Ask the study

Who lived in Bates County, Missouri, between 1880 and 1900? 39 people
Every record and fact that puts someone in the county, its towns or its townships in those years.
Who crossed the Atlantic? 61 emigrants
An emigration, a passenger list or a naturalisation, or born in Europe and died in the Americas.
Who was born in Switzerland and died in the United States? 32 people
A birth or baptism anywhere in Switzerland, and a death or burial anywhere in the United States.
Which Hegnauers served in the Civil War? 4 soldiers
A military record of the American Civil War, 1861–65.
Who lived past ninety? 38 people
Both ends of the life dated, ninety years or more apart. Oldest first.
The Hegnauer women, and the names they married into 292 women
Women born Hegnauer who married, each with her husbands’ surnames.
Which Swiss villages were home to the most Hegnauers? 162 places
Towns and parishes in Switzerland, by the number of people the evidence puts there.
What did war do to the family? 19 stories
The finds about soldiers, battles, drafts and pensions, from Sempach to the Civil War.
Which records name a Hegnauer nobody has identified yet? 538 records
Records the study has not yet linked to anyone. Somebody’s great-grandmother, very likely.

9 more questions

Everyone born or baptised in Igis 90 people
The village in the Rhine valley of Graubünden that the Missouri family left in 1856.
Twins 6 twins
Born or baptised on the same day as a brother or sister.
The most common first names 25 names
The first of each person’s given names.
Who appears in the most records? 25 people
The twenty-five people with the most records linked to them.
Who was in the papers most? 20 people
The twenty people named in the most newspaper items.
Who had eight children or more? 46 parents
Eight or more children in the study.
Where were the Hegnauers in 1900? 16 places
The places the evidence puts anyone in that year: the census, and every other record of it.
What happened in the 1850s? 12 stories
The decade of hunger in Graubünden, and of the crossing.
The oldest records of the name 194 records
Everything before 1600, earliest first.

The questions need JavaScript to answer: the database is fetched and questioned in your browser. Without it, everyone is in the A–Z, every record is in the archive, and the whole database is a download (SQLite, 11.6 MB).

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Named Men or women Family line Who were Age at death

With a picture a story a written life

And

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For the curious: ask in SQL

The database is in your browser, and it is your own copy: change it or break it and no harm is done (“Start afresh” gives you a new one). It is SQLite, with one addition, fold(text), which lowers the case and drops the accents, as the name searches do; the tables are described below. Up to 1,000 rows are shown.

Your query

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The tables

Two parts: the core (the people, their facts, families and places, the lines, themes and finds), 1.1 MB, comes first; the archive (the records, newspaper items, sources and written lives), 1.2 MB, follows when a question needs it. The download on the data page is both in one file.

people

2,097 rows in the core

Everyone in the study who has died, one row each. Living people are not in the database at all.

id text: The permanent H-number (H0001)
name text: The name the study uses
given_names text: Given names
surname text: Surname at birth, as the study spells it
suffix text: Jr., Sr. and the like
sex text: M, F or U (not known)
born text: Birth (or baptism) date as the study writes it: "8 Dec 1819", "about 1866", "before 1887"
born_year integer: The year of that date
birth_event text: Birth, or Baptism where that is the earliest record
birth_place text: Where, in the study’s standard form
birth_place_id text: The same place → places.id
died text: Death (or burial) date as the study writes it
died_year integer: The year of that date
death_event text: Death, or Burial
death_place text: Where
death_place_id text: The same place → places.id
lifespan text: The short form the site shows ("1819–aft. 1890")
age_at_death integer: In whole years, where both ends are dated (a "before" or "after" date gives none)
earliest_year integer: The first year the evidence puts them in: birth, else their earliest fact or record
latest_year integer: The last: death, else their latest fact or record
century integer: The century they were born in (19 for the 1800s)
line_id text: Their family line, where the study has placed them → lines.id
known_for text: Who they were, in a few words: "Union soldier, 1861–63", "Lived to 96"
sketch text: Their life in a sentence
has_biography integer: 1 if the study has written up this life in full, else 0
has_picture integer: 1 if their page has a picture: a document of theirs, or the place they came from, else 0
picture text: A small version of that picture (its address on this site)
picture_alt text: What the picture shows
picture_kind text: document (their own record) or place
stories integer: How many of the finds are about them
records integer: How many records are linked to them
newspapers integer: How many newspaper items name them
sort_name text: Surname then given names, for sorting
wikitree_id text: WikiTree ID, where there is one
familysearch_id text: FamilySearch Family Tree ID
findagrave_id text: Find a Grave memorial number
url text: Their page on this site

