A gift to you from Twigs of Yore (and son)

If you are the type to rip the paper off with abandon, go ahead and click here. If you always read the card first, carry on.

My 10 year old son (who was last mentioned on this blog snapping shots with the Billion Graves app) wants to be a coder when he grows up. I keep telling him that, once he has the skills, he can build my perfect genealogy software. He seems to have accepted this fate. Either that, or he thinks I’m joking*.

So one day, when Mr 10 was looking for ideas to code, I asked him to work out how to build a web form with a button that would return different search strings depending on what was entered. I wanted such a thing because late last year I analysed historical birth notices in Trove and came up with conclusions about an effective search approach to use. In short, the best results were obtained by running a series of searches with the surname and one other relevant search term in close proximity.

Mr 10 quickly worked it out and obliged with the coding. We are excited to present to you the ….

Trove Helper

Merry Christmas!

 

* I am joking. Mostly. Partly. A little bit.

I made my Ancestry hints 28% better

I was feeling mildly annoyed at Ancestry for the 891 “Ancestry Member Tree Hints” cluttering up my hint list. So many people still had those hints, despite my efforts to stamp them out. I had a funny nagging feeling that perhaps there was something about this that I had forgotten. I took a wander though my tree preferences, and look what I found….

I didn’t have to see those tree hints at all.

This is what my hints summary looks like now:

Much better!

Ancestry hints: The good, the great, the horrid

My Ancestry tree has a lot of shaky leaf hints which I leave unpruned and untended. I usually only look at them when I am concentrating on an individual. The more I do look at them, the more I worry about new researchers who might suppose that the hints are more reliable than they actually are.

I was considerably surprised when Randy Seaver of the Geneamusings blog recently looked at his first 400 hints and concluded that over 85% of the hints were for the specific person cited. I wondered for a minute if it was ‘opposites day’. My children often tell me it is, it’s so hard to keep track. 85% correct just didn’t feel like my experience. Not at all.

Commenters on his post suggested that the quality of hints received depended on the amount of relevant information in the tree, particularly relationship information. They also suggested that the hints are often for information that is already in the tree.

I’m not quite up for a review of 400 hints, but I could manage a review of one person and by good fortune the first person I looked at was a great candidate for the exercise.

My ancestor Ellen Fearn, who emigrated from Derbyshire, England to Australia in 1852, has 15 unreviewed hints to her name. She has good basic information in the Ancestry tree, including relationship information:

• parent names
• birth date and place
• spouse name
• marriage date and place
• 1851 census
• birth of her children including dates and places
• death date and place
• burial date and place

She also has some missing items that I know are available in Ancestry. These are things that I would hope to see in hints:

• baptism
• 1841 census
• immigration records

I am going to classify each hint as bad if it relates to a different person, good if it relates to her but duplicates existing information, or great if it contributes a fact that is not already in the Ancestry tree, such as one of the three I’ve identified. Records that I’m not sure about I’ll classify as as maybe. I’ll ignore any Ancestry member tree hints (which is my usual practice) and exclude them from the tally.

The ratings only reflect if the hint is ‘accurate’ in that it relates to the right person, and if it adds anything new. I’m not looking at the quality of the sources themselves or whether images are available.

Hint	Rating
England, Select Marriages, 1538-1973	Good
Victoria, Australia, Assisted and Unassisted Passenger Lists, 1839-1923	Great
Victoria, Australia, Assisted and Unassisted Passenger Lists, 1839-1923	Great
England, Select Births and Christenings, 1538-1975	Great
Derbyshire, England, Select Church of England Parish Registers, 1538-1910	Great
England & Wales, Civil Registration Marriage Index, 1837-1915	Good
1871 England Census	Bad
1861 England Census	Bad
Bristol, England, Select Church of England Parish Registers, 1720-1933	Bad
1871 England Census	Bad
1881 England Census	Bad
1881 England Census	Bad
1841 England Census	Great
1881 England Census	Bad
1871 England Census	Bad

Overall, a third of the hints added new information. I was very pleased to see that all three of the known missing facts were included among the hints.

On the other hand, around half of the hints were just plain wrong. I could see why most of them came up – the people had similar names and, usually, were from Derbyshire. If I had accepted the hints I would have grafted together a franken-family. How horrid.

The final tally was:

Great	5
Good	2
Bad	8
Total	15

I don’t think that the ancestor I chose is an oddity. My gut feeling is that she had better than average results compared to the rest of my tree. A quick spot check of the hints for several of my great-grandparents supports this – I had “ignored” up to 80% of the hints that had been offered to me for some ancestors. Hinting may work better for some populations than for others.

My conclusion about Ancestry hints?

