Very excited, on my way to my first #swib22

« Thanks to all presenters and moderators of the two Thursday sessions at #swib22. Recordings will soon be available via this playlist: https://www.youtube.com/playlist?list=PL7fMsenbLiQ2xcclhSnk1nv752E4N_Nqx »

— Retweet https://twitter.com/swibcon/status/1598390133128134669

You will find most of the presentation slides of #swib22 linked from the programme page at https://swib.org/swib22/programme.html

We will also add links to the recordings to the page, until then you can watch the recordings via the YouTube playlist at https://www.youtube.com/playlist?list=PL7fMsenbLiQ2xcclhSnk1nv752E4N_Nqx

We are looking forward to next SWIB where we'll meet in person again. #swib23 will happen in Berlin on September 11th to 13th. Thanks to @stabi_berlin for providing the venue! #swib22

That's a wrap with #SWIB22. Thank you @swib, always a great conference. Looking forward to #SWIB23 which will happen in Berlin (11-13 September)

Yes I deleted the previous toot, as in the dates were wrong! Thanks to @bencomp

#swib22 is closing. Thanks to the speakers, workshops facilitators, the programme committee members, the organizing team & all participants for another SWIB we have enjoyed very much!

The application of #IIIF and #LOD in digital humanities: a case study of the dictionary of wooden slips by Sophy Shu-Jiun Chen and Lu-Yen Lu

Data Linkage between LOD and IIIF through the seeAlso property
link the LOD-based descriptive metadata of an object or a Chinese character with its image data embedded in the IIIF Manifest

Image Annotation compatible with the Web Annotation Data Model (WADM)
- The current structure of faceted annotation contains WADM's motivations, tagging, describing, commenting, and classifying for different annotation purposes

#LOD #LOUD #LODLAM #swib22 @iiif

@acka47, vielen Dank und beste Grüße nach Köln! Und Glückwunsch zur erfolgreichen #swib22!

I’m enjoying being warm on the couch for the last morning of #swib22 but my companion has taken it to the next level of cozy

Principles for the Digital Scriptorium (DS) 2.0 Redevelopment

- Minimal data entry standards
- Members manage their own metadata (formats and values)
- DS 2.0 does not host images (--> #IIIF)
- DS 2.0 will provide semantic enrichment
- Open Access

More information about DS 2.0: https://digital-scriptorium.org/ds-2-0/

#swib22 #iiif #lod #lodlam @iiif

"LOD Applications" is the title of the last session at #swib22. It will start in a few minutes. As usual, join the live stream via https://swib.org/swib22/

In the end, we managed to get this deployed for #swib22 week, although this was rather last minute.

Thanks to all presenters and moderators of the two Thursday sessions at #swib22. Recordings will soon be available via this playlist: https://www.youtube.com/playlist?list=PL7fMsenbLiQ2xcclhSnk1nv752E4N_Nqx

We are also running this poll on the bird site and will soon post a poll in the #swib22 mattermost chat.

The reason for the missing crossposts to the bird site can be seen at https://crossposter.masto.donte.com.br/ #swib22

« Get ready for day two of #swib22! The first Tuesday session "Linked Library Data II" is about to start in a few minutes. Follow the live stream via https://swib.org/swib22/index.html. https://t.co/kvUELxrGjA »

— Retweet https://twitter.com/swibcon/status/1598345009194901504

There seems to be a problem with crossposting to the bird site. We thought about deactivating the account there anyway. What is your opinion on this?

#swib22

@swib Artem Reshetnikov's slide "Fairness in GLAM" shows how AI, based on the data of our "white male supreme" culture, perpetuates manifested sexist and racist etc. view of the world. This talk follows up @stacymallison "
Libraries, linked data, and #decolonization" keynote. One has to pay attention when using #AI techniques. #swib22

The "Machine Learning" session at #swib22 just started. Watch the live stream via https://swib.org/swib22/

Looking forward to this next #swib22 presentation "How are data collections and vocabularies teaching AI systems human stereotypes?"

I'll never forget the time I saw Dorothy Berry present about poor cataloging of music that was basically blackface (white writers writing "soul" or "Negro" "style" songs back in the day and modern catalogers being like "I guess this is Black music!") and someone said "could machine-learning fix this?"

like ... with THIS training data?