1. Working Group: DFT - some use cases - Peter Wittenburg, Raphael Ritz

2. Use Case: CLARIN Collection Builder
PID
data MD MD
data
data MD
collection
builder MD
data
data MD MD
data
data MD MD
data
MD+
data MD MD
data
repository 1
repository 2
Collection building across repositories is essential for running analysis. PhD students f.e. create their collection which exists of a MD object having a PID and storing many PIDs to refer to its components. Such a collection is an aggregation, but has an identity, can be cited, etc.

3. Use Case: Replication in EUDAT Data Domain
community 1
community 2
community 3
data MD MD
data
data
PID
data
MD+
MD+
data
MD+
data
EUDAT data domain
replicating data from different types of data organizations from different communities = creating a coherent domain of data is not trivial

4. Use Case: EUDAT Data Domain
urgently need PID Info Types:
cksm
cksm type
data_URL+
metadata_URL+
ROR_flag
mutability_flag
access_rights_store
etc.

5. Use Case: Curate Gappy Sensor Data in Seismology
sensing
p(t-5)
p(t-4)
p(t-3)
p(t-2)
p(t-1)
p(t)
real-time
p(t-5)
p(t-3)
p(t-1)
p(t)
receiving
p(t-4)
p(t-2)
packaging
completing
window (t1,k)
window (t1,k+1)
analyzing,
referring
window (t2,k)
window (t1,k+3)
real-time data due to limited delay, gappy data since referred data has gaps, dynamic data since gaps are being filled at random times

6. Use Case: Crowd Sourcing Data Management
buffering,
chunking
annotating
intermediate store
stream data
metadata
database
annotations
PID
system
Curation
Structuring
Curation/Structuring
- create proper MD
with all relations
- register PIDs for all
objects
permanent store
stream data
metadata
annotations
analysis

7. Use Case: Language Technology Workflows
collection
collection
collection
processing
module k
processing
module l
processing
module m
metadata
metadata
metadata
metadata k
metadata k
metadata l
PID
system
processing modules are service objects

8. Use Case: Language Technology Workflows
processing
module x
read collection MD
read MD
interpret MD & get PID
get data
process data & create new data
register PID
create MD*
update collection
if more in collection go 2
end
Typical processing modules are:
tokenize texts
tag part of speech in texts
parse (shallow) of texts
recognize named entity in texts
filter speech
detect voiced segments
detect speaker of segments
do rough classification of segments
etc.