There are some technical definitions (e.g. here), but allow me to put it more succinctly:
Reproducibility – people believe they can replicate the methods and outcomes based on the information provided in the research documents.
Replicability – they can really do so.
🙂
This has been a widely discussed topic, but when it comes to academic publishing, focus on quality over quantity.
Take my PhD adviser as an example. At this moment, he has “only” 27 journal papers and 40 conference papers according to dblp, but nearly 40000 citations, including 10+ papers with 1000+ citations, according to Google scholar.
In comparison, there are people around his seniority and in our fields (for calibration) with roughly 10-times publications but only one-tenth of citations.
(Citation is one of the mostly commonly used measure for quality/impact, but others are possible, such as products.)
He once told me that the best timing to publish papers is when people beg us to do so (using Brain Curless’ first SIGGRAPH paper as an example). That is probably too extreme, but publishing low quality papers not only wastes our time (it is better to go out and play) but also dilutes our reputation.
Anyone who likes a 50% discount code for SIGGRAPH Asia 2017 registration, feel free to contact me. The code expires on 24 November 2017. 🙂
— Li-Yi Wei (@liyiwei) October 26, 2017
[Update] The code went to Tejas Shroff, whom I don’t know but who seems to be doing interesting VR stuff.
Waking up in the middle of the night, sometimes I can remember ideas from my dreams.
My friend Nelson Chu could not attend SIGGRAPH 2017 to demo his Expresii, so I stood in for him.
Thanks to the wonderful product from Nelson, this is a fantastic presentation experience. I can interact with and talk to many different people, focusing more on practical utility than technical details. I had no time to get bored for the entire 2-hour duration. People kept on visiting even after the session closing. And I had a great time practicing playing the app myself.
Publishing a SIGGRAPH paper is about proving how smart we are, while demoing a SIGGRAPH app is about demonstrating how useful it is for you.
Instead of hosting research materials on our own servers (as I did in the old days for both ongoing projects and published outcomes), it is more flexible to share on GitHub/Bitbucket public/private repos that need revision control, and store the compiled files in other services, such as papers on research gate or semantic scholar, videos via YouTube/Vimeo, etc.
With this setup, the co-authors can edit the research page together, and have less to worry about server management.
We should share only information ready for the public domain, e.g., paper title only after the submission is formally approved for acceptance, and code/algorithm after filing the relevant patent(s).
I cannot believe I have not (really) noticed this earlier, but the current git/svn revision controls are based on simple line differences, without taking into account the actual editing operations which we actually did in SIGGRAPH 2011 for image editing.
As a very simple example, say a file contains an original line like this:
I love you. Do you love me?
User 1 breaks the line into two:
I love you.
Do you love me?
User 2 adds one word the line:
I love you. Do you love me too?
A revision control tool that considers editing operations can automatically merge the two edits:
I love you.
Do you love me too?
While the current svn/git tools, based on line differences, will simply give up and ask users for manual intervention.
Among the 3 options for your glorious SIGGRAPH (or other ACM) paper, I usually choose the new licensing agreement (option 2) because it does not require shelling out a few grands for retaining all rights (option 3) and allows the authors to retain the theoretical copyright unlike the traditional copyright transfer (option 1).
By theoretical, I meant that options 1 and 2 probably make little to no practical differences for authors, since the license transfer is perpetual and exclusive for ACM, and authors can share their preprints anyway.
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