When they are good
they are very, very good
but when they are bad
they are horrid!

Look at those Ancestry shaky leaf hints by all means, but take care.

I feel happy with my current approach. I generally review hints only when I am concentrating on the person in question. This allows me to review them with a critical eye, as my mind is primed with what I know about the person and their family.

Twigs of Yore has a brand new look

I started this blog way back in July 2009. My personal family history research site of the same name went live in March of 2011, running on TNG software.

It was always my intention to match the look and feel of the two sites so that they would feel like one. With the arrival of a new version of the TNG software came a new site template that I liked the look of enough to spark off another attempt. It took quite a bit of tweaking of both the blog and the research component – but at last I’m getting close to what I had in mind.

I’m thrilled to unveil the new-look Twigs of Yore sister sites.

This blog…

And the research site…

A new software update on the research site also means there are new site features. I’m yet to discover them all myself!

Visualising DNA matches–FTDNA data

I decided to see what I could learn from my Family Tree DNA (FTDNA) match data when I looked at it using the visualisation tool, NodeXL. For my earlier discussion of this tool, see my post where I investigate Ancestry DNA data with it.

I match with around 960 individuals in FTDNA. There are around 10,000 ‘in common with’ matches between those people. Lets see how 10,000 connections between 960 people looks….

Like a colony of spiders, perhaps?

Each dot represents a person, each line represent a DNA connection between two individuals. There are two bunched up areas of dots where my matches have a lot of interconnections, but otherwise there is little structure to be seen. I tried using all the different layout algorithms available, but this is as good as it gets on the first pass.

Since my father has tested I can divide my DNA matches into two groups based on whether they also match him. I have called the two groups “Paternal” and “Maternal” – which possibly is not entirely accurate but will be close enough for my purposes here – and redrawn the chart with each group laid out separately.

There are clearly a lot of interconnection between my maternal and paternal matches. I’m surprised by the number of the interconnections, as I don’t descend from an endogamous population.

There are two critical facts about the ‘in common with’ relationships that are not shown in the chart:

• how close the relationship between my DNA matches is, and more importantly
• whether their relationships are anything to do with my family tree.

It may be possible to incorporate the second point using FTDNA data. It should be possible to incorporate both points using GEDMatch. I hope to attempt this in a future post.

This exercise suggests to me that it would be even more dangerous than I thought to rely on on ‘in common with’ data without also inspecting segment data.

Exploring my DIY Ancestry DNA circles

In my last post I created DIY Ancestry DNA circles. When I looked at the circles, one of them was of immediate interest to me as there were two names I recognised. I’ve coloured those people in green:

The green dots represent a pair of known-to-each-other cousins that I have been in correspondence with. Their common ancestor shares a family name also found in my tree. Given our predicted relationship, it’s likely that our common ancestor is just one or two generations beyond the outermost branches of our known trees. It feels so close we could almost touch it! Yet, we haven’t found that extra bit of evidence that will help us locate the common link.

When I planned this post I was going to say that I noticed something useful when I changed the labels (not displayed here for privacy) to the person who administered the account. Which I did. But since then, I have found another feature available in the free version of NodeXL that made me very happy – a function that will create new “edges” between people based on information in whatever column you choose.

The function can be found under the heading “Graph Metrics”:

That was exactly what I wanted to do, and it was very quick and easy. A few clicks, the spreadsheet had a bit of a think, and it was done.

This is what it looks now that I’ve added additional relationships between people whose DNA accounts are administered by the same person. I’ve set the new edges to red:

There’s a group of three people who match myself and one or both of the ‘green dots’ and whose accounts are administered by the same person (so are probably known relatives to each other).

I contacted the administrator for those accounts, explained what I had found, and asked if the three individuals had a common ancestor. She replied and gave me the name of an individual born in the early 1800s.

I would love to say that the connection between us all was immediately apparent, or that we now know where in Scotland or Ireland we should look, or even that I have further evidence that the surname of the ‘green dots’ common ancestor is the right one. Unfortunately that’s not the case… yet. It could have been though, and that’s why this sort of exercise is worth doing.

I haven’t tried to contact the other three individuals in this circle. That’s next on my list – if I can hold myself back from trying out all the other things I can think of to do with this tool!

DIY Ancestry DNA circles

Ancestry didn’t give me any DNA circles, so I made my own. If you want to join me in the DNA circle loop, then you will need AncestryDNA results and:

• The DNAGedcom client ($5 monthly subscription); and
• NodeXL (free basic version).

Use the DNAGedcom client to download your Ancestry matches and in-common-with (ICW) results as spreadsheets. You will need to click “Gather Matches” and “Gather ICW”. It’s the most convenient way to get the shared match information from Ancestry.