Try: SELECT name, lifespan, known_for FROM people WHERE age_at_death >= 95 ORDER BY age_at_death DESC

names

5,689 rows in the core

Every name a person goes by: the study’s own, the other forms it records, and each spelling a record linked to them uses.

person_id text: Whose name → people.id
name text: The name
kind text: name (the study’s), also known as, or as written (in a record)
folded text: The name in lower case without accents, for searching
records integer: For "as written": how many of their records spell it so

Try: SELECT name, COUNT(*) AS people FROM names WHERE kind = 'as written' GROUP BY name ORDER BY people DESC

events

3,237 rows in the core

The facts of each life as the study concludes them, each graded by its evidence.

id integer: A number for the fact (it may change between exports)
person_id text: Whose fact → people.id
type text: birth, baptism, marriage, residence, occupation, military, immigration, death, burial…
label text: The fact as the person’s page names it
date text: As the study writes it
year integer: The year of that date
place text: Where
place_id text: The same place → places.id
grade text: proven, probable, possible, or not graded (no record linked to the fact yet)
spouse_id text: For a marriage: the spouse, where they are in the study → people.id
note text: The study’s note on the fact

Try: SELECT p.name, e.date, e.note FROM events e JOIN people p ON p.id = e.person_id WHERE e.type = 'occupation'

relationships

4,518 rows in the core

Parents, children and spouses. Each link is here twice, once from each side.

person_id text: The person → people.id
relative_id text: Their relative → people.id
relation text: What the relative is to the person: parent, child or spouse
grade text: For a parent or child: how sure the study is of the link (proven, probable, possible)
marriage_date text: For a spouse: the marriage, as the study writes it
marriage_year integer: The year of the marriage
marriage_place text: Where they married
marriage_place_id text: The same place → places.id

Try: SELECT p.name, COUNT(*) AS children FROM relationships r JOIN people p ON p.id = r.person_id WHERE r.relation = 'child' GROUP BY p.id ORDER BY children DESC LIMIT 10

places

991 rows in the core

Every place in the study, from country to parish, each inside the one above it: Rockville in Bates County, in Missouri, in the United States.

id text: The place’s key (its address on this site, where it has a page)
name text: In full, in the study’s standard form
short text: The first part of the name
kind text: country, state or canton, county or district, or town or parish
parent_id text: The place it lies in → places.id
same_as text: Where the gazetteer lists the same place twice: the entry the explorer uses → places.id
depth integer: 1 for a country, 2 for a state or canton, and so on down
country text: The country
region text: The state, canton or province
lat real: Latitude, where the place is pinned
lon real: Longitude
precision text: What the pin marks: a place, an area, a region or a country
people integer: How many people the evidence puts here or in a place inside it
records integer: How many records were made here or in a place inside it
earliest_year integer: The first year the evidence puts anyone here
latest_year integer: The last
other_spellings text: The place as the records spell it, where that differs, separated by semicolons
in_gazetteer integer: 1 if the place is in the study’s gazetteer (0 for a county or canton added only to hold the places in it), else 0
url text: Its page on this site, where it has one

Try: SELECT name, people, records FROM places WHERE kind = 'town or parish' AND country = 'Switzerland' ORDER BY people DESC LIMIT 20

place_within

3,412 rows in the core

Each place paired with every place it lies within, and itself, so that one join finds everything in Missouri or in Graubünden.

place_id text: The place → places.id
within_id text: A place it lies within (or the place itself) → places.id
steps integer: 0 for the place itself, 1 for the place just above, and so on

