The Widow Didn’t Get the Pension

I’ve received the pension images from the Civil War pension file for Thomas Graves who served in Company B of the 42nd Missouri Infantry. Graves was survived by a widow, a woman who was born Sarah Newman in Rush County, Indiana, in the 1850s.

By the 1880s she was in the general area of Randolph County, Missouri. It was hoped that Graves’ pension file would provide some information on her. It was also hoped that she applied for a pension under Graves’ name even though there was no reference to her on the index card for Graves. Widow’s names are usually included on these cards–there is even a space for their application number and certificate number on them.

Her omission from the card was not a mistake. There is no widow’s application for Sarah in Thomas’ pension file. There is no communication at all from her in the pension file. Sarah did not receive a pension in Thomas’ name.

But there was still information on Sarah in the file. Which goes to show that even if the widow didn’t apply that there still may be details on her in her husband’s pension file

Stay tuned.


Getting Through the ThruLines(tm) at AncestryDNA: Part II

After some experimentation, I’ll keep using “ThruLines”(tm) while keeping the following things in mind:

  • DNA may not lie, but online trees do.
  • “ThruLines”(tm) is great for an initial sort of matches that have attached trees with shared ancestors. You still need to work on documenting the connection because some trees have errors, some trees are incomplete, some people are related more than once, and some people may not be related through the name in the tree because there is an error in their tree and you are related in a different way.
  • “ThruLines”(tm) uses the “Big Tree,” grown in the big swamp of submitted trees. Projected ancestors are often pulled from the biggest tree with the name. Parent-child relationships may be projected simply because that relationship appears most often in submitted trees. It is an automated process that automatically reproduces what is most popular. Aside from irritating the taters out of me philosophically, it’s not valid methodology.
  • “ThruLines”(tm) projects relationships that may be true, but that are not supported by DNA at all, only by other online trees. This was discussed in the “Siefert-Bieger” and “Dunaway” sections of my earlier post. Fourteen DNA matches who all descend from Nancy Dunaway do not in any sense “prove” George was her father. Valid paper evidence combined with DNA evidence from descendants of other known children of George matching children of Nancy at a cousinship level consistent with that relationship are what is needed. 100 million descendants of Nancy matching either other does not prove she’s George’s daughter.
  • Don’t add anything to your tree that you have not validated and analyzed yourself. If you don’t know what it means to validate and analyze information, don’t add that information to your tree.

I can’t change what does any more than I can change what my dead ancestors did. Individuals can either choose to use the tool or not–that’s a personal decision.

It has helped me to initially sort my matches with connected trees into how they are likely related. I was doing that anyway myself, manually. “ThruLines”(tm) speeds up that process. I can tell whether the information connecting me to the DNA match came from my tree or a submitted one. That helps me analyze as well.

Adding names to my tree solely because “ThruLines”(tm) said so? I’d never do that.

Learning about a tool helps you to effectively use or decide not to use it. Using it without learning about it just makes you likely create more trees growing in the tree swamp.

Find out more about my “ThruLines”(tm) webinar.



What’s Not Written Is What I Really Want to Know

Genealogists should use every record they can access to paint as accurate a picture of their ancestor’s life as possible.

But often it is not enough. We all want to know more.

The reality is that no matter how many pieces of paper are left behind there are details that are missing. The fight over the estate of an ancestor may explicitly be about money or property, but the reality is that there are often other underlying issues. Those issues are often ones that we will never know. Courts won’t litigate over hurt feelings because there was a slight between two brothers twenty years before their father died.

Courts will allow litigation over money or estate property. But, as many readers are aware, fights over property are not always completely about the property.

But sometimes fights over money are over money.

Which is why it is best to stick to the written facts. Our speculation about what’s unwritten may be incorrect.

And our research and conclusions should stick to details and facts for which we have evidence. Sometimes that’s enough to keep us busy.



ThruLines(TM) Trees are Suggestions


Your tree has not been changed with ThruLines(TM).

What’s white is from your tree. What’s gray is from other trees in the set of trees at ThruLines(TM) indicates the submitter of the tree from which the “is box” information has been obtained.

Those gray boxes are showing you the suggested connection between the DNA test kit you submitted and the DNA kit that matches yours.

The displayed relationship may not be correct. It is up to you to check it out with other records and information.

Thrulines(TM) is giving you a suggestion. It is not changing your tree. It’s up to you to do the research.


