Context of provenance in IS-ENES2

To be completed by the go-between with help from the Ri-Rep.

Cover the stages of the data life-cycle in which the RI is involved, that pertain to the <topic> with references to more detail if the RI has them. Include quantitative and timeliness information, intended uses and so on - if such information is available.

Summary of IS-ENES2 requirements for provenance

Detailed requirements

1.     Do you already have data provenance recording in your RI? Yes, depending on the data analysis activity

If so:

2.     Where/when do you need it, e.g., in the data processing workflows, data collection/curation procedures, versioning control in the repositories etc.?

 Mostly in data collection procedures as well as data processing workflows

3.     What systems are you using? Community tools e.g. to manage what has been collected from where, and what is the overall transfer status or e.g. to generate provenance log files in workflows.

4.     What standards are you using?

i.     Advantages/disadvantages No standard by now, first experiments toward the use of PROV-O in a specific analysis project.

ii.     Have you ever heard about the PROV-O standard? Yes.

5.     Do you need provenance tracking?

i.     If so, which information should be contained? Input data characteristics (names, characterizing facets, checksum, unique ids), tools used (git svn tags), output files, timing information, platform/environment information.

6.      What information do you need to record regarding the following:

i.     Scientific question and working hypothesis?

The data has been produced following a very details experimental protocol. We need to collect all the information needed to assess how exactly the protocol has been followed (facets, control vocabulary, documentation : es-doc.org).

ii.     Investigation design? Authors information.

iii.     Observation and/or measurement methods?

iv.     Observation and/or measurement devices?

v.     Observation/measurement context (who, what, when, where, etc.)?

vi.     Processing methods, queries?

vii.     Quality assurance?

 Performed quality assurance procedures, results of QA software.

7.     Do you know/use controlled vocabularies, e.g. ontologies, taxonomies and other formally specified terms, for the description of the steps for data provenance? Not yet.

8.    What support, e.g. software, tools, and operational procedures (workflows), do you think is needed for provenance tracking?

Agreements on what information to record and simple APIs to be able to be integrated in analysis tools and frameworks.

9.      How does your community use/plan to use the provenance information?

 -For catalogues as additional metadata for data products.

-For end users to understand the derivation history of data products.

-For tools to automatically “replay” specific analysis parts.

i.     Do you have any tools or services in place/planned for this purpose? No generic ones – specific loggers, etc. 

Formalities (who & when)

Add additional rows to the above table if you have covered this topic with this RI by holding discussions with several people, or if you have delegated some discussions; to show the full authorship and duration.