Abstract: Embodiments relate to processing a data set stored in a computer system. In one aspect, a method of processing a data set stored in a computer system includes providing one or more parameters for quantifying data quality of the data set. A processor generates, for each parameter of the one or more parameters, a reference pattern indicating a dysfunctional behavior of the values of the parameter. The data set is processed to obtain values of the one or more parameters. A parameter of the one or more parameters is identified whose obtained values match a corresponding reference pattern of the generated reference patterns. The identified parameter is assigned a resource weight value indicating the amount of processing resources required to fix the dysfunctional behavior of the identified parameter.

Abstract: The invention relates to a computer-implemented method for user authentication using a cryptographically secured register. An authentication request for authenticating the user is received. The user is authenticated using a root identity of the user. A successful authentication requires receiving a credential assigned to a root identifier of the root identity of the user. An authentication context of the requested authentication is identified. One of the one or more delegated identities assigned to the root identity of the user and assigned to the identified authentication context is identified. In response to a successful authentication of the user, an authentication token is issued confirming the successful user authentication and identifying the successfully authenticated user by the delegated identifier of the identified delegated identity.

Abstract: A computer implemented method for classifying at least one source dataset of a computer system. The method may include providing a plurality of associated reference tables organized and associated in accordance with a reference storage model in the computer system. The method may also include calculating, by a data classifier application of the computer system, a first similarity score between the source dataset and a first reference table of the reference tables based on common attributes in the source dataset and a join of the first reference table with at least one further reference table of the reference tables having a relationship with the first reference table. The method may further include classifying, by the data classifier application, the source dataset by determining using at least the calculated first similarity score whether the source dataset is organized as the first reference table in accordance to the reference storage model.

Abstract: The present disclosure relates to a method for a secure storage, matching and linking of data records. The method comprises: receiving a current data record having one or more attributes, each attribute having an attribute value. For each attribute of at least part of the attributes a predefined set of variations of the attribute value of the attribute may be generated. The received attribute values may be encrypted resulting in an encrypted record and the generated sets of variations may be encrypted. The encrypted record may be stores in a storage system in association with the respective encrypted sets of variations.

Abstract: A computer-implemented method includes generating, by a computer device, a plurality of clusters of unmanned aerial vehicles (UAVs) from a plurality of UAVs having different UAV characteristics, the clusters being generated based on the UAV characteristics of each of the UAVs; determining, by the computer device, task characteristics for a first task; selecting, by the computer device, one of the clusters based on the task characteristics of the first task; assigning to the first task, by the computer device, a first UAV of the plurality of UAVs from the selected cluster; receiving, by the computer device, task feedback regarding an attempt by the first UAV to complete the first task; and reassigning, by the computer device, and based on the task feedback, the first UAV to a determined one of the plurality of clusters.

Abstract: The present disclosure relates to a method for enabling data integration. The method comprises collecting matching results of matching of records by a matching component over a time window. The number of false tasks of user defined tasks and system defined tasks in the collected matching results may be determined. The matching criterion used by the matching component may be adjusted to minimize the number of user defined tasks while the fraction of false tasks stays within a certain limit. The matching criterion may be replaced by the adjusted matching criterion for further usage of the matching component.

Abstract: The invention relates to a computer-implemented method for user authentication using a cryptographically secured register. An authentication request for authenticating the user is received. The user is authenticated using a root identity of the user. A successful authentication requires receiving a credential assigned to a root identifier of the root identity of the user. An authentication context of the requested authentication is identified. One of the one or more delegated identities assigned to the root identity of the user and assigned to the identified authentication context is identified. In response to a successful authentication of the user, an authentication token is issued confirming the successful user authentication and identifying the successfully authenticated user by the delegated identifier of the identified delegated identity.

Abstract: The present disclosure relates to a method for centrally processing data records using a record linkage algorithm. The method comprises providing a centralized master repository for storing data records in a predefined data structure having a set of attributes. At least one clustering metric is provided. Clusters of records may be determined using a clustering function that is based on the at least one clustering metric. For each particular cluster, a set of configuration data for the record linkage algorithm may be defined based on a value of the clustering metric within that particular cluster. The individual data records may be assigned to one or more clusters of the clusters using the clustering metric values and the record linkage algorithm may be applied to a set of two or more individual data records assigned to at least one common cluster using the set of configuration data for the common cluster.

Abstract: The present disclosure relates to a method for centrally processing data records using a record linkage algorithm. The method comprises providing a centralized master repository for storing data records in a predefined data structure having a set of attributes. At least one clustering metric is provided. Clusters of records may be determined using a clustering function that is based on the at least one clustering metric. For each particular cluster, a set of configuration data for the record linkage algorithm may be defined based on a value of the clustering metric within that particular cluster. The individual data records may be assigned to one or more clusters of the clusters using the clustering metric values and the record linkage algorithm may be applied to a set of two or more individual data records assigned to at least one common cluster using the set of configuration data for the common cluster.