Working with ThruLines(TM) at AncestryDNA Webinar

We’re excited to offer an hour-long presentation on the new ThruLines(TM) functionality at AncestryDNA. This functionality makes it easier to organize and sort some of your DNA matches at AncestryDNA. The session was held on 17 March 2018 and includes:

  • understanding  where the information in the tree comes from–what’s yours and what’s someone else’s;
  • basics of evaluating the information in the tree;
  • responsibly using ThruLines(TM) information;
  • limitations of ThruLines(TM)
  • basics of how much DNA you typically share with certain cousins and relationship prediction;
  • do you really have the right genealogical connection with that DNA match;
  • using ThruLines(TM) to sort your matches with linked trees;
  • problem-solving and trouble shooting with ThruLines(TM).

Our focus is on:

  • being practical, hands-on, and easy-to-understand;
  • not getting overly excited about using ThruLines(TM);
  • employing sound genealogy methodology.


If you ordered this presentation and did not receive your download, email me at (include the email address used for purchase) so that I can remedy the situation.


Calculating An Age Range

Ages given in any document can easily be incorrect. That doesn’t mean they should not be analyzed.

The Civil War pension for Riley Rampley provides six ages for him at different times. I was curious just how consistent these ages were.

The six ages provided in the pension application are shown on the chart. The dates on which the ages were given range from 1886 through 1893.

Those ages were used to create a range of birth dates for each age. Then to see how consistent the birth date ranges were a timeline was created. The ages were not entirely consistent, but they were relatively close. Given that ages can easily be off by a year or two in any given record, this is not a surprise.

All of the ages given are consistent with a date of birth between July and October of 1835. That’s not a wide range of dates. Riley’s “known” date of birth of 25 August 1835 falls within that range.

Ages given for individuals will not always be consistent, but if you’ve got a person with varying ages such an analysis may be helpful in reaching a conclusion about when they probably were born.

And it may also help you to determine if one age is so far off from the others that it might have been a clear error.

The assumptions I made in this analysis were that:

  • Riley knew his age
  • Riley provided his age for all the documents in this study
  • Riley was always able to remember his age
It’s always a good idea to write down your assumptions when doing any analysis. You can’t know which assumptions may not be valid later if you’ve not listed them.



Which Great-grandchild Are You?

Regular readers know that I’m not a big fan of writing prompts, memes, or other activities that I loosely categorize as “busy work.” I’ve got a long list of things to write about as it is, don’t really follow the crowd in any way shape or form, and usually need to see a reason behind doing just about any activity.


I got to thinking about my great-grandparents and their great-grandchildren the other day. I realized that in my attempt to document the deceased, I really, out of personal preference, don’t document the living as much as other genealogists do.

In the case of two sets of great-grandparents, I know (off the top of my head) where I fit in the age order of all their great-grandchildren.

  • Fred (1893-1960) and Tena (Janssen) (1895-1986) Ufkes–I’m the oldest great-grandchild. In fact for nearly twenty years, my brother and I were their only great-grandchildren.
  • Charlie (1875-1948) and Fannie (Rampley) (1883-1965) Neill–I’m their third oldest great-grandchild. Two of my first cousins are the oldest great-grandchildren and then there’s me. At least I’m pretty certain.
  • George (1869-1934) and Ida (Sargent) (1874-1939) Trautvetter. I’m not certain where I fit into the age order of great-grandchildren.
  • Mimka (1881-1969) and Tjode (Goldenstein) 1882-1954) Habben. I’m even less certain where I fit into their list of great-grandchildren.
Do you know where you fit in your great-grandparents’ list?

A Post About a Triple Relationship

This 5th cousin 1 time removed and I share 111 cM of DNA over 4 segments. The screen shot in this image is from AncestryDNA but this post is not about any one specific DNA site. 111 cM of DNA is unusual for 5th cousins 1 time removed to share (the “Shared CentiMorgan Project” by Blaine Bettinger (cousins with this relationship  usually match between 0-79 cM with an average of 21 cM that are shared).

Of course the numbers at Bettinger’s site are based upon samples submitted by users. There will be exceptions.

This is an exception, but not in the way one might think.

This match and I are actually not just 5th cousins once removed. We are:

  • Third cousins once removed–both descending from my 2nd great-grandparents Riley and Nancy (Newman) Rampley.
  • Fourth cousins–both descending from  my 3rd great-grandparents Johann Christopher Janssen and Elska Tjarks Fecht.
  • Fifth cousins once removed–both descending from my 4th great-grandparents Eilt Gerdes Post and Christine Janssen.

