Leveraging the New Multimedia Module: Automation and Integration

1. Leveraging the New Multimedia Module: Automation and Integration Rebecca Snyder Smithsonian, NMNH

2. Automation – Embedded metadata is my friend…

3. Digitization Project Example: Automation Integration Challenges Future Work Photographers 1 project. 15 photographers. 18 months. 600,000 images. One gigantic mess

4. Automation Integration Challenges Future Work Media Staging Area - MeSA Approved users map to the SAN unit like another networked drive. Centralized area for image and other data storage. Provides space to assemble, manage, organize and standardize projects. SAN is backed up and maintained by IT.

5. Automation Integration Challenges Future Work Project Data Organization and Embedded Metadata: “When once is enough...” With all project data centralized in the Media Staging Area (MeSA) on the SAN, project personnel can use Adobe Bridge (or other product) to apply common metadata across all images within a group, so it only is entered once. Individual images/files can be edited with unique metadata as well. The Multimedia Module autopopulates the values entered into IPTC, Exif and XMP fields. For NMNH, focus is placed on the IPTC metadata fields since the DAM supports IPTC (IIM) and also autopopulates fields based on the embedded metadata. Metadata entered once, automatically read by two systems.

6. Automation Integration Challenges Future Work Collections Based Images/Files Images placed into EMu’s Multimedia Module. Metadata embedded into multimedia file headers are read by EMu and fields autopopulated – minimizing the need to reenter data. Each derivative generated by EMu will inherit the embedded metadata chosen by the department. Especially useful when generating images for the web. These autopopulated fields can be searched and reported upon (with some CR filtering…).

7. Automation Integration Challenges Future Work Non-Collections Based Images/Files Once project is either finished or at a designated milestone, completed project folders with organized and complete data are ingested en masse into the DAM via a backend connection by informatics staff. Assets within each project folder will have a common set of metadata applied to all within it. Embedded metadata is read by the system and DAM fields autopopulated. As needed/desired, researchers can log into the front end of the DAM and add additional information.

8. Automation Integration Challenges Future Work NO REENTRY OF DATA REQUIRED. Same file in the DAM. All the embedded metadata is automatically read by the DAM and the appropriate fields populated.

9. Integration – KE is my new best friend…

10. Collections and Web Records Summary (06/2007): Automation Integration Challenges Future Work † Approximate. Includes Entomology Primary Types, Odonates, Mosquitoes

11. NMNH Multimedia Records (10/2007): Automation Integration Challenges Future Work All live environments: 543,247 multimedia records • A subset of images to be added within 12-18 months: • Entomology Type Imaging Project: ~111,000 type specimens each with at least 4-6 images (444-666,000 images) • Botany Cacti image collection: ~200,000 images • Botany Latin American Plant Initiative: ~600,000 images • Fishes: ~10,000 images

12. Automation Integration Challenges Future Work Information Management File/Digital Asset Management

13. Benefits of using an external digital asset management system: Automation Integration Challenges Future Work • primary focus on managing the physical file • focus beyond multimedia file formats • ability to identify files (multimedia, text, pdf, etc.) you determine are at risk of format obsolescence and bulk convert to new format – while keeping original and using new derivative as the ‘current use’ version (ie: version control) • version control also provides check-in/check-out functionality • for SI: integration with prototype federated searching layer and planned “Trusted Digital Repository” archiving system

14. Coarse Planned Integration Flow: Automation Integration Challenges Future Work SI Federated Searching Layer NMNH EMu Web NMNH EMu SI DAM Linux UNIX/Texpress Oracle DBMS filter filter SI TDR (trusted digital repository)

15. Envisioned DAM <-> EMu Integration: Automation Integration Challenges Future Work • User ingests file within multimedia module as normal. • EMu automatically generates thumbnail and ~200x200 pixel image for display on multimedia tab (a ‘quick access’ copy). • Either at time of save or at set intervals, EMu passes original image to the DAM – basically treating the DAM as a remote storage location. • EMu access and flag settings used to determine which security/permission model within DAM system to apply to file. • When EMu user requests original image download, EMu sends request to DAM for file.

16. Maintaining EMu access flags in the DAM: Automation Integration Challenges Future Work

17. Automation Integration Challenges Future Work

18. Challenges: Automation Integration Challenges Future Work • When to pass original image to DAM? At time of save? Weekly pushes? When Data Manager sets new DAM ready flag to yes? • Writing new embedded metadata to image files… Will KE add this functionality? If so, must only be data that is not subject to change (ie: not specimen storage location, etc.). • Difficult to add values in fields from other modules. Possible to have most commonly used fields as local copies within multimedia module… • How to keep DAM and EMu records up to date if metadata changes? Possibly have backend of EMu take advantage of DAM’s check-in/check-out feature. EMu will have to ‘update resource’ to get new metadata values.

19. Other Challenges: Automation Integration Challenges Future Work • How to handle ‘set’ data? Images and other media that are individual files but need to be treated and delivered as a set. • Examples: • DICOM. Large number of individual slices that combined make a single CT scan. All must be present to recreate specimen. Not practical to import all 1000+ files separately into EMu and link all 1000+ multimedia records to catalog record… • Extended Depth of Focus (EDF) Imaging. Image series that is used to create a single composite image. Best practice keeps original images, not just composite. • Raw images files. Separate record? Version of tiff surrogate?

20. Contact Information: Rebecca Snyder Smithsonian, NMNH snyderr@si.edu 202.633.0754

21. Automation Integration Challenges Future Work The “Big Picture” With metadata standards standardized and used by NMNH systems, data can be easily shared with all other SI systems under the “EDAN” layer – making federated, pan-institutional searches possible. Ex: A US Senator's office calls and asks for everything the Smithsonian has on his/her state. Much easier to search once than to individually query each unit’s various systems. Working prototype with the various SI Library Systems.