NodeXL is where the magic happens. It’s an Excel tool for social network analysis. I used NodeXL because it’s in Excel which I’m familiar with and it has all the facilities I need in the free version. I don’t know anything about social network analysis, and I didn’t need to in order to get the result I wanted. Follow the instructions on the website linked above to get started. It takes a little fiddling to get used to it, but in the familiar Excel interface it’s not as intimidating as it might at first seem.

Now the fun begins!

When you create a file using the template, you will see an extra ribbon, and an area for your charts to display. Those extra features won’t be there when you open Excel as normal, only when you open a spreadsheet from the template.

You will see several tabs. The most important for our purposes are “Vertices” and “Edges”. Think of “Vertices” as people, and “Edges” as relationships between people. The list of Match IDs goes into “vertices”, and the paired Match IDs in the ICW file goes into “edges”. As it’s Excel, you can cut and paste data into the sheets. I pasted twice on each sheet – the first time with just the match ID numbers in the first column (or two columns for Edges), then the rest of the columns into the “add your own columns here” section.

Click “Refresh Graph” to see a graph of your information. When you first drop match information in you will probably get a big mess of dots and crossing lines. There are options to fix that.

With a bit of fiddling, I came up with this:

 

Look! I’ve got circles!

Each dot represents a person, each line a DNA relationship between two people. When trying to interpret the information remember that that Ancestry has a cut off – it won’t show shared matches unless at least one of the people is a fourth cousin or closer to you. At least, that’s how I think it works. I’m not sure if they also have to be fourth cousins or closer to each other to show up. If you can enlighten me on exactly how it works, I’d be grateful.

The point is to remember that because of the cut-off there are likely to be other relationships between the dots that you can’t see. I assume that’s what’s happening with the fan shaped ‘circles’. I had 35 fourth cousins or closer at the time of making this chart and no circles or “New Ancestor Discoveries”.

To get distinct clusters I first used the “Group by cluster…” option on the toolbar.

The groups might still be mixed up at this stage. To separate the groups from each other, I clicked the little arrow dropdown to the right of “Circle” (above) and under “Layout options” I chose “Lay out each of the graph’s groups in it’s own box”.

For the layout I chose “Circle”. Because I wanted DNA circles. You could make a DNA spiral or a sine wave or a grid or a random layout or … but circles work nicely and they help with the circle-envy. This option is available both on the main NodeXL ribbon, and in the settings at the top of the graph area.

“Autofill columns” on the main ribbon lets you easily move information from your own columns into the columns that control the graph’s appearance. There are a lot of options to play with – size and colour of dots, thickness of lines all have potential. I set the size of each dot to the number of Shared cM with me. You can also label the dots using information on the sheet. The obvious label to use is the person’s name.

You need to refresh the graph by clicking “Show graph” when data changes on a worksheet. If you’re only changing display options, you can save the recalculation time by clicking “Lay Out Again”.

There’s a lot of fun to be had just playing with the options. I’ve also tried this with my FTDNA results. For those, I had a much busier chart. Different clustering algorithms had different effects, and the dynamic filter came in useful to clear away matches who sat in distracting “pile up regions” which could be seen as a dense collection of interlinked spots.

In my next post I’ll show you how I used my DIY Ancestry DNA circles to identify a new research lead.

Victorian Places

I’ve just come across the excellent Victorian Places website, which was produced by Monash University and the University of Queensland.

The site blurb says:

“This is a website containing the history of all the places in Victoria (Australia) that have now or once had a population over 200 at any time since the establishment of Victoria as a British colony.”

The entries I looked at were everything a genealogist hoping to be spoonfed basic contextual information about an ancestral place could desire. I think I’ll be making heavy use of the site.

Waiting for the mailman

OUR ILLUSTRATIONS. (1883, February 21). Illustrated Australian News (Melbourne, Vic. : 1876 - 1889), p.17. Retrieved April 1, 2016, from http://nla.gov.au/nla.news-article63186253.

Today I put in an order with the UK GRO for the death certificates of not one, but two of my five-times-great grandfathers.

I have at least a name (which may or may not be correct) for just 18 of my 128 five-times-great ancestors - and only one death certificate. The majority of that generation died in the early 1800s, so finding that two more of them managed to hang in there until English civil registration started is huge!

Best case scenario – I’ll have the certificates in 10 days. I’ll be rushing to the mailbox when I hear the postie!

A colour coded longevity chart

As I said in my recent Facebook post, I love a good colour coded chart!