DNA is not an even split from each ancestor, but it is worth noting that these three connections are somewhat evenly split through my tree. Riley and Nancy are my paternal grandfather’s grandparents. Johann and Elska are my maternal grandfather’s great-grandparents (through his mother) and Eilt and Christine are my maternal grandfather’s great-great-grandparents (through his father). I can’t just add the expected average amount of shared DNA for these relationships and conclude that is how much a cousin with these multiple relationships will share with me.

As we’ve mentioned before and as others have mentioned, just because I got half of each of my parents DNA does not mean that I got exactly one-fourth of each of my grandparents’ DNA. One rough analogy is to think that each person has $100 (in $1 bills) as their birthright and will pass $50 of that to their child. Each of my parents shuffled their $100 before passing half of it on to me. Yes, I have half of my dad’s money and half of my mom’s money, but depending upon how they shuffled it, I may not have exactly 1/4 of what my grandparents originally had.

Back to my 111 cM match.

It’s possible that the DNA we share does not even come from the Post family shown in the illustration. Our shared DNA could easily have come from the other two families that we share. There’s nothing to say that just because we share DNA and three sets of ancestors that we have to share DNA from all of them.





Responsibly Using “ThruLines(tm)” at AncestryDNA

To begin with, remember that the only DNA matches that appear in “ThruLines(tm)” at AncestryDNA are those who have trees attached to their results. Their tree may be hidden but they will still show and, in some cases, the names in their genealogical connection may be displayed on your “ThruLines(tm)” results page. One current advantage of using “ThruLines(tm)” as it is currently structured is that it allows you to see how you connect with individuals whose trees are hidden but are connected to their results.

Remember–you and someone else get “ThruLines(tm)” page together for an “ancestor” if you share DNA and if you have a shared name in your tree. There is no guarantee that you connect in the way AncestryDNA is suggesting via “ThruLines(tm).” It is possible that you and the match really connect through an ancestral line that is currently blank in the linked online tree for you or your match.

As mentioned in an earlier post, “ThruLines(tm)” puts information from other trees in gray when displaying it on your results tree for that set of shared matches.

There’s not a lot to responsibly using the “ThruLines(tm)” at AncestryDNA. The rules are fairly simple:

  • Do not add names to your tree just because “ThruLines(tm)” says it is a potential ancestor. Do actual research.
  • If you and your shared matches all descend from Susan and one of your matches thinks Susan’s father is Bubba, that does not mean you descend from Bubba. I don’t care if “ThruLines(tm)” suggests he is your ancestor or not. I do not care if they put Bubba at the top of the page or not.
  • Do not add names to your tree just because “ThruLines(tm)” says it is a potential ancestor. Look at original records.
  • Remember that you could be related to a person more than one way.
  • Do not add names to your tree just because “ThruLines(tm)” says it is a potential ancestor. See if it makes sense.
  • Standard genealogy methodology still applies. DNA is but one research tool. Don’t let it be your only one.
  • Do not add names to your tree just because “ThruLines(tm)” says it is a potential ancestor. Double check their work.
  • DNA will not catch all errors. If there are two grandsons of Edward Tinsley named James Tinsley, you’ll be  DNA match for them. It won’t tell you that you have the wrong father for James.
  • Do not add names to your tree just because “ThruLines(tm)” says it is a potential ancestor. Don’t.

Personally I’m using this tool to streamline a little filtering of my matches for further research. It’s a tool that makes it a little faster to do things I’ve been doing by hand already. It’s not the greatest thing since sliced bread.

And that’s about it.


Getting the Civil War Pension of David A. Newman


I’ve decided to get the Civil War pension of David A. Newman. The Kentucky native served in an Iowa unit (Company I 20th Regiment of the Iowa Infantry). The unit index card for him does not indicate his widow received a pension, so the amount of family detail may not be as much as I hope. However, it is still possible the file contains significant details.

David’s brother is my 3rd great-grandmother and I’m hoping his file at least provides a specific place of birth in Kentucky for him. The family’s migration in Indiana and points west is reasonably well document, but their time in Kentucky has not been studied in as much detail. It’s hoped his pension will help with that.

David had no known close relatives in his military unit and the brother from whom I descend did not live in Iowa. For those reasons, I’m not hoping for testimony from relatives in his application–but one never knows.