Scoda company networks


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  • Some slide prompts to support a data framing investigation around corporate data.
  • When I buy something from a Shell petrol station, who do I enter into a transaction with?When Shell builds a new petrol station, who owns it?When Shell enters into a new extraction contract, who actually enters the contract?What, exactly, is this thing we thing of as the company “Shell”?
  • It’s a sprawl….
  • Can we make sense of the sprawl using company data?And if so, what sort of company data?
  • An accurate statement of the company name could be useful, and a company registration number in some jurisidiction.It could be even more useful to have a single “meta” or international namespace within which a unique identifier for every registered corporate entity could exist.
  • There may be other bits of information we can use to make sense of how a company evolves. When was it created, for example, or dissolved; and who are the directors?
  • It would also be useful if we could identify how companies are related to each other through various ownership relationships.(And if we could identify contractual relationships between members of the same corporate sprawl, that could be useful too…)
  • One possible source for some of this data – in a data format – is OpenCorporates.comThere are a couple of ways we can pull the company data out (and we can also get some directors information too…)
  • We can search for a company by name…
  • Or we can use something called a reconciliation API to get a confidence scored match on a company given its name…
  • We can look up data for a company given its corporate identifier. This information includes the registered address, formation date, and so on…
  • And more data from the identifier lookup… here are the directors, for example.
  • We can also start topull out information about subsidiaries of a company.
  • For the directors, we can search for them by name (putting the name in quotes looks for an exact match on the quoted string).
  • So that’s some of the data we have to hand. Now how we can make use of see to see how companies are linked?
  • Here are a few ideas…
  • Now it’s your turn….
  • Contact us…
  • If you aren’t a programmer, here’s way of getting the data into a tabular form you may be more comfortable with…
  • We can load the data in from an appropriately formed JSON URL
  • Select the block of data typical of the sort you want to map into a single row.
  • Here’s the result – nicely tabulated data.
  • You can also find identifiers from company names using the reconciliation API.
  • And if you want to pull down more data about a company using it’s company identifier, or more information about a director from an officers record, you can do…
  • Scoda company networks

    1. 1. Company Data
    2. 2. When we talk of a company such as “BP” or “Shell”, what do we actually mean?
    3. 3. What do we mean by “company data”?
    4. 4. Company … … name … number … registered address
    5. 5. Company … … formation date … dissolution date … directors
    6. 6. Company … … subsidiaries … shareholdings … “parents” … contracts
    7. 7. Company data ompanies/gb/04366849 Subsidiaries gb/04366849/network.json?depth=2
    8. 8. earch?q=%22royal%20dutch%20shell%22
    9. 9. al%20dutch%20shell%22
    10. 10.
    11. 11.
    12. 12.
    13. 13. OSEF%20MEINRAD%20ACKERMANN%22
    14. 14. So how might we identify how corporate entities be related or linked…?
    15. 15. … similarity of name? … ownership? (parent-child; common parent (siblings)? etc) … co-directors? … space (registered address)? … time (formation & dissolution dates)?
    16. 16. You’ve seen the pieces – so what’s the jigsaw…?
    17. 17.
    18. 18. Appendix - How to grab the data using OpenRefine