Colour coded birthplaces charts have been doing the rounds, sparked off by J Paul Hawthorne. I confess I didn’t see his original post – I understand the trees doing the rounds are mostly based on an Excel template he provided. He certainly added a lot of colour to my recent genealogy reading!

I have been using various sorts of visual cues in my charts for a very long time. I’ll say it again – I love a good colour coded chart! The ability to add visual cues to charts is one of my must-have genealogy software features. Family Historian has exceptional capabilities in this respect but, and it’s a big but, you need to be comfortable with functions and formulas to get the most from it. Fortunately, I eat functions and formulas for breakfast.

On this occasion I was further inspired by Pauleen Cass, who took the colour coded chart in a different direction and added Health Inheritance information to her chart.

I’ve created a longevity diagram scheme with a different colour for each decade of life attained, 90+ being the top age bracket. I picked a colour-blind safe set of colours from the Colorbrewer website with a deep red/orange for childhood deaths through to a deep blue for those aged 90+. I’ve used grey for living/no age at death information.

I would really like to have fewer yellow boxes and more deep blue boxes on my tree! The two orange boxes aren’t so much of a concern for my own personal wellbeing – I survived having my children and I’m not likely to be lost at sea.

The nice thing about having a diagram scheme set up within your genealogy software is that you can then use it to look at other parts of your tree with no fuss.

My ancestors Robert Mack and Jane Mercer lost too many young children. Looking at the three grey boxes below – Eliza would have been no more than 15 and the second Robert no more than 10. I have information that Alexander at least lived to early adulthood, but I don’t know what became of him after that. My ancestor Catherine with the palest of blue boxes looks suddenly quite robust compared to the rest of her family.

Although Family Historian diagram schemes involve some setting up, they can be easily shared among users. Download the scheme, double click to install. Easy.

I’m thinking of giving this diagram scheme a few more tweaks – perhaps to use age at death estimates so more of those I-know-they-must-be-red boxes will show as such, and contributing it to the Family Historian User Group website.

Can you do this grade five history homework?

Recently my grade 5 son was given this homework task:

History - migration

During history, you have been examining migration and some of the reasons people migrate to different countries. Your task is to write a migration story about a member of your family, alternatively research a migration story.

Some things to include:

• Name of person that migrated
• Date of migration
• Why they migrated
• How they migrated (e.g. by boat)
• Their thoughts and feelings about adapting to a new country
• Any other relevant information

I'm not sure how a ten year old would manage this homework if their family were not relatively recent immigrants. In my son's case, he had a huge advantage since I've been researching the family for the past 25 years. At last, a reason for him to look at some of the research that I have been most excited about! I think he was quite perplexed to see how excited Mummy was about his homework.

I drip fed him source documents over a few days and talked with him about what they meant. Passenger lists, newspaper articles and of course the wonderful letter from John himself that I found at the National Library.

My son’s answer, below (included with his permission), was entirely his own words.

History migration John Allsop

John Allsop migrated to Australia with his wife and children. The boat left England on the 12^th of March 1852. On the Chowringhee there were 319 passengers. Throwout the journey 95 people got cholera 98 people had fevers and 39 other cases even the doctor got sick and they were worried he was going to die. The ship had a total of 17 deaths. On the ship there were 9 babies been born including a new son for Jonh and Ellen. They arrived on 5^th July 1852.

Johns family came as Assisted Immigrants because in England they were poor and the government needed more workers for Victoria. When he got there it was the gold rush but he did not run away to get gold. In Australia he was much happyer because he got more money and he had his own house he now had enough money he could save it and sent it to his mother.

Trove Tuesday: The Gallant Sorter of the G.P.O.

The Gallant Sorter of the G.P.O
5FT. 9IN., and Wore a Mo

A young girl named Jane Davis
about 20, proceeded against an ex-
public servant named John McMahon
for the maintenance of her illegitimate
child.

…

Excerpt from: The Gallant Sorter of the G.P.O. (1895, August 9). North Melbourne Gazette (Vic. : 1894 - 1901), p. 2. Retrieved February 5, 2016, from http://nla.gov.au/nla.news-article107123768.
Note: The full article is much longer than the excerpts included with this post. Follow the link above if you wish to read it.

This article had my attention for two reasons. Firstly, I believe John McMahon – the ‘gallant’ mo-wearing post office employee – was my grandmother’s uncle. That would make the illegitimate child my first cousin twice removed.

Then there’s the “Mo” itself.

Here in Australia, “mo” is a slang term for a moustache. I was surprised to see the term in print as early as 9 August 1895.

I wondered how long the term had actually been around for. The free online dictionaries I could find weren’t very helpful. The offline dictionary on my bookshelf included the term, but gave no start date. Then I thought to check if the National Library of Australia’s electronic resources included a more complete Oxford Dictionary than the free online version.

