Sap Ag

Sap Se

Gunther Stuhec

Jens Lemcke

Markus A Peter

Gerd Ritter

Daniel Buchmann

Renzo Colle

Michael Seubert

Paola Sala

Stephan Hetzer

Werner Gnan

Joachim Kenntner

Thilo Kraehmer

Gregor Rieken

Johann Kemmer

Toralf Grossmann

Thomas Nitschke

Andreas Bold

Tao Yu

Georg Podhajsky

Antonia Gross

Markus Biehler

Matthias Schmitt

Andre Wagner

Andreas Brossler

Wolfgang Nieswand

Andreas F Morsch

Christoph Lehner

Thomas Maag

Rudolf Winkel

Stefan Elfner

Otto Makris

Ralf Sievers

Michael Zoeller

Jochen A Rasch

Axel Kuehl

Volker Jaeck

Uwe Pyka

Ruediger Radcke

Daniela Schapler

Andreas Schneider

Michael P Dietrich

Frank Thome

Dagmar Schultze

Karsten Koetter

Corinne Kuster

Dominic Poetschke

Jens Zachmann

Theo Zimmerman

Gabriel Alvarez

Gerhard Gschwender

Joerg Hendricks

Wolf Hengevoss

Christine Hofmann

Bernhard Kelnberger

Volker Wiechers

Dietmar Nowotny

Karsten K Bohlmann

Daniel Bock

Robert Doerner

Arnulf Schueler

Stefan Adelmann

Stefan Franke

Volker Ripp

Renato Zadro

Adam Kiwon

Werner Liebold

Nathali Ortiz Suarez

Reiner Seyler

Florian Gessner

Frank Brunswig

Thomas Fiedler

Daniel Oberle

Wolfgang Pfeifer

Karl Christian Roediger

Frank Damaschke

Juergen Denner

Patrick Gross

Frank Reinemuth

Dirk Weissmann

Armulf Schueler

Dotchka Pentcheva

Helmut K Glaenzer

Martin Möller

Muhammad Wasimullah Khan

Enterprises express the concepts of their electronic business-to-business (B2B) communication in differently structured ontology-like schemas. Collaborations benefit from merging the common concepts into semantically unique Business Entities (BEs) in a merged schema. Methods and systems for labeling the merged schema with descriptive, yet short and unique names, are described. A heuristically ranked list of descriptive candidate phrases for each BE is derived locally from the names and descriptions of the underlying concepts. A semantically unique candidate phrase is assigned to each BE that discriminates it from the other BEs by employing a constraint satisfaction problem solver.

Labeling entities in a canonical data model

Techniques for managing communication between businesses include defining a plurality of business context parameters associated with a first entity and a second entity; retrieving a first set of business requirements from a first entity and a second set of business requirements from a second entity based on the business context parameters; generating a message implementation guideline including one or more source elements associated with the first set of business requirements; receiving a second message implementation guideline including one or more target elements from the second entity; and generating a mapping guideline including mapping entities between the one or more source elements and the one or more target elements.

Streamlining end-to-end flow of business-to-business integration processes

Techniques for managing communication between businesses include selecting a source message guideline including a first plurality of elements; selecting a target message guideline including a second plurality of elements; selecting a business context corresponding to the source message guideline; generating a plurality of potential mapping entities between the first plurality of elements and the second plurality of elements; and selecting mapping entities from the plurality of potential mapping entities based on an accuracy threshold of the mapping entities.

Mapping for collaborative contribution

Labelling entities in a canonical data model

The present disclosure describes methods, systems, and computer program products for providing and maintaining an evolving canonical data model (CDM) which consolidates current knowledge of the correspondences of existing schemas. One computer-implemented method includes receiving the plurality of source hierarchical schemas, each source hierarchical schema being stored as a computer-readable document in computer-readable memory, processing, using a computer, the source hierarchical schemas to generate a merged graph, the merged graph comprising a plurality of merged nodes, each merged node being provided based on one or more nodes from at least two of the source hierarchical schemas, and determining, using the computer, that the merged graph includes one or more conflicts and, in response, resolving each conflict of the one or more conflicts to generate a computed-transitive-edge-free, conflict-free merged graph as a unified data model (UDM), wherein resolving comprises splitting one or more merged nodes into respective sub-sets of merged nodes.

