1. Organizational Relationships and Shaping the Digital Resource July 21, 2010 Johanna Bauman, Senior Production Manager, ARTstor

2.  Subscription-based digital library of over one million images in the areas of art, architecture, the humanities, and social sciences with a set of tools to view, present, and manage images for research and pedagogical purposes.  Community-based aggregator of existing image content to which we are committed to providing persistent and consistent access for ARTstor subscribers.

3.  First collection launched in summer 2004  1,200 subscribing institutions  Over 1,000,000 images  Over 170 unique collections  Over 700,000 images in the queue to be added to ARTstor  150,000-200,000 images added per year

7. Metadata

9. Educators, scholars, and students at a variety of non-profit institutions including universities, colleges, museums, public libraries, and K-12 schools. Historians of art and architecture and others engaged in the visual arts, as well as individuals in fields as diverse as American Studies, Anthropology, Asian Studies, Classical Studies, Literary Studies, Medieval Studies, Music, Religious Studies, and Renaissance Studies.

10.  Museums  Image Archives, Libraries, Special Collections  Visual Resources Collections  Sponsored Professional Photographers  Scholar Photographers with Unique Content

11.  Existing Digital Scans  Born Digital Photography  New Scans from Transparencies  New Scans from Prints

12.  Format: TIFF or Camera RAW (or JPEG if no TIFFs or Camera RAW are available)  Pixel Dimensions: Minimum of 3,000 on the long side (preferably 6,000 for born digital and scans from large format transparencies)  Color Space: Adobe RGB (converted to sRGB for online delivery)  Bit Depth:16 bit (converted to 8 bit for online delivery often 8 bit is acceptable)  File size: ranging from 36-200 megabytes  Resolution: variable 300-600 ppi (pixels per inch)

13.  Excel spreadsheets – data created in Excel or exported from other database systems  XML exported from other database systems  FileMaker Pro databases  Access databases  Embedded metadata in custom XMP panels or that uses IPTC

14. 1. VRA Core – Visual Resources Collections 2. CDWA (Cataloging for the Description of Works of Art) – Museums (TMS) 3. MARC – Libraries 4. Dublin Core – All 5. Custom – Scholars, Photographers, etc.

15. Image Capture/Scanning Acquisition and Processing Image Quality Control Metadata Creation (ARTstor requires item- level control) Metadata Mapping and Enhancement Legal Review Ingest to ARTstor Long-Term Storage

16. Image quality is inadequate or images have been over-processed Image sizes are inconsistent or don’t meet the minimum requirements and it is hard to weed them out by size Images and metadata don’t match (image and/or data orphans) Metadata is inconsistent and cannot be easily mapped Metadata is too minimal to be enhanced or needs additional cataloging

17. Data Enhancements to Facilitate Advanced Search

18. Review sample images before agreements are signed and provide guidance from the outset Provide documentation of best practices for image enhancement and metadata creation Provide potential contributors with Excel templates for cataloging Set contributors up with custom XMP panels for cataloging their images

19.  Larry Qualls – Photographer creating born digital images and cataloging them in Adobe Bridge using a custom panel  Christopher Roy – Scholar with existing digital content that needed to be cataloged  Milton Rogovin – Existing scanned photographs that needed to be cataloged

20. BenefitsChallenges Clear relationship between image and metadata Schema that come bundled with tools like Photoshop and Portfolio do not meet the needs of the cultural heritage community Ability of the contributor to see the image while they are cataloging it rather than having to move between the image and a spreadsheet It is harder for contributors to edit and review the embedded metadata so there is a higher margin for spelling errors and the like When using existing tools, such as Bridge there is an easy way to associate the same data with multiple records If contributors are using their own custom panels it may be hard to identify and extract the data

21.  It is intended primarily to support the activities of archivists and librarians who received digital files with embedded metadata and need to extract data to upload to local systems  Extracts all XMP namespaces as well as EXIF fields targeted to meet NISO 739.87 standards that could be ingested into a PREMIS-based preservation system  Checks if files are corrupt  Checks for the presence of a custom panel and whether or not required fields have been filled in

22.  Developed on the Adobe Air platform, which is available for download for free  Currently in QA  Will be available for free download from the ARTstor website and as an open source application by the end of 2010

23.  Networked image management platform that will allow institutions to build, manage, access, and share visual content across their own campuses and integrate it with ARTstor images  Partnering with eight colleges and universities in developing the tool set and infrastructure (Harvard, Cornell, Yale, NYU, Colby College, Middlebury, University of Illinois, U of Miami)  Tools will include: image management, cataloging, content management, and delivery  Will facilitate sharing of collections with other institutions as well as providing content to the ARTstor Digital Library