Abstract: A system for diagnosing an additive manufacturing device is provided. The system includes one or more processors, one or more non-transitory memory modules communicatively coupled to the one or more processors and storing machine-readable instructions. The machine-readable instructions, when executed, cause the one or more processors to: determine parameters associated with at least one subsystem of the additive manufacturing device, the parameters being related to a build generated by the additive manufacturing device; compare the parameters with threshold values; and determine a failure mode, among a plurality of failure modes, associated with a subsystem of the at least one subsystem of the additive manufacturing device based on the comparison of the parameters with the threshold values.

Abstract: According to certain aspects of the present disclosure, a computer-implemented method is provided. The method includes receiving, at a mobile device management server from a threat feed server, at least one security statement. The method includes parsing the at least one security statement into parsed information. The method includes creating a custom threat feed of common vulnerabilities and exposures with at least the parsed information. The method includes selectively creating an alert associated with one common vulnerability and exposure of the common vulnerabilities and exposures, wherein the alert comprises a remediation action associated with the one common vulnerability and exposure. The method includes determining at least one managed device, managed by the mobile device management server, and associated with the remediation action of the alert. Systems and machine-readable media are also provided.

Abstract: An information handling system may include a processor, a display device communicatively coupled to the processor, and a management controller communicatively coupled to the processor and the display device and configured to, in response to a failure of the information handling system, determine a component of the information handling system as a source of failure, generate a unique failure code associated with the failure, encrypt the unique failure code to generate an encrypted unique failure code, and display the encrypted unique failure code to the display device.

Abstract: Implementations described herein relate to methods, systems, and computer-readable media to monitor a distributed computing system. In some implementations, a method may include obtaining a first plurality of monitoring metrics of a respective application of one or more applications executing over the distributed computing system, obtaining time-series data of the first plurality of monitoring metrics, programmatically analyzing the time-series data of the first plurality of monitoring metrics to determine a second plurality of monitoring metrics, wherein the second plurality of monitoring metrics is determined to be a predictive set of the first plurality of monitoring metrics, and monitoring the distributed computing system by monitoring the second plurality of monitoring metrics.

Abstract: An anomaly factor estimation apparatus includes a memory and a processor configured to execute training an anomaly detection model for performing anomaly detection based on an error of output data with respect to input data represented by a multidimensional numerical vector; inputting test data into the anomaly detection model, to determine whether the test data corresponds to an anomaly based on output data output from the anomaly detection model and the test data; and calculating a degree of contribution to the anomaly for each dimension of the test data based on a likelihood of said each dimension, in response to determining that the test data corresponds to the anomaly.

Abstract: An acquirer acquires abnormality information indicating that an abnormality has occurred in equipment provided in a conference room. The equipment is, for example, a display device such as a display or a projector. A conference information generator generates conference information indicating a progress status of a conference which is carried out in the conference room by processing information output from a device provided in the conference room. An information transmitter determines a first timing which is a timing at which abnormality-relevant information which is information to be transmitted due to occurrence of the abnormality is transmitted using the conference information and transmits the abnormality-relevant information to the equipment or another device at the first timing.

Abstract: A method is provided for diagnosing probable root causes of anomalies in computing environments. The method is performed by an anomaly analytics server in networked communication with hosts. The method includes (a) receiving a topology map; (b) receiving event data associated with each host; (c) receiving an anomaly baseline defining thresholds for identifying an anomalous status in each host application; (d) analyzing the event data and the anomaly baseline to determine a host anomaly status for each host; (e) analyzing the host anomaly status and the topology map to determine a tier anomaly status for each of the host tiers; (f) identifying at least one host tier as a root cause host tier by processing the tier anomaly statuses and the set of tier dependencies; and (g) generating an alert identifying each root cause host tier as a probable root cause of an anomaly.

Abstract: One or more non-transitory computer readable media contain program instructions that, when executed by one or more processors, cause the one or more processors to perform operations including: creating and managing a plurality of smart entities, each of the smart entities including a plurality of attributes; receiving inbound data from one or more enterprise applications; translating the inbound data into values for one or more of the plurality of attributes; writing the plurality of attributes to the smart entities; reading the plurality of attributes from the smart entities; translating the plurality of attributes into outbound data; and providing the outbound data to the one or more enterprise applications.

Abstract: In an embodiment, an electronic circuit includes: a plurality of signal channels; a signal collection circuit configured to determine an action of the electronic circuit based on channel signals from the plurality of signal channels; and a first signal management circuit coupled between the plurality of signal channels and the signal collection circuit, the first signal management circuit including: a set of internal registers, a set of user registers, and a decoder configured to program the set of internal registers based on a content of the set of user registers, where the first signal management circuit is configured to receive the channel signals via the plurality of signal channels, generate first aggregated signals based on the received channel signals and a content of the set of internal registers, and transmitting the first aggregated signals to the signal collection circuit.

Abstract: A system and method of deployment of malware detection traps by at least one processor may include performing a first interrogation of a first Network Asset (NA) of a specific NA family; determining, based on the interrogation, a value of one or more first NA property data elements of the first NA; obtaining one or more second NA property data elements corresponding to the specific NA family; integrating the one or more first NA property data elements and the one or more second NA property data elements to generate a template data element, corresponding to the specific NA family; producing, from the template data element, a malware detection trap module; and deploying, on one or more computing devices of a computer network, one or more instantiations of the malware detection trap module as decoys of the first NA.

