Domus house history project

Genealogy
1

Hi,

I wanted to share a new genealogy project of mine, for those who haven’t heard of it yet.

The idea was born while working on Gramps Web’s map view: I’m creating places of type “building” for each house where an ancestor lived. In combination with Gramps Web’s OpenHistoricalMap layer and historical map overlays, this allows me to build little geographical time machines for my ancestors’ home towns.

However, I always felt this house history research goes beyond genealogy and could profit from a public, open data repository where local historians could share their (documented) research results about building construction/demolition dates, owners, and inhabitants by period, as well as historical imagery.

At some point, I realized Wikidata already allows to publish all of this information, it’s just so general that it’s hard to know which data to add where, and there is no map view to actually browse the data.

That’s where Domus comes in: it’s an open data web platform for house history research that runs entirely in your browser, with all data stored openly in Wikidata. It’s hosted by the German association for computer genealogy (CompGen) and you can find it here:

It can be used for any house that exists, or has ever existed, world wide. Lots of buildings already show up on the map - mostly landmarks added to Wikidata. Please try it out, add a few buildings and give me feedback!

For those who are interested in the technical background, there is also a writeup here:

Currently, this project isn’t integrated with Gramps (Web) yet, but I’m planning to add Wikidata building pins to the Gramps Web map as ab optional layer. There is already a plugin for Webtrees: GitHub - hartenthaler/hh_external_places: webtrees module for enriching shared places with Wikidata, FactGrid, GOV and GeoNames information · GitHub

2

Hi,

Oh, great, it already covers some of my recent contributions on OpenHistoricalMap layer (e.g., some areas).

Note, maybe to also display at least the starting date for the build around details on the sidebar (sorry, I do not know the exact API key/value for that, it is an attribute on OpenHistoricalMap)?

I have an other sample, where this house from 1570 does not exist anymore (since 2014/2015) and the address is now pointing to a wrong location (related to a new construction very close). I guess this is wikidata issue as OpenHistoricalMap layer should be able to properly handle this type of data (address versus location or GPS stuff). e.g., the related node will display something like:

Attributs
end_date 	2014
historic 	yes
source:name 	5 rue du Lavoir
source:url 	https://www.archi-wiki.org/Adresse:5_rue_du_Lavoir_(Vendenheim)
start_date 	1570
wikidata 	Q15952483
wikipedia 	fr:Maison au 5, rue du Lavoir à Vendenheim

Anyway, they are very cosmetic issues. Also, it should occur outside big cities. Domus lets me quickly link and match wikidata id on OpenHistoralMap layer. Coordinates on wikidata are still fuzzy (or need a review), but the OpenHistoricalMap data will be more “complete”.

Note, active on an other project (above url, based on wikipedia engine) related to architecture, I losted some notices in the past. For me, it was related to something like the Google API supersed on many custom coordinates set by users (current limitations on this project). Like a validation roundtrip which forces to use Google’s addresses base. As google’s data around locations or altitudes are not always very smart, clever or even efficients, local expertise should not be erased at least for historical (and geographical) data, like house history.

An other technical challenge will be to properly handle addresses on a timeline : addresses might be different for one building. e.g., house number on a street will be different according to the date of the census or specific events (wars, sources, etc.) or models (states, countries, local customizations, etc.).

Thank you.

3

I also got mistakes (or false-positiv) with LiDAR Mapping for elevations and altitudes (sloped roofs, trees, etc.) but google’s database seems to sometimes use poor estimations, like if all constructions and buildings had the “same” base, starting point or earthwork value, like a slope gap.

Few meters errors can lead to a wrong address too or a wrong building.