Abstract: Disclosed herein is a translation platform making use of both machine translation and crowd sourced manual translation. Translation is performed on pages in an application. Manual translations are applied immediately to local versions of the client application and are either human reviewed or reverse machine translated and compared against the original text. Once verified, the translations are applied to all end-clients.

Abstract: Various embodiments relate to data science and data analysis, computer software and systems, and computing architectures and data models configured to facilitate management of enterprise functions, and, more specifically, to an enterprise computing and data processing platform configured to activate risk management transformations of enterprise data in-situ, responsive to identifying a risk event, and further configured to implement a risk management data channel to facilitate analyses and responses associated with an enterprise computing device. In some examples, a method may include receiving a risk data signal, identifying a portion of the risk data signal, computing data representing a risk level, classifying data associated with a hierarchical business data object in accordance with a risk level, aggregating classified data with other data associated with other business data objects classified as a function of risk to form aggregated data, causing presentation of aggregated data as a function of risk.

Abstract: Various embodiments include a computer-implemented method performed by an optimization engine. The method can include receiving a request to deploy a resource for one of multiple service lines, where each service line is operable independent of the other, the resource belongs to a pool of resources, and each resource has learned features regarding suitability for any of the service lines. The method can further include mediating the request to identify suitable resource(s) that satisfy the request, where suitability is determined based on the learned features output by a machine learning model based on inputs indicative of interactions between the plurality of service lines and the pool of resources. The method can further include deploying an identified resource that satisfies the request for the service line, wherein the identified resource is deployable among at least two or more of the service lines.

Abstract: Disclosed herein is a translation platform making use of both machine translation and crowd sourced manual translation. Translation is performed on pages in an application. Manual translations are applied immediately to local versions of the client application and are either human reviewed or reverse machine translated and compared against the original text. Once verified, the translations are applied to all end-clients.

Abstract: Disclosed herein is a translation platform making use of both machine translation and crowd sourced manual translation. Translation is performed on pages in an application. Manual translations are applied immediately to local versions of the client application and are either human reviewed or reverse machine translated and compared against the original text. Once verified, the translations are applied to all end-clients.

Abstract: Disclosed herein is a translation platform making use of both machine translation and crowd sourced manual translation. Translation is performed on pages in an application. Manual translations are applied immediately to local versions of the client application and are either human reviewed or reverse machine translated and compared against the original text. Once verified, the translations are applied to all end-clients.

Abstract: Management of metadata applied to life cycle inventory (LCI) and life cycle assessment (LCA) data is provided. Life cycle inventory data may be provided through a secure framework to a data hub where it may be validated and audited and where the received life cycle inventory data may ultimately be used to generate a life cycle assessment score for a given product. Life cycle inventory data may be provided via a structured data template provided by a supplier or obtained by a supplier via a requested unit business process model. Metadata may be applied to each LCI data item to allow the data items to be stored, sorted, search, retrieved and used for validating and auditing the data and for comparing the data to other data items of similar data types for eventual use in the generation of the aforementioned life cycle assessment score for a given product.

Abstract: User interfaces are provided for submitting and obtaining life cycle inventory and assessment data. Suppliers of goods and/or services may provide life cycle inventory data via a user interface component through a secure framework to a life cycle inventory and assessment data hub for validation and auditing. Access to the life cycle inventory and assessment data hub may be through a web services platform for allowing the suppliers secured access to the data and functionality of the data hub. Suppliers and end users may access the data hub via the web services platform using one or more LCI/LCIA user interfaces for obtaining validated and audited life cycle inventory data and for obtaining generated and/or aggregated life cycle assessment scores for one or more goods and/or services.

Abstract: Aggregation of life cycle impact assessment data and generation of life cycle impact assessment and scoring for goods and/or services or for components of goods and/or services are provided. Life cycle inventory data for components of goods and/or services are validated and audited to determine their available use in the generation of life cycle impact assessments for the goods and/or services. Life cycle impact assessments (LCIA) and LCIA scores are generated for each component or phase of production, use or disposal of a given good and/or service. LCIAs and LCIA scores for each component or phase are aggregated together and composite LCIAs and LCIA scores are generated for the good and/or service. The generated LCIAs and LCIA scores may be exposed to consumers, and the LCIAs and LCIA scores may be updated periodically as required to account for changes in LCI data for the scored good and/or service.

Abstract: Collection of life cycle inventory (“LCI”) data for all phases of the life of goods and/or services is provided. Suppliers of goods and/or services may log into a LCI and assessment data hub via one or more access points for entering LCI data on all phases of development, production use and/or disposal of their goods and/or services. Access to the data hub, as a central data collection point, requires authentication of accessing suppliers via a security framework associated with the data hub. LCI data may be provided via a structured data template, or raw business or business transaction data may be entered in association with a unit process model requested by the supplier.

Abstract: Management of metadata applied to life cycle inventory (LCI) and life cycle assessment (LCA) data is provided. Life cycle inventory data may be provided through a secure framework to a data hub where it may be validated and audited and where the received life cycle inventory data may ultimately be used to generate a life cycle assessment score for a given product. Life cycle inventory data may be provided via a structured data template provided by a supplier or obtained by a supplier via a requested unit business process model. Metadata may be applied to each LCI data item to allow the data items to be stored, sorted, search, retrieved and used for validating and auditing the data and for comparing the data to other data items of similar data types for eventual use in the generation of the aforementioned life cycle assessment score for a given product.