themes in obis-usa, for discussion in arctic atn workshop philip goldstein march 25, 2013 o cean b...

Themes in OBIS-USA, for Discussion in Arctic ATN Workshop

Philip GoldsteinMarch 25, 2013

Ocean Biogeographic Information System


OBIS-USA Program – Three Aspects

• US Node of International OBIS• UNESCO/IODE

• Part of Federal Marine Biological Data Architecture

• Includes OBIS-USA, OBIS-SEAMAP, NODC

• Compatible with DMAC

• Motivated by specific Federal funders

• USGS Core Science, Analytics and Synthesis• USGS Internal Missions such as Biological Data and CMSP

• Operational Help!


OBIS-USA Functions

• Biogeographic data:• Taxon Name

• Location, depth, time, precision (x, y, z, d, t, e)

• Circumstances of observation

• Standards-based

• National Resource

• Bring together:

• Data originators

• Discovery and continuing applications

• Archival requirements and access (NODC)


Delivered Results of Enrollment - Checklist

Enrollment Checklist✔ OBIS-SEAMAP

✔ OBIS-USA

✔ NODC

✔ NetCDF version of data

✔ USGS Metadata Clearinghouse

✔ Data.gov

✔ International OBIS

✔ GBIFWhen enrollment is complete, check these items off – these products will all be complete.

Enrollment is the process of bringing data on board and making it accessible to the required channels.


Qualitative Results of Enrollment:Wealth of Data

Qualitative Results of Enrollment

Asset Dataset Richness, Documentation, Quality and Standards Established

Value Dataset publicly accessible and usable; Application opportunities multiplied

Security Life cycle from origin application archive has been anchored

Investment Enhanced relationship of data originator with OBIS-USA and NODC; also enhance data origination practices? Enhance community where data originated?

Community Data originator’s voice accessible to future development of standards and applications

• Assisted Enrollment

• Self-Enrollment


Flavors of Enrollment

• “Train-the-Enroller” creating experts in the community - “Points of Light”

• Reference Implementation

• Contrast requirements and opportunities of machine-generated data vs human-generated data

• Don’t neglect metadata

Enrollment Communications:Perhaps the Main Pre-Condition


Agency

PI / Mgmt

Science

Data

Agency

Program Mgmt

Science

Data

The bulk of the work is done at science and data levels.

Management and leadership levels give “go-ahead” and address prioritization if needed.

EnrollmentActivities

OBIS-USAand friends

DataParticipants

Consensus and communications at several levels must be established and remain healthy through enrollment.

Most of the effort involved in enrollment will be done by data staff with input from science team(s). Leadership and decision levels must be aware and oversee prioritization if necessary.

dbGenerate and service

configs

Metadata to FGDC XML

OBIS-USA Dataset Enrollment (steps a-j)

Image Table Generate Machine Metadata

Load occurrence format to MBG server location (if not already)

Capture metadata that can be queried or calculated from dataset contents.

b e


Map to MBG

Create mapping document; identify questions at field- and dataset-level; review and resolve with data originator.

d

Gather Human

Metadata

Descriptive metadata for all purposes: citation, abstract, georef, taxon ID, sampling and calc methods.

c

Occurrence Data

Format

Get data intotaxon-location-time format; from data originators’ various original technologies.

a

Publish Metadata

Sync NODC Sync iOBIS

Populate FGDC format metadata in XML using human and machine contents from previous steps.

Run script(s) to incorporate new dataset into OBIS-USA total database; run scripts to update web service configs.

FGDC accessible by Clearinghouse and verified; FGDC to GCMD; FGDC to ISO (potential).

Make new dataset (data and metadata) available to NODC; verify transfer and accession information.

Make data available to iOBIS; verify transfer; verify GCMD.

f g h i j

This chart is provided only as an example of a process; it is not intended to be a model for a specific Arctic ATN data management process. =Philip

Metadata to FGDC XML

dbGenerate and service

configs

OBIS-USADataset Enrollment

Publish Metadata

Sync NODC Sync iOBIS

Image Table Generate Machine Metadata

Load occurrence format to MBG server location (if not already)

Populate FGDC format metadata in XML using human and machine contents from previous steps.

Capture metadata that can be queried or calculated from dataset contents.

Run script(s) to incorporate new dataset into OBIS-USA total database; run scripts to update web service configs.

FGDC accessible by Clearinghouse and verified; FGDC to GCMD; FGDC to ISO (potential).

Make new dataset (data and metadata) available to NODC; verify transfer and accession information.

Make data available to iOBIS; verify transfer; verify GCMD.

b e

f g h i j


Map to MBG

Create mapping document; identify questions at field- and dataset-level; review and resolve with data originator.

d

Gather Human

Metadata

Descriptive metadata for all purposes: citation, abstract, georef, taxon ID, sampling and calc methods.

c

Occurrence Data

Format

Get data intotaxon-location-time format; from data originators’ various original technologies.

a

Interaction:•Steps in highlighted in orange indicate substantial and essential involvement of data originator•Here is where to balance cost and detail, and build enthusiasm •Here is the excellent opportunity to build community

• Redundant biological data programs?

No – the goal is to be complementary. This is challenging in practice and communication.

• Put data in one place and be done with the task of sharing

Not a question of channel, it’s a question of process. Make sharing a well-defined process that can be done flexibly when, where, by whom, with what resources.

• Spectrum from operational to research

This spectrum will influence data technology for sharing; also influences investigator’s motivation for sharing; also external motivation (customer) varies


Discussion Topics

• Be strategic about data types

It takes resources to be able to support and integrate different data types.

If you are reusing existing data types, don’t re-import them; integrate with them remotely on a standard-interface basis.

If you are innovating new data types or extending features of existing data types, get funded for it. It will require effort and this effort will contribute value to your community and others.


Discussion Topics

themes in obis-usa, for discussion in arctic atn workshop philip goldstein march 25, 2013 o cean b...

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