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DTSTAMP:20220812T074334Z
LOCATION:Osaka Room
DTSTART;TZID=Europe/Stockholm:20220627T173000
DTEND;TZID=Europe/Stockholm:20220627T180000
UID:submissions.pasc-conference.org_PASC22_sess137_msa192@linklings.com
SUMMARY:Utilizing Data Lakes for Managing Multidisciplinary Research Data
DESCRIPTION:Minisymposium\n\nUtilizing Data Lakes for Managing Multidiscip
 linary Research Data\n\nGreiner\n\nScientific research institutes face a l
 ot of the same challenges as commercial organizations when it comes to man
 aging data. Just like for commercial organizations, a common situation is 
 data silos, or even wors, data swamps. The fundamental problem is that the
  continual manual effort needed to govern data prooves to be too much for 
 many research institutes. A possible solution would be to automate as much
  of the process as possible, and to minimize the amount of duplicated effo
 rts. In the present talk, we discuss our current efforts to improve data m
 anagement of a mid-sized an academic research institution. We show that, w
 hile some aspects of data management are very similar to those faced in co
 mmercial organizations--such as data ingestion, processing, and reporting-
 -some others aspects are quite specific to the use case of academic resear
 ch. In these cases, we adapt or re-build cutom modules to accomodate for t
 he unique workflows of researchers. In the end, we aim to make use of know
 n best practices and technologies, while embracing the uniqueness of resea
 rch practices.\n\nDomain: Computer Science and Applied Mathematics
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