Try: SELECT p.name FROM places p JOIN place_within w ON w.place_id = p.id WHERE w.within_id = 'graubunden-switzerland'

person_places

4,660 rows in the core

Where and when the evidence puts each person: their own facts, and the records linked to them (proven or probable) in which they took part, as the one baptised, married or buried, a parent at a baptism, or one of a census household. Built from events and records, for the "who lived where" questions.

person_id text: Who → people.id
place_id text: Where (empty when the evidence gives only a date) → places.id
year integer: When
kind text: born, married, died, or lived (any other evidence of them there)
event text: What puts them there: the fact’s type or the record’s event
from_record text: The record, when the evidence is a record → records.id
from_event integer: The fact, when the evidence is one of their facts → events.id

Try: SELECT DISTINCT p.name FROM person_places pp JOIN people p ON p.id = pp.person_id JOIN place_within w ON w.place_id = pp.place_id WHERE w.within_id = 'bates-missouri-united-states' AND pp.year BETWEEN 1880 AND 1900

lines

22 rows in the core

The family lines: the clusters of Hegnauers the study has traced together, by where they lived. People not yet fitted to a family have no line.

id text: The line’s key (its address on this site)
name text: Its name
code text: The study’s short code for it
people integer: How many people in it have died (living members are not counted here)
year_from integer: The first year of the line’s records
year_to integer: The last
intro text: The line in a sentence or two
url text: Its page on this site

Try: SELECT name, people, year_from, year_to FROM lines ORDER BY people DESC

themes

23 rows in the core

What kind of life a person had, as far as the records say: emigrant, soldier, farmer, lived past ninety…

id text: The theme’s key (emigrant, civil-war, long-lived…)
label text: Its name
description text: What puts someone in it
people integer: How many people have it

Try: SELECT label, people FROM themes ORDER BY people DESC

person_themes

1,150 rows in the core

Which themes each person has.

person_id text: Who → people.id
theme_id text: Which theme → themes.id

Try: SELECT p.name, p.lifespan FROM person_themes t JOIN people p ON p.id = t.person_id WHERE t.theme_id = 'twins'

finds

197 rows in the core

The finds: the stories in the records, each retold in a few lines, with the record, newspaper item or research it comes from.

id text: The find’s key (its address on /stories/finds/)
title text: What happened, in a line
teaser text: The story in a sentence
story text: The short retelling
kind text: accident, court, war, travel, wedding, death, office, business, land, church-school, social…
kind_label text: The kind in words
date text: When, as the study writes it
year integer: The year
place text: Where
place_id text: The same place, where it is in the gazetteer → places.id
line_id text: The family line of the person it is mainly about → lines.id
score integer: How much of a story it is, 3 to 5
source text: Where it comes from
source_type text: record, newspaper, article (the study’s research) or person (a biography)
source_url text: That source’s page
url text: The find on this site

Try: SELECT year, title FROM finds WHERE kind = 'war' ORDER BY year

find_people

619 rows in the core

The people each find is about, the main one first.

find_id text: The find → finds.id
person_id text: A person in it → people.id
position integer: 1 for the person it is mainly about

Try: SELECT p.name, COUNT(*) AS stories FROM find_people fp JOIN people p ON p.id = fp.person_id GROUP BY p.id ORDER BY stories DESC LIMIT 10

about

6 rows in the core

About this database: when it was made, from what, and the terms of use.

key text: What
value text: The value

Try: SELECT * FROM about

records

6,594 rows in the archive

Every record in the archive: one entry in a register, index, census or newspaper, with the name as the clerk wrote it. None is about a living person.

