Today’s LODLIB update reflects datatype normalization and quality control checks across all of our GMarc datasets (Hahn, Zahn, Harnack, Tsutsui, BeDuhn, Roth, Klinghardt, Nicolotti). While we have only released the full text of the first three, since their print works are in the public domain, we have made use of all of this normalized data in our new data tabulations (3.7) and data visualizations (3.8). While our own iterative critical edition is still in progress, the counts and graphs for all earlier editions should now remain static, thus we are now comfortable building these data tabulations and visualizations into forthcoming journal articles and book reviews.
In other related news, Jason BeDuhn and I are meeting later today to discuss the Westar SBL session on Q and the Gospel of Marcion. Given our overlapping scholarly work, I’m very much looking forward to the conversation. I also received just today the proofs of my forthcoming data paper for the Journal of Open Humanities Data. It’s always nice to see one’s work as it’s about to go to (digital) press.
This week’s version continues our work to build out data normalization rules and standards for the academic/scientific study of the Gospel of Marcion. We’ve had another fruitful round of feedback about our Harnack datasets and short data paper for the Journal of Open Humanities Data. If we can get peer-reviewed agreement on the normalization of Harnack’s GMarc data, then normalizing the data of all of the other GMarc reconstructions will be far easier by comparison. In the meantime, in this week’s LODLIB, we have proposed new data normalization rules for the reconstructions of GMarc by Tsutsui (1992), Roth (2015), Klinghardt (2015/2020/2021) and Nicolotti (2019).
One of the great things about the LODLIB format is to visualize data while it is in process of peer-review and correction. The slew of data visualizations I released last week (another sample below) can easily be revised and updated if and when there are legitimate peer-reviewed corrections or consensus emerges about data normalization standards and/or the underlying normalized data. Visualizing data is so crucial to understand their importance and recognize their patterns, yet data are so often noisy, messy, and in fluctuation. Hence our modes of scholarly communication must adapt to accommodate these flexible processes, aiming for greater and greater clarity, fidelity, and scholarly consensus with each round of feedback and continuous improvement.
This week’s version initiates data normalization for the study of the Gospel of Marcion in concert with our freshly revised datasets for the fourth round of review of a short data paper and related datasets we have submitted to the Journal of Open Humanities Data, whose Editor-in-Chief is Barbara McGillivray at the Alan Turing Institute at Cambridge. The peer-review process has been wonderful and indeed transformative in my thinking and methodology.
The normalization of GMarc data (transforming past messy/noisy reconstructions into standardized data) will—mark my words—prove the tipping point in the transformation of the scholarly study of the canonical and non-canonical gospel strata into legitimate Data Science. In concert with our new normalization standards and normalized datasets of public domain reconstructions, we also release a slew of data visualizations illustrating the contents and relationships of all past GMarc reconstruction datasets. These visualizations clearly reinforce our scientific hypotheses and proofs that GMarc was in fact the third gospel stratum, based on two sources (the first gospel stratum, Qn, and an early version of Mark).
The age of hagiographical controlling bias and assumptions in Gospel Studies is over. The age of Gospel Data Science is upon us. Scholars can either get on board or get out of the way, but no matter what you do, you can’t stop this.