<trackbot> Date: 16 June 2015

Ali Anil SINACI to talk about SALUS project

<Lloyd> zakim ipcaller is lloyd

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<Marc_Twagirumukiza> Hi, am calling in with my Laptop

Anil's slides: http://tinyurl.com/salus20150616

Anil: Background in CS. Was tech lead in SALUS project, officially ended in APril.
... Was an EU project with 10 partners.

slide 2

slide 5

slide 9

slide 10

slide 11

CIM = Common Information Model

slide 12

slide 13

slide 15

slide 16

slide 17

slide 18

slide 19

slide 20

<ericP> Euler

http://eulersharp.sourceforge.net/

anil: Used Euler for semantic translation: http://eulersharp.sourceforge.net/

slide 23

slide 24

slide 25

slide 26

slide 27

anil: Data element exchange profile is being prototyped.
... Will allow definitions to be shared.
... Main motivation was for form designers to auto populate forms.
... E.g., during clinical trial, if researcher is designing a form, it can be associated with a data element.
... Modeled as abstract data elements.

dbooth: What are the plans for SALUS now that the project has officially ended?

anil: For the whole framework, no concrete plan to use it all. But for different components, partners are building more tools.
... Metadata registry can also be used in other domains.
... SALUS is not planning to continue the framework, but components

<Zakim> ericP, you wanted to ask about common information model

eric: You have two levels of mapping: 1. map the different terminologies; 2. map the information model.
... You ontologized the CCDA model, lifting, and worked toward CIM.

anil: Yes, first CCD and then CIM.

eric: Was there an advantage to that over picking one of the physical models and using it?

anil: biggest advantage was to leave the mapping to the outside world.

eric: Does that mean you matierlized the data in your info model?

anil: Yes.

eric: so you wrote n mappings from the source models to your CIM?

anil: Yes.

eric: I'm guessing a lot of our future work is to develop our ability to do those mappings. Your wisdom on that?

anil: at the beginning we tried to build a CIM to cover all data requirements based on our use cases.
... But it's not possible to meet all field requirements. One size does not fit all.
... And it's a fact that tthere will be many models around. Thats' why we built this metadata registry.
... using ISO 11179.

eric: How much did you model? Patients and observations? Did you get into constellations of observations, or just single observations?

anil: Not much detail, just codes of observations.
... On slide 6 we queried for some conditions and analyzed common conditions that happened at the same time. We can ask for multiple conditions.

dbooth: Data element exchange profiles: Sharable? Reusable?

anil: Most are now available

paul: slide 28 also mentiones data element exchange

anil: they allow machines to access the details of the data element definition, so that a SPARQL or other script can use that to access data.

dbooth: Assessment: success of using RDF? What benefits and challenges did you experience?

anil: Challenge was performance.
... Executing the reasoners for inference requires much more processing time.
... But the models and changing them are easier in RDF.
... And if data is not available it doesnn't break, it just doesn't show it.
... Also doing the mappings for the data transformations.

dbooth: More specifics about performance challenges? what was used and what did you run into?

anil: Machine w 16 cores and 64GB, we had difficulty processing Lombardi region data, 16M patients, 500M records in conditions, 300M prescription records.
... Answering a query like shown takes about 2 days, mostly doing translations: XML to RDF and also to the CIM.
... Euler is not enough on this hardward.
... We tried to implement our own map-reduce algorithm to overcome this, and might be better to use big data framework.

ADJOURNED

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Present: Kerstin_Forsberg Tony_Mallia Brian_Pech Marc Darrell_Woelk Anil_Sinaci Charlie_Mead Lloyd_McKenzie EricP Paul_K._Courtney Claude_Nanjo David_Booth
Found Date: 16 Jun 2015
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