Abstract: A system and method are provided for predicting a signal strength for a specific location. The method includes operations for predicting mobile device signal strength by building a database of mobile signal information. The mobile signal information includes signal strength for a plurality of mobile devices located at a plurality of three-dimensional, geospatial coordinates and utilizing a plurality of mobile signal providers/carriers. The method predicts, using the database, a signal strength for a particular mobile device at a particular set of three-dimensional, geospatial coordinates utilizing a particular mobile signal provider/carrier and displays the prediction at a specific time.

Abstract: A computer implemented method for classifying at least one source dataset of a computer system. The method may include providing a plurality of associated reference tables organized and associated in accordance with a reference storage model in the computer system. The method may also include calculating, by a data classifier application of the computer system, a first similarity score between the source dataset and a first reference table of the reference tables based on common attributes in the source dataset and a join of the first reference table with at least one further reference table of the reference tables having a relationship with the first reference table. The method may further include classifying, by the data classifier application, the source dataset by determining using at least the calculated first similarity score whether the source dataset is organized as the first reference table in accordance to the reference storage model.

Abstract: An ontology is automatically generated for a set of data from multiple data sources. A semantic network of known concepts serves as an ontology template for a target domain of knowledge with known concepts defined as base entity types. Logical groupings of data and associated technical metadata are read from the data sources. Data discovery techniques are applied to detect semantic and/or syntactic classification of data attributes in the logical groupings of data. For each of the logical groupings of data, an entity type with properties for the data attributes are generated and the generated entity type is added to the semantic network with classifications of the properties as derived from the applied data discovery techniques. Semantic meanings of the generated entity types are generated and associated with other entity types within the semantic network and the semantic network is output as a resultant ontology for the set of data.

Abstract: An example operation may include one or more of identifying a request for a service in an enterprise network, responsive to identifying the request for the service, creating a service request message that includes user profile role information for authorization purposes, creating a blockchain transaction based on the service request message, and responsive to creation of the blockchain transaction, determining audit trail information exists based on audit trail requirements stored in a smart contract, and the audit trail information includes user profile authentication information and the user profile role information.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for processing suspect duplicate records in a master data management system. A master data management module identifies two or more suspect duplicate records in the master data management system based on scores. A matching engine classifies the two or more suspect duplicate records, by comparing the scores against threshold values, into one of: a match, a non-match, and a possible match. The master data management module re-classifies the suspect duplicate records and adjusting the threshold values of the matching engine for classification of future records, in response to receiving, by a data stewardship client, a user input indicating an incorrect classification of the suspect duplicate records.

Abstract: Ontologies are used to comprehend regular expressions, by selecting, based on a context relating to a domain of a regular expression, an ontology and an assertion base, parsing the regular expression to identify at least one fragment of the regular expression, identifying one or more assertions in the assertion base corresponding to one of the identified fragments, identifying, for each identified assertion, an associated node in the ontology, and returning, based on the associated nodes, a concept in the ontology as representing the associated fragment of the regular expression.

Abstract: The present disclosure relates to a method for data anonymization of a database system. The method comprises: determining if a first dataset and second dataset of the database system have a relationship indicative of an entity having values in the two datasets. A request may be received from a user for at least one of the first and second datasets. In case the first dataset and second dataset have the relationship, at least one of the first and second datasets may be modified such that the indication of the entity is not accessible to the user. And the requested dataset may be provided.

Abstract: A method, computer system, and a computer program product for smart validation of suspicious activity reports is provided. The present invention may include receiving a plurality of suspicious activity data from a reporting software. The present invention may also include analyzing the plurality of suspicious activity data using a plurality of analytics, wherein the analysis validates the plurality of stored suspicious activity data using the plurality of analytics. The present invention may then include providing feedback to a user based on the analyzed plurality of suspicious activity.

Abstract: The invention relates to a computer-implemented method for user authentication using a cryptographically secured register. An authentication request for authenticating the user is received. The user is authenticated using a root identity of the user. A successful authentication requires receiving a credential assigned to a root identifier of the root identity of the user. An authentication context of the requested authentication is identified. One of the one or more delegated identities assigned to the root identity of the user and assigned to the identified authentication context is identified. In response to a successful authentication of the user, an authentication token is issued confirming the successful user authentication and identifying the successfully authenticated user by the delegated identifier of the identified delegated identity.

Abstract: The invention relates to a computer-implemented method for classifying a set of data values. For each of the data values of the set of data values, a set of one or more terms associated with the respective data value is determined using one or more first knowledge bases. A set of common terms is determined. The set of common terms comprises terms present in more than one of the sets of terms. For each of the common terms, a number of hits for a lookup query against one or more second knowledge data bases is determined. One or more common terms of the set of common terms with the smallest number of hits are determined and a result is returned. The result comprises the one or more common terms with the smallest number of hits as one or more candidate classes for classifying the set of data values.

Abstract: A computer implemented method for data anonymization comprises: receiving a request for data that needs anonymization. The request comprises at least one field descriptor of data to be retrieved and a usage scenario of a user for the requested data. Then, based on the usage scenario, an anonymization algorithm to be applied to the data that is referred to by the field descriptor is determined. Subsequently, the determined anonymization algorithm is applied to the data that is referred to by the field descriptor. A testing is performed, as to whether the degree of anonymization fulfills a requirement that is related to the usage scenario. In the case, the requirement is fulfilled, access to the anonymized data is provided.