2019: My Year in Reading

All of the data that follows was collected by me throughout the year using a combination of Google Sheets and Google Calendar. This year, I analyzed my reading using both the start and finished dates for each title: for example, I totaled how many books I started reading each month and also how many I finished each month. I calculated separate averages for both and found the overall totals work out the same either way. Average days to read titles are based on the number of days actually spent reading each title, and not necessarily the full span from starting date to finished date.

A complete list of all the books I read in 2019 is at the bottom of this post.


For a list of my favorite books I read this year, go here >

I participated in #LibFaves19 on Twitter. See my selections here >

I didn’t create a “Least Favorites” list this year. I started to but then realized I enjoyed even my least favorite books too much to justify such a list. It was a good year for reading!

Continue reading “2019: My Year in Reading”

Year End Lists Are Coming

Starting Monday, December 9, I’ll be posting my top 10 books from 2019 on Twitter under the hashtag #LibFaves19. In preparation for this, I’ve begun creating my overall favorites and least favorites lists for the year, and prepping for my annual Year in Reading post.

This has me thinking more about my recent post on reader burnout. And I’ve made a decision:

This will be the last year I do a Year in Reading post for a while. I won’t track my reading in 2020.

This will be the sixth year I’ve tracked it and it’s not working for me. I think it does more harm than good. My hope is taking that obligation off my plate will relieve much of the stress I feel around my reading life. Which means I won’t be able to do a comprehensive Year in Reading report next year.

I’ll still participate in #LibFaves and I’ll continue to post lists of my favorites and least favorites of the year. But no more tracking or reporting. I just want to let my reading be what it is without worrying about it.

2018: My Year in Reading

All of the data that follows was collected by me throughout the year using a combination of Google Sheets and Google Calendar. All seasonal and monthly calculations are based on the date each title was begun. Average days to read titles are based on the number of days actually spent reading each title, and not necessarily the full span from begun date to completed date.

A complete list of all the books I read in 2018 is at the bottom of this post.


For a list of my favorite books I read this year, go here >

For a list of my least favorite books of the year, go here >

I participated in #LibFaves18 on Twitter. See my selections here >

Continue reading “2018: My Year in Reading”

2017: My Year in Reading

All of the data that follows was collected by me throughout the year using a combination of Google Sheets and Google Calendar. All seasonal and monthly calculations are based on the date each title was begun. Average days to read titles are based on the number of days actually spent reading each title, and not necessarily the full span from begun date to completed date.

A complete list of all the books I read in 2017 is at the bottom of this post


First things first: I’m a hypocrite.

In 2016, I wrote a post about the importance of reading more widely in genres I don’t normally read. I even posted lists of titles and swore to spend some amount of time in 2017 reading them.

I didn’t. I didn’t read any of them.

Continue reading “2017: My Year in Reading”

2016: My Year in Reading

All of the data that follows was collected by me throughout the year using a combination of Google Sheets and Google Calendar. All seasonal and monthly calculations are based on the date each title was completed. Average days to read titles are based on the number of days actually spent reading each title, and not necessarily the full span from begun date to completed date.

A complete list of all the books I read in 2016 is at the bottom of this post.


I read 70 books in 2016. This year I overwhelmingly read fiction:

Continue reading “2016: My Year in Reading”

2015: My Year in Reading

All of the data that follows was collected by me using a combination of Google Sheets and Google Calendar. Once again, I elected not to track pages read—too much discrepancy between formats to generate meaningful comparisons.

A complete list of all the books I read in 2015 is at the bottom of this post.


I read 66 books in 2015. Fiction titles outnumbered nonfiction by 2-to-1:

Continue reading “2015: My Year in Reading”

The Relevance of Libraries

On April 10, 2015, KCUR’s “Up to Date” program interviewed Prof. John Palfrey about the future of libraries in the Digital Age, the day after he gave a talk on the subject at the Kansas City Public Library. During the interview, KCUR tweeted a question meant to provoke discussion about the future of libraries:

Prof. Palfrey offers an optimistic and robust vision for the future of libraries, but even he frames the discussion in a way that implicitly fuels the fire for those who question their relevance.

I’ve spent a lot of time looking at the data and I have to say—I can’t understand how the relevance of libraries has come into question in the first place. It bothers me that we’ve allowed this question to define the discussion about their future. I can’t think of any other public or civic institution or service that can boast the kind of numbers that libraries do. I tweet-stormed some of the most powerful:

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Infographic – 2014: My Year in Reading

My friend Bil liked my 2014: My Year in Reading post so much, he made an infographic of it:

Infographic - 2014: My Year in Reading
This image is entirely the property of Bil Gaines.

He asked me to name an animal and I chose the three-toed tree sloth.

Bil is an amazing writer / artist / father / husband / shark lover / bland car enthusiast / SEO guru. Please read his blog. Also, if you want any fancy-schmancy infographics, drop him a line.

[AUTHOR’S NOTE added December 27, 2019: I was going through my old tracking spreadsheets and discovered an error in my original post. I had listed my longest stretch without reading as 28 days from August 11-September 8. I miscalculated this information. My longest stretch without reading in 2014 was actually 35 days from April 4-May 8. I can’t update this infographic, though.]

2014: My Year in Reading

I have a friend who posts a list of all the books they read each year on their Facebook page. This has inspired me to write my own Year in Reading posts.

All of the reading data that follows comes from my Goodreads account. A complete list of all the books I read last year is at the bottom of this post.

EDITOR’S NOTE: I realized after I posted this on February 12, 2015, that I had miscalculated some of my figures based on the data. On February 13, I recalculated all my figures to correct for my previous mistake. This post has been updated to reflect these new calculations. I added a day to my time-to-read figures.


I read 40 books in 2014. It was a nonfiction-heavy year for me.

  • 24 nonfiction
  • 16 fiction

Continue reading “2014: My Year in Reading”

Thoughts On Automated Recommendation Services for Libraries – A Correction

Re-reading my post from last month, Thoughts On Automated Recommendation Services for Libraries, I realize that I’m somewhat wrong about the role of locality in automated recommendation systems. Amazon and Netflix can (and I think they do) integrate user location data in their recommendation algorithm. They can skew results based on strong trends that appear among proximate user groups.

I’m also somewhat wrong about how recommendations work in BiblioCommons—ratings and reviews for individual titles are aggregated from multiple libraries, as well as user-created reading lists. Reviews from local library staff are prioritized over others, but I don’t know if local library user-created reading lists are prioritized. Regardless, these are individually curated pieces of content, these sections aren’t automated in the same way that Netflix is. This content is related to an individual item in the catalog and doesn’t generate lists of recommendations as one typically expects from Readers’ Advisory services.

The “Similar Titles” type of content in the sidebar in BiblioCommons is what I think of when I look for reading recommendations, and this content is also the most directly analogous to Netflix / Amazon. However, this content doesn’t get generated by BiblioCommons at all—these titles come from third party services like NoveList.

So locality can be a meaningful factor in automated recommendation systems—such systems are smart enough to recognize that local trends are important, even if they aren’t yet intelligent enough to know what local trends mean.

But libraries still don’t have enough data to make such algorithms work. We still rely on curation and the personal touch to create real value for our patrons.