Edward P Calusinski

US Patent:

20060235715, Oct 19, 2006

Filed:

Dec 22, 2005

Appl. No.:

11/318428

Inventors:

Carl Abrams - Briarcliff Manor NY, US
Ronald Adinolfi - Yardley PA, US
Edward Calusinski - Bartlett IL, US
Cornelius Crowley - Morristown NJ, US
Michael Fleming - Eastchester NY, US
Teresa Glasser - New York NY, US
Jennifer Gromada - Princeton NJ, US
Max Hrabrov - Brooklyn NY, US
Guerney Hunt - Yorktown Heights NY, US
Kenneth Jones - Lansdale PA, US
Sugandh Mehta - Wayne NJ, US
Francis Parr - New York NY, US
Aviv Orani - Highland Park NJ, US
Matthew Rice - Medway MA, US

International Classification:

G06Q 99/00

US Classification:

705001000

Abstract:

A multi-source multi-tenant reference data utility and methods for forming and maintaining the same, delivering high quality reference data in response to requests from clients, implemented using a shared infrastructure, and also providing added value services using the client's reference data. Included are data cleansing and quality assurance of the received data with full tracking of the sourcing of each value, storage of resulting entity values in a repository which allows retrievals and enforces source based entitlements, and delivery of retrieved data in the form of on demand datasets supporting a wide range of client application needs. An advantageous implementation has additional services for reporting on data quality and usage, a selection of value adding data driven computations and business document storage. By using a shared infrastructure and amortizing the costs of data quality assurance across a plurality of clients, while ensuring that clients only receive values from data sources to which they are licensed, better quality data at lower cost is delivered.

US Patent:

20060247944, Nov 2, 2006

Filed:

Dec 22, 2005

Appl. No.:

11/318425

Inventors:

Edward Calusinski - Bartlett IL, US
Cornelius Crowley - Morristown NJ, US
Teresa Glasser - New York NY, US
Jennifer Gromada - Princeton NJ, US
Max Hrabrov - Brooklyn NY, US
Guerney Hunt - Yorktown Heights NY, US
Kenneth Jones - Lansdale PA, US
Sugandh Mehta - Wayne NJ, US
Francis Parr - New York NY, US
Aviv Orani - Highland Park NJ, US

International Classification:

G06Q 99/00
G06Q 40/00

US Classification:

705001000, 705035000

Abstract:

Provision for scalable cleansing and value enhancement of data in the context of a multi-source multi-tenant data repository. The source data comes from multiple sources and on multiple topics. Evolutionarily tracked source data tags are used to hold tracking information reflecting the nature and sources of each change to the data, as it is affected during the various stages of data processing. The stages of processing include validation, normalization, single-source cleansing and cross-source processes. Various rules are applied during these stages, and evolutionarily tracked source data tags are used to record sources and agents of all changes to the data. As information is processed, transformed, and added to the repository, corresponding evolutionarily tracked source data tags are stored in association with the various information elements. The information contained in these tags can be used to enforce data entitlements in a multi-tenant data repository environment.

US Patent:

20060235714, Oct 19, 2006

Filed:

Dec 22, 2005

Appl. No.:

11/318426

Inventors:

Ronald Adinolfi - Yardley PA, US
Edward Calusinski - Bartlett IL, US
Cornelius Crowley - Morristown NJ, US
Teresa Glasser - New York NY, US
Jennifer Gromada - Princeton NJ, US
Max Hrabrov - Brooklyn NY, US
Guerney Hunt - Yorktown Heights NY, US
Sugandh Mehta - Wayne NJ, US
Francis Parr - New York NY, US
Matthew Rice - Medway MA, US

International Classification:

G06Q 99/00

US Classification:

705001000

Abstract:

A method, apparatus and software for responding to a request for an on demand dataset by configuring and then executing a workflow process tailored to the requester's needs. The generated workflow gathers identified information from a repository, organizes its format and delivers it to the requester. The on demand dataset request specification is structured to allow independent specification of (1) data to be included, (2) policy on which value sources to use; (3) delivery mode—including real-time, batched, and one-time query modes, (4) output format, and (5) delivery and communications protocols and other on demand dataset properties. This separation of concerns allows a wide variety of on demand data set requirements from different requesters to be met. Delivery of information from an outsourced multi-source multi-tenant data repository to its tenants is a context in which the method is useful.