Exploring Metadata Objects and Relationships - Enterprise Information Management - SCN Wiki
S2 Trust Relationship Specification E2 Reputation Network M3 Trust Engine D1 Hestia Framework Trust Relation and MetaData Information Database The. Page: Main Features of the Information Steward () Impact and Lineage Diagram. InfoSphere® Information Server tools analyze and transform data that comes from databases and data files. The metadata that describes databases and data.
The one-to-many possible relationships can be found in the last three fields of a favorite: The two tables that are used in the TDS 6. The TDS Metadata window is docked by default. Click the favorite from which you want to remove a relationship.
Click the Value text box of one of the fields and enter noInformation. The one-to-many relationship is removed from the favorite.
Metadata - Wikipedia
Removing many-to-many relationships from a favorite The many-to-many relationships are added and managed in the TDS Metadata favorites window under the favorite as related objects. Impact lists other metadata objects that are affected by data within a particular metadata object.
For example, a universe object can impact multiple reports. Lineage lists sources from which a particular metadata object obtains its data. For example, a report column obtains its data from a universe object, which in turn obtains its data from a column in a table in a relational database. An alias is another name for an object in a different system.
For example, an alias in one database might refer to a relational table in a different database. A synonym is just another name for an object in the same system. Same As means just that - the object is the same as another object. This relationship can exist only between objects of the same type.
- Implementation relationships
For example, a Same As relationship can exist between each object in a test system and its corresponding object in a production system. Same As is also highlighted on the Impact and Lineage diagram with a dashed line between the two objects The Related To tab will display Primary Key — Foreign Key relationships as well as any additional relationships that you have created on your own will show up here.
The process indexes pages then matches text strings using its complex algorithm; there is no intelligence or "inferencing" occurring, just the illusion thereof.
Hierarchical, linear and planar schemata[ edit ] Metadata schemata can be hierarchical in nature where relationships exist between metadata elements and elements are nested so that parent-child relationships exist between the elements. An example of a hierarchical metadata schema is the IEEE LOM schema, in which metadata elements may belong to a parent metadata element. Metadata schemata can also be one-dimensional, or linear, where each element is completely discrete from other elements and classified according to one dimension only.
An example of a linear metadata schema is the Dublin Core schema, which is one dimensional.
Use metadata to generate entity diagrams
Metadata schemata are often two dimensional, or planar, where each element is completely discrete from other elements but classified according to two orthogonal dimensions. Hypermapping frequently applies to layering of geographical and geological information overlays. Metadata with a high granularity allows for deeper, more detailed, and more structured information and enables greater level of technical manipulation.
A lower level of granularity means that metadata can be created for considerably lower costs but will not provide as detailed information.
c# - Metadata information for the relationship could not be retrieved - Stack Overflow
The major impact of granularity is not only on creation and capture, but moreover on maintenance costs. As soon as the metadata structures become outdated, so too is the access to the referred data. Hence granularity must take into account the effort to create the metadata as well as the effort to maintain it. Standards[ edit ] International standards apply to metadata. Much work is being accomplished in the national and international standards communities, especially ANSI American National Standards Institute and ISO International Organization for Standardization to reach consensus on standardizing metadata and registries.
This standard specifies a schema for recording both the meaning and technical structure of the data for unambiguous usage by humans and computers. This standard also prescribes the details for a metadata registry, and for registering and administering the information objects within a Metadata Registry.
While this standard describes itself originally as a "data element" registry, its purpose is to support describing and registering metadata content independently of any particular application, lending the descriptions to being discovered and reused by humans or computers in developing new applications, databases, or for analysis of data collected in accordance with the registered metadata content.
This standard has become the general basis for other kinds of metadata registries, reusing and extending the registration and administration portion of the standard. The Geospatial community has a tradition of specialized geospatial metadata standards, particularly building on traditions of map- and image-libraries and catalogues. Formal metadata is usually essential for geospatial data, as common text-processing approaches are not applicable.
The Dublin Core metadata terms are a set of vocabulary terms which can be used to describe resources for the purposes of discovery.
Removing TDS metadata relationships
The original set of 15 classic  metadata terms, known as the Dublin Core Metadata Element Set  are endorsed in the following standards documents: Microformats lower the barrier to entry. Most digital cameras write metadata about model number, shutter speed, etc. Metadata can be used to make organizing in post-production easier with the use of key-wording. Filters can be used to analyze a specific set of photographs and create selections on criteria like rating or capture time.
Photographic Metadata Standards are governed by organizations that develop the following standards. They include, but are not limited to: Telecommunications[ edit ] Information on the times, origins and destinations of phone calls, electronic messages, instant messages and other modes of telecommunication, as opposed to message content, is another form of metadata.
Bulk collection of this call detail record metadata by intelligence agencies has proven controversial after disclosures by Edward Snowden of the fact that certain Intelligence agencies such as the NSA had been and perhaps still are keeping online metadata on millions of internet user for up to a year, regardless of whether or not they [ever] were persons of interest to the agency. Video[ edit ] Metadata is particularly useful in video, where information about its contents such as transcripts of conversations and text descriptions of its scenes is not directly understandable by a computer, but where efficient search of the content is desirable.
This is particularly useful in video applications such as Automatic Number Plate Recognition and Vehicle Recognition Identification software, wherein license plate data is saved and used to create reports and alerts.