I’m excited to share some enhancements to my Research Like a Pro with DNA genealogy research log template in Airtable. You can access the new templates here:
RLP with DNA Research Log 4.1 (2025)
RLP with DNA Research Log 4.1 (2025) – Blank
The blank base does not include example data that you need to remove before using. If this is your first time using my Airtable templates, I recommend practicing with the base that has example data so you can see what it’s supposed to look like.
Below is an overview of the changes made. To see a complete list, go to my change log here: RLP with DNA Airtable Template 2025 Updates.
I used Google Gemini (AI) to create and outline and first draft of this post, based on my changes log in Google Docs.
1. Z-Score Added to DNA Match Details Table
One of the key additions is the inclusion of the z-score in the DNA Match Details table. This statistical measure helps you assess the significance of the shared DNA between two individuals, providing valuable context for your analysis. By incorporating the z-score, you can quickly identify matches that warrant further investigation.
The z-score is a statistical measure that indicates how many standard deviations a particular data point is from the mean. In the context of DNA matches, it shows how far the shared DNA between two individuals deviates from the average shared DNA for a given relationship.
Previously, the template only provided a checkbox for whether the shared DNA fell within the expected range and another checkbox for whether it was within one standard deviation above or below the mean. This approach only gave a general idea of how typical the shared DNA was.
By incorporating the z-score, the template now offers a more precise understanding of the shared DNA’s proximity to the mean. A z-score between -1 and 1 signifies that the shared DNA is within one standard deviation of the mean, which means the amount of DNA matches the relationship you found between the test-takers. A z-score of 3, for example, means the shared DNA is three standard deviations above the mean, indicating it’s much more DNA shared than expected, and warrants further investigation.
2. More Field Descriptions
I’ve also expanded the descriptions within the template to offer clearer guidance and instructions. These descriptions will make it easier for both new and experienced users to navigate the research log and utilize its features effectively. To view the description of a table or field, hover over or click the (i) with a circle around it to the right of the field title.
3. Location Table Jurisdictions
The Locations table now uses formulas to automatically separate the location details into the correct jurisdictions (town, county, state, and country). To make this work correctly, you need to enter the location details in a specific format, starting with the smallest locality and separating each one with a comma.
For example, if you want to add the location “Quaker, Vermillion, Indiana, United States,” you would enter it exactly like that, with commas separating each part. If you don’t know one of the localities, you can leave it blank, but you still need to include the comma to maintain the correct format, i.e. ” , Vermillion, Indiana, United States,” or “, , Indiana, United States.”
4. Research Log and Timeline Automation
Finally, I’ve added an automation to the Research Log and Timeline that automatically creates a row in the Timeline from the Research Log. The automation between the Timeline and Research Log tables allows you to automatically create a Timeline entry from a Research Log entry by checking a box in the research log.
- Trigger: The automation is triggered when a record in the Research Log table is updated, specifically when the “Add to Timeline” checkbox field is checked.
- Action: When triggered, the automation creates a new record in the Timeline table.
- Field Mapping: The new Timeline record’s fields are populated with data from the corresponding Research Log record. Specific fields in the Timeline table are mapped to fields in the Research Log table, ensuring that relevant information is transferred.
It’s crucial to fill out all the necessary fields in the Research Log row before checking the “Add to Timeline” box. The automation only copies the data once, when the box is checked. After checking the box, it may take a few seconds for the new Timeline record to appear. The Event Type field in the Timeline is a multiple-select field, and the automation will select “Record” by default. You can then manually change this to a more specific event type.
Free Airtable users are allowed 100 automation runs per month. To see the automation and edit it, go to the “Automations” tab in the top. To get back to your tables, click the “data” tab.
5. AI Report Text Field in the Research Log and Timeline
For those who have a paid account at Airtable, which is required for AI Long Text Fields, I have added a column with a prompt to generate a section of your research report from the row in your research log. The AI model will only be able to generate text once all the fields used in the prompt have been filled out. Sometimes I use “none” for the FANs or other fields that aren’t relevant to a particular source so it can still generate the text. The prompt is:
The paragraphs generated will not always be perfect, but they are a start. Refining the prompt may help you get better results, depending on your needs for the project. For example, the AI model generated this text about Elam’s Findagrave headstone:
Elam Hollingsworth is commemorated by a headstone located in Preston, Franklin, Idaho, United States, which provides vital information about his life and death in 1905. The headstone transcription reads:
Elam
[^1]
Hollingsworth
June 1, 1838-Mar. 28, 1905.The headstone is an original source, as it is a physical artifact created at the time of Elam Hollingsworth’s death. There are no friends, family, associates, or neighbors (FANS) listed on the headstone.
**Comments**
The headstone is an important source for Elam’s birthdate. Without other sources for his birthdate, we wouldn’t have the exact date. It may be beneficial to review the cemetery layout and other Hollingsworth burials to determine if there was a family plot; perhaps his wives were buried near him.
[^1]: Find a Grave, database with images (https://www.findagrave.com/memorial/27122910: accessed 28 January 2025), memorial 27122910, Elam Hollingsworth (1838–1905), Preston Cemetery, Preston, Franklin County, Idaho; gravestone photo by Beverly Dansie.
The prompt tells the AI model to use markdown to create a footnote out of the source citation field. Markdown can be copied and pasted into Google Docs by turning on a setting under tools > preferences > enable markdown. Once this is enabled, one of the options when you right click is to “paste with markdown.” Markdown can also be pasted into Word with the Writage plugin.
An AI text field was added to the Timeline Table to help you write the starting point information for a research report. The field is called “AI Text Generation.”
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I hope these updates to the RLP with DNA base will help you as you keep track of your DNA matches and documentary evidence. Some ask if they should use this base even without DNA evidence for a particular project, and the answer is yes. I always use the most up to date RLP with DNA Airtable base template for my new projects to take advantage of the latest features; partly because this is the only base I continually update every year. Also, even if you’re not using DNA evidence for this phase of research, you might add it in the future.
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