Canonical data model for iterative effort reduction in business-to-business schema integration

Methods, systems, and computer-readable storage media for user-guided multi-schema integration and include actions of receiving a plurality of schemas, each schema defining a data structure and including a plurality of intermediate elements and a plurality of leaf elements, receiving leaf correspondences that match leaf elements between schemas of the plurality of schemas, processing the plurality of schemas and the leaf correspondences using closed frequent itemset mining to define a first plurality of redundancy groups, each redundancy group including a proposed correspondence between intermediate elements of schemas, displaying the first plurality of redundancy groups to a user, receiving user input, the user input including one or more actions to one or more redundancy groups in the first plurality of redundancy groups, processing the plurality of schemas, the leaf correspondences and the one or more actions to define a second plurality of redundancy groups, and displaying the second plurality of redundancy groups.

User-guided multi-schema integration

A name of one or more entity classes of the data model may be refined to conform to a naming convention. A semantic meaning of each of the names and one or more attributes of each entity class may be determined. It may be determined that the name of a first entity class is semantically similar to the name of a second entity class based on a semantic distance between the semantic meaning of the names, where a substantial similarity may be determined between the first entity class and the second entity class by comparing the semantic meaning of the one or more attributes of the first entity class to the semantic meaning of the one or more attributes of the second entity class. The data model may be normalized based on the substantial similarity.

Data model optimization

A method for building dictionary entry names for data elements of a canonical data model includes identifying candidate terms for the dictionary entry name of a node or equivalence class of the canonical data model. The method includes counting a frequency of occurrence of candidate terms in use and based on the use counts creating a candidate ordering of terms for the complete ordered dictionary entry name of the node or equivalence class. The method further includes validating the candidate ordering of terms for the complete ordered dictionary entry name of the node or equivalence class by comparison of the ordering with reliable dictionary entry name entries in a database and/or by usage counts in search engine results.

Dictionary entry name generator

Methods and systems consistent with the present invention provide a data processing system having a business object model reflecting the data used during a business transaction. Consistent interfaces are generated from the business object model. These interfaces are suitable for use across industries, across businesses, and across different departments within a business during a business transaction.

Consistent set of interfaces derived from a business object model

Methods, systems, and computer-readable storage media for receiving a plurality of source hierarchical schemas, processing the source hierarchical schemas to generate a merged graph, which is comprising a plurality of merged nodes, each merged node being provided based on one or more nodes from at least two of the source hierarchical schemas, determining and resolving using conflicts in the merged graph to generate a conflict-free merged graph, wherein resolving comprises splitting one or more merged nodes into respective sub-sets of merged nodes, defining and processing a constraints satisfaction problem (CSP) to generate a plurality of mediated hierarchical schemas (MHSs), each MHS being a solution to the CSP, identifying an MHS of the plurality of MHSs as an optimum MHS, wherein a canonical hierarchical schema (CHS) is provided as the optimum MHS, and storing the CHS as a computer-readable document in a computer-readable memory.

Computing canonical hierarchical schemas

Operations for generating a unique name for at least one of several data elements include receiving a definition of a data element for which a unique name is to be created. The unique name is to comply with a predefined name format. The definition comprises human-understandable descriptive language. The data element is to identify an information category in an electronic communication. A noun phrase and a verb phrase are identified in the definition, and the unique name is generated using a first noun obtained from the noun phrase and a second noun obtained from the verb phrase. A computer system includes a repository having the data elements stored therein, and a name generating module that receives at least one of the definitions that is associated with one of the data elements and generates a unique name for the data element.

Generating a unique name for a data element

In general, the subject matter described in this specification can be embodied in methods, systems, and program products for discovering information that is related to a unique object identifier from a decentralized collection of computing systems. A unique object identifier is identified. A first information request that includes the unique object identifier is forwarded to a first computing system. First information that the first computing system has stored in association with the unique object identifier is received from the first computing system. An identifier for a second computing system is received from the first computing system in response to the first information request. A second information request that includes the unique object identifier is forwarded to the second computing system based on the received identifier. Second information that the second computing system has stored in association with the unique object identifier is received from the second computing system.

Registering and discovering unique identifiers

Growing community of inventors

Heidelberg, Germany

Gunther Stuhec