FactGrid talk:Career Statements

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Basic ontology of FactGrid Property:P165 career statements

  1. Career statement — Baker, lieutenant
  2. Career statement with qualifying attributes — Court-Baker, lieutenant of the French Army
  3. Career statement noting a specific position — Bishop of Canterbury, President of the University of Erfurt
  • We use P3 statements from bottom to top to gain a basic ontology
  • We put all career statements on a single Property Property:P165 - as precise as we want to (and get the less nuanced options with the wdt:P2/wdt:P3* query.
  • We put P1007 links on all the items
  • We generate some more properties for specific statistics (like "required academic/professional education", "tariff wage" etc.)

Katrin Moeller's OhdAB Database on FactGrid

Problem of the three properties: P165: Career Statements, P164: Positions, P166: specific positions

Wikidata has basically two properties: Occupation (P106) and Position held (P39]).

The FactGrid equivalents are Career statement Property:P165 and Office held Property:P164. Our "Career statement" property is more inclusive, allowing all the statements one might find on a personal record (such as retired, pensioner, widow, candidate of theology).

The additional Property:P166 came into use in order to state specific job descriptions on items such as Pastorate Altenbergen. It might make sense to fuse this Property into Property:P165.

Could we go a whole step further and reduce everything to Career statement Property:P165 statements? Not that easily if we still want to be able to run a simple count on all the shoemakers of a town. We might have to cleanse our career statements for that purpose of all statements that refer to specific positions in regiments etc.

Statistics

It is not yet possible to run statistics on our career statements. At the moment we will get widely scattered fields of often extremely specific statements. Pies or bubble graphs will need succinct reductions to work with. A first pattern could be:

  1. Church
  2. Military
  3. Law, government and administration
  4. Crafts
  5. Commerce
  6. Agriculture
  7. Education and academia
  8. Artists and writers
  9. Servants
  10. Prostitutes and mistresses
  11. Landed property
  12. Unemployed / sick people / students/

We can run several patterns side by side - all they need is Properties and the respective statements on our career statements.

Wives are a difficult category - in a way they are a group of their own, in a way they belong to the trade of their husbands up to thee "professor's wife" who is eager to be noted in this condition.

Check

Verschiedene Statistiken

Statistik des Produktionsprozesses

  • Landwirtschaft
  • Rohstoffförderung
  • Handwerkliche Verarbeitung
  • Industrielle Verarbeitung
  • Handel
  • Firmenverwaltung
  • Öffentliche Verwaltung
  • Firmenmanagement
  • Öffentliche Amtsführung
  • Bildung
  • Wissenschaft

Wirtschaftszweige nach Rohstoffen

Tierverwendung

Reichweite

  • Global
  • International
  • National
  • Regional
  • Urban
  • Dörflich

Ausbildungshöhe

  • ohne Ausbildung (Tagelöhner)
  • Familiär / Tradition (Landwirtschaft)
  • Lehre / Meister
  • Praktisches Bildungssystem (Fachschulen)
  • Höheres Bildungssystem (Universitäten)