Abstract: Mechanisms are provided to implement a multi-layer analytics framework. The multi-layer analytics framework obtains a plurality of analytics from one or more analytics source computing systems, at least two analytics being written in different computer programming languages. The multi-layer analytics framework applies a wrapper to each of the analytics in the plurality of analytics to thereby generate wrapped analytics. The wrapper provides a unified interface for executing the analytics in the plurality of analytics regardless of the particular computer programming language used to create the analytics. The multi-layer analytics framework registers the wrapped analytics in an analytics registry, and executes an analytics pipeline comprising wrapped analytics in the analytics registry to perform an analytics operation based on the unified interface of the wrappers of the wrapped analytics.

Abstract: A multi-layer analytics framework is provided that obtains a plurality of analytics from one or more analytics source computing systems. The framework applies a wrapper to each of the analytics, where the wrapper provides a unified interface for executing the analytics regardless of the particular computer programming language used to create the analytics. The framework registers the wrapped analytics in an analytics registry, receives a request to perform an analytics operation on an input dataset, from a request computing system, and automatically generates an analytics pipeline comprising a plurality of wrapped analytics retrieved from the analytics registry. The framework executes the analytics pipeline and returns results of executing the analytics pipeline to the requestor computing system.

Abstract: Mechanisms are provided to implement a multi-layer analytics framework. The multi-layer analytics framework obtains a plurality of analytics from one or more analytics source computing systems, at least two analytics being written in different computer programming languages. The multi-layer analytics framework applies a wrapper to each of the analytics in the plurality of analytics to thereby generate wrapped analytics. The wrapper provides a unified interface for executing the analytics in the plurality of analytics regardless of the particular computer programming language used to create the analytics. The multi-layer analytics framework registers the wrapped analytics in an analytics registry, and executes an analytics pipeline comprising wrapped analytics in the analytics registry to perform an analytics operation based on the unified interface of the wrappers of the wrapped analytics.

Abstract: Mechanisms are provided to implement a multi-layer analytics framework. The multi-layer analytics framework obtains a plurality of analytics from one or more analytics source computing systems, at least two analytics being written in different computer programming languages. The multi-layer analytics framework applies a wrapper to each of the analytics in the plurality of analytics to thereby generate wrapped analytics. The wrapper provides a unified interface for executing the analytics in the plurality of analytics regardless of the particular computer programming language used to create the analytics. The multi-layer analytics framework registers the wrapped analytics in an analytics registry, and executes an analytics pipeline comprising wrapped analytics in the analytics registry to perform an analytics operation based on the unified interface of the wrappers of the wrapped analytics.

Abstract: Systems and methods for remotely provisioning software to process data stored in a virtualized storage environment are provided. In one embodiment, the method comprises receiving a request, at a first location, for processing data using a software application, wherein the data is stored in a virtualized storage space at a second location and the software application is invoked in a virtualized computing environment at a third location; using a service at the first location to remotely invoke one or more instances of the software application over the virtualized computing environment at the third location; and using the service at the first location to remotely manage transfer of data stored in the virtualized storage space at the second location to the third location.

Abstract: A multi-layer analytics framework is provided that obtains a plurality of analytics from one or more analytics source computing systems. The framework applies a wrapper to each of the analytics, where the wrapper provides a unified interface for executing the analytics regardless of the particular computer programming language used to create the analytics. The framework registers the wrapped analytics in an analytics registry, receives a request to perform an analytics operation on an input dataset, from a request computing system, and automatically generates an analytics pipeline comprising a plurality of wrapped analytics retrieved from the analytics registry. The framework executes the analytics pipeline and returns results of executing the analytics pipeline to the requestor computing system.

Abstract: Mechanisms are provided to implement a multi-layer analytics framework. The multi-layer analytics framework obtains a plurality of analytics from one or more analytics source computing systems, at least two analytics being written in different computer programming languages. The multi-layer analytics framework applies a wrapper to each of the analytics in the plurality of analytics to thereby generate wrapped analytics. The wrapper provides a unified interface for executing the analytics in the plurality of analytics regardless of the particular computer programming language used to create the analytics. The multi-layer analytics framework registers the wrapped analytics in an analytics registry, and executes an analytics pipeline comprising wrapped analytics in the analytics registry to perform an analytics operation based on the unified interface of the wrappers of the wrapped analytics.

Abstract: Machines, systems and methods for dynamically implementing storlets in a storage data path. The method comprises receiving a request to perform a storage-related function on data stored on a first data storage medium in a data storage system; verifying the request by way of an authentication and authorization mechanism to prevent unauthorized access to data stored on the first data storage medium in the data storage system; and utilizing a storlet to service the request, wherein the storlet is dynamically deployed on a node in the data storage system such that the node has sufficient resources to support the storlet to service the request.

