The document discusses the integration of data science and machine learning into library systems, emphasizing the importance of librarian skills in developing effective metadata and recommendation systems. It highlights the need for libraries to adopt digital solutions akin to those of commercial giants while leveraging the expertise of information specialists for better user experiences. The combination of big data and cognitive technologies aims to enhance the relevance and transparency of content provided to library users.

1. Bo Weymann
DBC & data science –
where to go and why?

2. So why do we produce a knowledge
system, recommenders, automagic
metadata,…..
Using Math…...
As Christian told you about..........

3. A combined vision –
BIG META DATA and replication on
librarian skills
based on Machine Learning,
Datascience
and librarians
We could for a moment call it Librarian
computing

4. librarian skills are valuable in many
contexts - the problem is that there are
so few of them
Datascience as a strategic tool for
libraries can compensate this and maybe
even bring librarian skills in to situations
and in ways that are innovative

5. library users want digital solutions and
services in the same way as dominating
media giant do through solutions with
cognitive understanding - but libraries do
not need to know and help the user from
a commercial aim

6. In DBC we produce a lot of metadata -
BUT
To create and aggregate metadata in
those amounts as library users need
only through intellectual processes
and librarians m/w
– are a NO GO

7. So we felt a scence of necessity
Academic networking, courses and
experiments in: Machine learning,
datascience
Inspiration from commercial

8. LIBRARIAN COMPUTING

9. Librarian Computing
shall be used in
production -
in end user interfaces as well as
production of metadata and
metadata systems

10. Information specialist’s can
Structure the knowledge &
Navigating the large amounts of it
the librarian can
recommend it best in context &
communicate and convey
her commitment

11. The information specialist

12. Skills
Create and aggregate metadata - Cognitive
machine based on large amounts of data
and BIG DATA
Create a new taxonomi from a data set
Can seek out new relevant data sets
Can connect taxonomies
…........

13. librarian intermediary

14. Skills
empathize with the user's needs
be critical
tell why she recommends something to you
Cognitive "search engine” and recommender
system based on Machine Learning and
datascience, existing web services, user
feedback, user behavior, taxonomies,
metadata, data sets from social media, etc.
gives users the best possible content
depending on context…..with transparancy