The document discusses implementing a digital asset management system using SharePoint 2013. It covers key SharePoint enterprise search features like enhanced user interfaces, display templates, analytics and suggestions, and query rules. It also discusses video and media features in SharePoint 2013 like thumbnails, players, and supported formats. The document recommends using out-of-the-box SharePoint features for DAM, including search, taxonomy-based classification, and remote blob storage. It concludes with contact information for the author.
4. Key SharePoint Enterprise Search Features
Enhanced User-Friendly Interface
Display Templates
Analytics and Suggestions
Query Rules
5. Enterprise Search: User Interface
Fluid
Search Results
Content Previews
Mixing of Content
Flyout panels
6. Enterprise Search: Display Templates
Specific display of
search results based on
the type of content
Custom display
templates can be easily
created using standard
JavaScript
Huge potential for
enhancing and
improving search user
interface
7. Enterprise Search: analytics and suggestions
Search Engine, tracks
clicks and provides
suggestions
Search Engine captures
user behaviour and
makes
recommendations
Analytics and
Suggestions can be used
to enhance content
discovery on the Intranet
8. Enterprise Search - Query Rules
responding intelligently to users with Query Rules
acting
Recognize a product,
promote the Knowledge Center
Resources
Recognize an image search,
query for images of cameras
Recognize a top Video search,
show videos of the Surface
understanding
Learn more about our
products
Find pictures of our cameras
What can the Surface do?
communicating
13. How Remote BLOB Storage Works
2.
Enforce
Business
Logic
1. Save Request
3. Save Blob
4. Write Blob
5. Return BLOB ID
6. Save Metadata &
BLOB ID
7. Back to User
18. Assets Uploading
Create Album than upload images:
– Using standard Browser Interface (Drag & Drop)
– Using Windows Explorer , where album appears as a folder
29. Key Points / Lessons Learned
• SharePoint search is a good platform to build robust
and efficient applications
• Use as much as possible “out-of-the-box” standard
features, provided by the SharePoint platform
• Use well defined taxonomy/assets classification based
on the standard SharePoint Metadata service
• Classify assets with external Legacy Data, using the
SharePoint BCS Services
• Remote Blob Storage should be correctly configured
and maintained
• Site blob storage should be correctly configured .
Check SharePoint Log files for any cache critical
errors.
SharePoint 2013 Search Based Application:
Search Verticals for Albums, Videos, Images, Audio and Illustrations
Custom Search Display templates to show relevant assets information
Custom Search “Facets”/Filters display templates to narrow down results
SharePoint 2013 Assets Library to manage content
Remote Blob Storage (RBS) to store large media content outside the database
Comprehensive Digital Assets classification taxonomy – more than 10’000 terms
Bulk classification based on Assets Albums (based on SharePoint Document Sets)
Standard SharePoint publication approval process
Faceted navigation is the process of browsing for content by filtering on refiners that are tied to category pages. Faceted navigation lets you specify different refiners for category pages, even when the underlying page displaying the categories is the same.
Faceted search
From Wikipedia, the free encyclopedia
Faceted search, also called faceted navigation or faceted browsing, is a technique for accessing information organized according to a faceted classification system, allowing users to explore a collection of information by applying multiple filters. A faceted classification system classifies each information element along multiple explicit dimensions, enabling the classifications to be accessed and ordered in multiple ways rather than in a single, pre-determined, taxonomic order.[1]
Facets correspond to properties of the information elements.[2] They are often derived by analysis of the text of an item using entity extraction techniques or from pre-existing fields in a database such as author, descriptor, language, and format. Thus, existing web-pages, product descriptions or online collections of articles can be augmented with navigational facets.
“Faceted search” is the rubrick for a site that allows users to refine search results by categories (aka “facets”). This kind of interface appears on a lot of sites (Kayak and Kudzu are two examples that come to mind). If not implemented with care, faceted metadata search interfaces can be a huge problem SEO-wise, as they create an almost infinite set of pages for a search engine robot to get hung up on.
Consider the following sets of category metadata on a restaurant search:
- restaurant
- chinese
- italian
- quiet
- romantic
- pleasanton
By clicking around on these categories you can get a huge number of results (6*5 factorial? – any Einsteins out there?) such as:
- Chinese restaurant
- Quiet Chinese restaurant
- Romantic Chinese restaurant
- Romantic quiet Chinese restaurant
- Romantic quiet Chinese restaurant in Soho
- Romantic quiet Chinese Italian restaurant in Soho
- etc.
So you get a bunch of problems – too many pages, confusing navigation and probably a duplicate page problem to boot as a lot of these pages tend to have the same data on them.
So how do you solve this and still offer faceted search?
1. Figure out which are your most important pages among the million possible combinations
2. Create linear paths for the search engine robots to follow using noindex tags, nofollow tags and your robots.txt file
3. Make sure that no page that you are pointing the bots to has more than one of each data type (e.g. quiet but not romantic, and vice-versa) – unless you think having two of a type is good for SEO, but that would involve some complex planning and coding.
4. Remember that if you already have this problem you will need to purge the problem pages from the search engines’ indexes before you try to fix it using bot herding or else the bots will never revisit your problem pages.
For more on faceted search check out the following:
Intelligenx
Drupal faceted search
MOSS faceted search
Sharepoint faceted search
Endeca Technologies