Abstract: Machines, systems and methods for dynamically implementing storlets in a storage data path. The method comprises receiving a request to perform a storage-related function on data stored on a first data storage medium in a data storage system; verifying the request by way of an authentication and authorization mechanism to prevent unauthorized access to data stored on the first data storage medium in the data storage system; and utilizing a storlet to service the request, wherein the storlet is dynamically deployed on a node in the data storage system such that the node has sufficient resources to support the storlet to service the request.

Abstract: Machines, systems and methods for sanitizing data are provided. The method comprises determining whether a data request is submitted by an authorized user, in response to receiving the data request, wherein the data request is for accessing first data stored on a data storage system; in response to determining that the data request is submitted by an authorized user, analyzing data access history by the user to the data storage system; in response to determining that the user has previously accessed data on the data storage system that in light of the first data reveal confidential information which the user is not authorized to access, restricting user's access to the confidential information.

Abstract: Systems and methods for optimal data storage are provided. The method comprises storing data objects that are most closely related in a storage container by modeling a constraint satisfaction problem for placement of said data objects in one or more storage containers, wherein a weight is assigned to an edge connecting two data objects based on an association defining relationships between the two data objects connected by said edge, taking into account certain penalties for placing multiple copies of the same object in the one or more storage containers, and wherein a storage container comprises a logical or physical storage area as a unit of storage.

Abstract: Systems and methods for remotely provisioning software to process data stored in a virtualized storage environment are provided. In one embodiment, the method comprises receiving a request, at a first location, for processing data using a software application, wherein the data is stored in a virtualized storage space at a second location and the software application is invoked in a virtualized computing environment at a third location; using a service at the first location to remotely invoke one or more instances of the software application over the virtualized computing environment at the third location; and using the service at the first location to remotely manage transfer of data stored in the virtualized storage space at the second location to the third location.

Abstract: Systems and methods for optimal data storage are provided. The method comprises storing data objects that are most closely related in a storage container by modeling a constraint satisfaction problem for placement of said data objects in one or more storage containers, wherein a weight is assigned to an edge connecting two data objects based on an association defining relationships between the two data objects connected by said edge, taking into account certain penalties for placing multiple copies of the same object in the one or more storage containers, and wherein a storage container comprises a logical or physical storage area as a unit of storage.

Abstract: Methods for generating a characterizing summary and generating a collection of relevant preservation objects in a preservation system are provided. A characterizing summary is generated by collecting first information about a preservation object; collecting second information about other preservation objects or other metadata; generating a characterizing summary according to the first information and the second information; and adding the characterizing summary to the preservation object. A collection of relevant preservation objects is generated by accessing one or more preservation objects by way of one or more metadata included in a target preservation object constructed for content data; determining whether each of the accessed preservation objects is relevant to the target preservation object; adding each relevant preservation object to a list of relevant preservation objects; and generating the collection of relevant preservation objects according to the list of relevant preservation objects.

Abstract: A digraph including a plurality of ordinary nodes, at least one of a composition node and a decomposition node, and a plurality of arcs interconnecting any of said nodes.

Abstract: A computer based method for the preservation of a digital information in a data set includes receiving a data set to be preserved, the data set including a plurality of preservation objects; creating a fixity table, the fixity table including one or more data types corresponding to preservation data types contained in the preservation objects, each data type being assigned an importance rank and one or more fixity function; for each preservation object, creating a Merkle tree corresponding to the preservation object and based on the fixity table.

Abstract: A digraph including a plurality of ordinary nodes, at least one of a composition node and a decomposition node, and a plurality of arcs interconnecting any of said nodes.

Abstract: Methods for generating a characterizing summary and generating a collection of relevant preservation objects in a preservation system are provided. A characterizing summary is generated by collecting first information about a preservation object; collecting second information about other preservation objects or other metadata; generating a characterizing summary according to the first information and the second information; and adding the characterizing summary to the preservation object. A collection of relevant preservation objects is generated by accessing one or more preservation objects by way of one or more metadata included in a target preservation object constructed for content data; determining whether each of the accessed preservation objects is relevant to the target preservation object; adding each relevant preservation object to a list of relevant preservation objects; and generating the collection of relevant preservation objects according to the list of relevant preservation objects.

Abstract: A computer based method for the preservation of a digital information in a data set includes receiving a data set to be preserved, the data set including a plurality of preservation objects; creating a fixity table, the fixity table including one or more data types corresponding to preservation data types contained in the preservation objects, each data type being assigned an importance rank and one or more fixity function; for each preservation object, creating a Merkle tree corresponding to the preservation object and based on the fixity table.

Abstract: A digraph including a plurality of ordinary nodes, at least one of a composition node and a decomposition node, and a plurality of arcs interconnecting any of said nodes.