Success! The Oxford English dictionary gives the earliest use as…
… drumroll … 4 August 1894.

One year earlier than my find, almost to the day. So close! It would have been fun to find an earlier usage.

But back to John McMahon. The mocking reference to his mo in the headline came about because having dumped the pregnant girl, it was claimed that he then showed her a letter he intended to send in reponse to a matrimonial advertisement.

…
He had shown witness a letter
which he intended to send to a girl in
answer to a matrimonial advertise-
ment in the Age. She identified the
letter.

Mr. Daly read the letter, which was
to the following purport :—
Letter Carrier's Room, G.P.O.
13th December, 1894.
“Dear Nellie,—I take great pleasure
in answering your advertisement in
to day's Age. I am a letter sorter at
the G. P. O. at an annual salary of £158
and will receive my annual increment
of £12 shortly.
“I am 5ft 9¼in in height and scale
11 stone 2lbs, and a good all round
athlete. (Dr. Lloyd : yes, a good all
round man—Laughter). I am con-
sidered good looking, of dark complex-
ion and I wear a moustache”.—(Loud
laughter).
…

I have found and obtained the birth certificate for the child but don’t yet know what became of her or her mother.

Rearranging a genealogy jigsaw

I’ve been having a lot of fun fitting together the puzzle pieces of the Allsop family of Tissington, Derbyshire, England. In doing so, I’ve learnt more about the capabilities of my genealogy software package, Family Historian.

Partial transcripts and images of the parish records for Tissington are on FamilySearch. I’ve gone through these, starting with the transcriptions and looked at every relevant image (plus a few) to make any corrections (not many) and add in the information not included in the transcripts (quite a lot) in a spreadsheet. I’ve also found census entries for anyone called Allsop who lived in or was born in Tissington and done the same thing plus added in a few bits and pieces from other sources.

Now the fun begins!

I used a plugin to load the spreadsheets into my Family Historian software giving me a file with lots of mini trees - and lots of duplicated people.

I started out by setting up the columns in the individual record view to be sorted by given name then estimated birth date (Family Historian has functions to calculate that) – and a columns relating to birth, baptism, marriage, census, death and burial. For the census I set the display up to show the place, if I had a census entry for the person, or a strike through if the census was before their earliest possible birth date, or after their last possible death date.

Clicking the image below should take you to a full size view.



Some duplicates were easy to spot, such as following a family group through the census. I merged any that appeared clear cut. I was left with a few more substantial trees, and quite a lot of stray small family groups and individuals. It was a good start, but time for a new approach if I wanted to get any further.

This is when I tried something with my software that I haven’t done before. I knew that there was an option to insert an additional tree into a chart, but I hadn’t ever made use of it as I had thought of it as mostly a presentation feature. It occured to me that I could use it as an analysis feature.

To get started I ran the standard “All Facts” query and sorted it by date. Starting with the earliest fact – the baptism of Richard Alsop, son of John and Jane Alsop on 15 May 1673 – I created an all-relatives chart. I then went down the list of facts and inserted an extra ‘tree’ for each fact not yet represented on the main chart.

Many of the ‘trees’ consisted of one or two names only. I could drag and drop the trees around, so I placed each ‘tree’ near to where I thought it might belong. I could also insert or draw shapes and text on the chart all from within Family Historian. Below is a marked up portion of the multiple tree chart. The coloured loops show the people from different ‘trees’ who I think may be the same person.



You can see that I had five separate records in the late 1660s and early 1700s containing a Robert Allsop.

• Baptism of Robert son of John and Jane in 1677
• Marriage to Mary Wragg 1703
• Birth of a son Thomas to Robert and Mary in 1704
• Burial of Mary, wife of Robert, in 1728 (no age given), and
• Burial of Robert in 1729 (no age or relationships given).

It didn’t seem so obvious when I was looking at a long list of names and dates as it does, to me, on the chart.

I also think that the Thomas who married Elizabeth Goodwin in the chart above may be the same person who married Martha, a few years later. The Thomas who married Martha is most likely my 6x great-grandfather, so I’m quite interested to know who his parents were.

Blowe is a zoomed out view of the multiple tree chart. I counted 27 separate trees within the full version (which was very wide!), most of which I will be able to combine together now that I’ve seen how the pieces fit. A few individuals who I am not (yet?) able to fit in to the main family tree are sitting to the side.



For now I consider this little exercise to be an experiment and a learning experience. I’m very happy with how it’s working and I’m having a lot of fun. Sliding the different ‘trees’ into place really does feel like putting together a jigsaw puzzle.