International Business Machines Corporation

Guenter Anton Sauter

Charles Daniel Wolfson

Brian Patrick Byrne

Hayden Marchant

Chung-Sheng Li

Ivan Matthew Milman

Harald Clyde Smith

Sushain Pandit

Brent P Gross

Michael R Self

Frederick L White

Aris Gkoulalas-Divanis

Mei Yang Selvage

Peter Alan Coldicott

Mary Ann Roth

Holger Kache

Olaf W Zimmermann

Benjamin Honzal

An initiation of an emergency communication with an emergency service associated with an emergency telephone number is detected by a mobile communications device. A completion of the emergency communication using a first communication path associated with a mobile communications service provider is attempted. The mobile communication device determines that the emergency communication using the first communication path has failed. An identity of a destination of the failed emergency communication is determined using location and telemetry data from the mobile communication device. A connection of the mobile communications device to the identified destination is facilitated using a second communication path. The mobile communications device is identified to the determined destination as an originator of the connection.

Emergency call service backup using device user plane communications

Managing and validating a project using an information landscape. Embodiments include providing an information landscape including a topology of landscape elements for the project, linking the topology of landscape elements to a plurality of solution artifacts, and validating at least one of the plurality of solution artifacts and semantics of the information landscape.

Information landscape modeling, analysis and validation

A system, method and computer program product for anonymizing data. Datasets anonymized according to the method have a relational part having multiple tables of relational data, and a sequential part having tables of time-ordered data. The sequential part may include data representing a 'sequences-of-sequences'. A 'sequence-of-sequences' is a sequence which, itself, consists of a number of sequences. Each of these kinds of data may be anonymized using k-anonymization techniques and offers privacy protection to individuals or entities from attackers whose knowledge spans the two (or more) kinds of attribute data.

Anonymization for data having a relational part and sequential part

An information integrity rules framework manages rules across heterogeneous enforcement systems by managing canonical rules that are mapped to native rules and enforcement system-specific rules. The information integrity rules framework discovers an existing native rule utilized by an enforcement system, which is written in an enforcement system-specific format. Next, the information integrity rules framework creates a mapping entry and maps the native rule to a canonical rule, which is independent from the enforcement system. When the information integrity rules framework detects a change to one of the rules managed by the framework, the information integrity rules framework propagates the change to other corresponding rules across enforcement systems managed by the framework.

Information integrity rules framework

An approach is provided for selecting one or more trust factors from trust factors included in a trust index repository. Thresholds are identified corresponding to one or more of the selected trust factors. Actions are identified to perform when the selected trust factors reach the corresponding threshold values. The identified thresholds, identified actions, and selected trust factors are stored in a data store. The selected trust factors are monitored by comparing one or more trust metadata scores with the stored identified thresholds. The stored identified actions that correspond to the selected trust factors are performed when one or more of the trust metadata scores reach the identified thresholds. At least one of the actions includes an event notification that is provided to a trust data consumer.

Trust event notification and actions based on thresholds and associated trust metadata scores

An approach is provided for selecting a trust factor from trust factors that are included in a trust index repository. A trust metaphor is associated with the selected trust factor. The trust metaphor includes various context values. Range values are received and the trust metaphor, context values, and range values are associated with the selected trust factor. A request is received from a data consumer, the request corresponding to a trust factor metadata score that is associated with the selected trust factor. The trust factor metadata score is retrieved and matched with the range values. The matching results in one of the context values being selected based on the retrieved trust factor metadata score. The selected context value is then provided to the data consumer.

Configurable trust context assignable to facts and associated trust metadata

Evaluating and prioritizing architectural design pattern alternatives for data integration is provided. A set of decision factors is derived from requirements for a system to be integrated. A default score is assigned to each decision factor based on historical data integration knowledge, and the default scores are weighted. A priority score is also assigned to each decision factor based on collected inputs from system metadata and subject matter experts in the enterprise system. Next, an individual consolidated score for each decision factor is calculated using the default score, the weighted score, and the priority score, and a total consolidated score is calculated from the individual consolidated scores for the architecture design pattern. The total consolidated score for the architecture design pattern may be compared against total consolidated scores for other architecture design patterns to determine a suitable candidate architecture design pattern for data integration.

Semi-automatic evaluation and prioritization of architectural alternatives for data integration

An approach is provided in which atomic trust scores are computed using a atomic trust factors that are applied to a plurality of metadata. A first set of composite trust scores are computed using some of the atomic trust scores. The composite trust scores are computed using a first set of algorithms. Some of the algorithms use a factor weighting value as input to the algorithm. A second plurality of composite trust scores is computed using some of the composite trust scores that were included in the first set of scores as input. A fact and one of the second set of composite trust scores are presented to a user. The presented composite trust score provides a trustworthiness value that corresponds to the presented fact.

Generating composite trust value scores, and atomic metadata values and associated composite trust value scores using a plurality of algorithms

Methods, systems, and articles of manufacture for constructing and populating data marts with dimensional data models from a set of data repositories that contain factual and association information about a set of related assets are disclosed. An intermediate data warehouse is generated to process the facts and associations for each asset. Using the intermediate warehouse, one or more data marts are generated with fact tables, dimensions, and hierarchies to fully model the information available for each asset.

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Ridgefield, CT, United States of America

Guenter Anton Sauter