id text: The permanent O-number (O01533)
date text: As the record gives it
year integer: The year
sort_date text: The date as YYYY-MM-DD, for sorting (00 where the month or day is not known)
name_as_written text: The name exactly as written
name_folded text: The same in lower case without accents, for searching
given text: Given names as written
surname text: Surname as written: one of the name’s many spellings
event text: Baptism, burial, census, obituary…
category text: The archive’s grouping: Birth and baptism, Marriage, Death and burial, Census and residence, Military, Migration, Newspapers, Other
place_as_written text: The place as the record gives it
place text: The same place in the study’s standard form
place_id text: The same place → places.id
role text: The part the named person plays: the one baptised (principal), a parent, a witness…
about_name text: For a parent’s or witness’s entry: whose event it is
about_event text: And which event
source_id text: Where it was found → sources.id
collection text: The collection or database
person_id text: The person it is linked to, if any → people.id
link_grade text: How sure the study is that it is about that person: proven, probable, possible, or not linked
newspaper_id text: For a newspaper record: the item it is part of → newspapers.id
citation text: The source citation
notes text: The study’s notes on it
added text: When it joined the study (YYYY-MM-DD)
original_url text: The original, where it is online
url text: Its page on this site

Try: SELECT surname, COUNT(*) AS records FROM records GROUP BY surname ORDER BY records DESC LIMIT 20

record_people

8,521 rows in the archive

The people each record concerns: the person it is linked to, and anyone whose page cites it as a source.

record_id text: The record → records.id
person_id text: The person → people.id
how text: linked (the record is about them; see records.link_grade) or cited (their page cites it)

Try: SELECT p.name, COUNT(*) AS records FROM record_people rp JOIN people p ON p.id = rp.person_id GROUP BY p.id ORDER BY records DESC LIMIT 10

event_records

4,691 rows in the archive

The records behind each fact.

event_id integer: The fact → events.id
record_id text: A record it rests on → records.id

Try: SELECT e.type, e.date, r.collection FROM event_records er JOIN events e ON e.id = er.event_id JOIN records r ON r.id = er.record_id WHERE e.person_id = 'H0001'

newspapers

370 rows in the archive

The newspaper items: every article the study has found that names a Hegnauer, with its transcription or abstract.

id text: The item’s key (its address on this site)
headline text: The headline, or what the item is about
paper text: The newspaper
paper_place text: Where it was published
date text: The issue
iso_date text: The same as YYYY-MM-DD
year integer: The year
page text: The page
kind text: Social news, Deaths and obituaries, Politics and elections, Courts and estates…
place text: Where the news is from
place_id text: The same place → places.id
has_text integer: 1 if the item is transcribed or abstracted in full, else 0
text text: The transcription (before 1929) or abstract, as plain text
original_url text: The page at Newspapers.com
url text: The item on this site

Try: SELECT date, paper, headline FROM newspapers WHERE text LIKE '%runaway%'

newspaper_people

712 rows in the archive

The people each newspaper item names, as it names them.

newspaper_id text: The item → newspapers.id
person_id text: The person, where the study has identified them → people.id
as_written text: The name as printed
role text: Their part in the news: hotel guest, candidate, bride…
record_id text: The record that ties them to the item → records.id
grade text: How sure the study is it is them: proven, probable, possible, or not linked

Try: SELECT n.date, n.headline, np.as_written FROM newspaper_people np JOIN newspapers n ON n.id = np.newspaper_id WHERE np.person_id IS NULL

sources

10 rows in the archive

Where the records were found: the archives and websites.

id text: The source’s key
name text: Its name
what text: What it holds
records integer: How many records in the archive come from it
year_from integer: The earliest of them
year_to integer: The latest
url text: Its website

Try: SELECT name, records, year_from, year_to FROM sources ORDER BY records DESC

collections

313 rows in the archive

The collections and databases within each source.

source_id text: The source → sources.id
name text: The collection
records integer: How many records in the archive come from it
year_from integer: The earliest
year_to integer: The latest

Try: SELECT name, records FROM collections ORDER BY records DESC LIMIT 15

biographies

348 rows in the archive

The written lives, as plain text, for the people the study has written up in full.

person_id text: Whose life → people.id
text text: The biography, without its footnotes
words integer: How long it is

Try: SELECT p.name FROM biographies b JOIN people p ON p.id = b.person_id WHERE b.text LIKE '%cholera%'

Questions to start with