cdkmoose wrote:
| From the deeper dataset documentation, it looks like this free
| dataset is a field subset of their paid product.
| mikecoles wrote:
| I'd like to see parent company listed. How many brands fall
| under TTI or Unilever?
|
| For example, a hierarchy of tool brands:
| https://www.protoolreviews.com/power-tool-manufacturers-who-...
| NoboruWataya wrote:
| https://search.gleif.org/#/record/549300MKFYEKVRWML317
|
| (Not brands, but shows you subsidiaries.)
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