Abstract: Generating persistent multifaceted statistical distributions of event data associated with computing nodes is disclosed. From a data stream, events are identified that occur during a first time interval. Characteristics associated with the events are determined. Based on a primary characteristic, it is determined that an event corresponds to an event cluster. The event count for that cluster is incremented. It is determined that the characteristics correspond to an event descriptor of events in the cluster. Responsive to requests to view the event cluster, information about descriptors from the cluster are displayed indicating events having a particular event descriptor, or a summary of characteristics that distinguish the descriptor from other event descriptors.

Abstract: A TCU includes: a wide-area communication section that performs wireless communication with a base station; a short-range communication section that performs wireless communication with an access point; a vehicle-to-vehicle communication section that performs wireless communication with a relay vehicle; and a communication control section that transmits upload data by using any one of the wide-area communication section, the short-range communication section, and the vehicle-to-vehicle communication section, wherein the communication control section transmits the upload data more preferentially by using the short-range communication section or the vehicle-to-vehicle communication section than by using the wide-area communication section when an upload deferment condition is met, and transmits the upload data more preferentially by using the wide-area communication section than by using the short-range communication section and the vehicle-to-vehicle communication section when the upload deferment condition is

Abstract: Embodiments of the invention relate to an application monitoring and unplanned event remediation system, which analyzes event data to generate dynamic testing strategies and then apply said testing strategies in real-time to predict future events. The invention utilizes past event data to prioritize testing of particular application conditions, allowing for continuous monitoring without creating unnecessary strain on available computing resources. Because a variety of application operating states can result in unplanned events, the present invention provides the functional benefit of adapting testing strategies in real-time as an application's operating state changes, increasing the likelihood of correctly predicting a future event. The present invention also provides a system of alerting a managing entity system to a future event, as well as providing instructions for preventative or remedial actions which may serve to lessen the potential impact of an unplanned event on a managing entity.

Abstract: A CCI (I3C SDR) processing section determines status of an index when requested to be accessed by an I3C master for a read operation. An error handling section then controls an I3C slave 13 to detect occurrence of an error based on the status of the index and to neglect all communication until communication is restarted or stopped by the I3C master, the I3C slave 13 being further controlled to send a NACK response when performing acknowledge processing on a signal sent from the I3C master. This technology can be applied to the I3C bus, for example.

Abstract: Methods, systems, graphical user interfaces (GUIs), and computer-readable media for presenting GUI elements generated based on information associated with an event are generally described. An event information presentation system may be configured to present GUI elements generated based on substantially real-time event information associated with a live event, such as a sporting event. Illustrative event information may include object movement and location information for objects such as event participants (for instance, players) and articles (for instance, a football for a football game event). The event information may be interpreted based on activity categories to automatically differentiate, organize, highlight, or the like the event information in order to generate relevant and meaningful GUI elements.

Abstract: A computerized method of diagnosing a mislabeling of a source type of a received event. The method comprising operations of receiving an event by a source type analysis logic with a data index and query system, wherein the event includes a portion of raw machine data and is associated with a specific point in time, obtaining an original source type assigned to the event and one or more predicted source types. The one or more predicted source types are determined by analysis of a data representation of the event in view of training data and the training data includes a plurality of data representations corresponding to known source types. Additionally, the computerized method also includes an operation of, determining whether the event has been mislabeled and in response to determining the event has been mislabeled, diagnosing a source of the mislabeling.

Abstract: Disclosed are embodiments for improving remote diagnostics of a computer system. Some embodiments obtain operational parameter values and log data from a plurality of network devices, and provide the operational parameter values and log data to a machine learning model. The model is trained to identify a root cause of a degradation of the computer system based on the operational parameter values and log data, and to provide recommendations of log data level settings for the network devices. If the model identifies a root cause of the degradation with sufficient confidence, a remedial action is identified and applied to the computer system. If the confidence level is insufficient, log data level settings of the network devices are modified based on the recommendations of the model. This process is performed iteratively, for example, such that the model receives log data based on its recommended log data levels, until a root cause is identified with sufficient confidence.

Abstract: Plan of action and milestones (POA&M) automated generation engine (PAGE) systems are provided along with related methods. A number of distributed tamper protected configuration scanning systems configured to scan computer files in selected target systems across a network and generate target system configuration scan results files. The PAGE system also includes a number of POA&M configuration selection user interfaces and visualization systems enabling users to select, inform, and customize POA&M outputs based on POA&M configuration files that include POA&M library files that are associated with different types of plans or actions (e.g., cyber security configuration for networked computers). An expert system is also provided for receiving a plurality of configuration file inputs (e.g., configuration scan results file and various baseline files, e.g.

Abstract: Techniques for providing lifecycle handling of faults associated with a storage appliance. The techniques can include recording information or details of one or more detected faults associated with a storage appliance in a fault database, analyzing the recorded fault information/details by an analytic tool, and determining whether to perform immediate recovery or defer recovery of the detected fault(s) based at least on a recommendation of the analytic tool. In this way, taking the storage appliance offline upon occurrence of a single fault can, for the most part, be avoided. In addition, because the detection of faults is not performed within a fault domain for a filesystem handling files for a single or limited number of volume families, a deduplication domain for the files of the filesystem is not restricted to the single or limited number of volume families.

Abstract: A semiconductor memory apparatus including a data memory array, a parity memory array, a data read/write and correction part, a parity read/write part and a syndrome generating and decoding part is provided. The data read/write and correction part reads the data memory array and outputs a first application reading data. The parity read/write part reads the parity memory array and outputs a parity reading data. During a read cycle of an application data, the syndrome generating and decoding part generates a syndrome writing data according to the first application reading data, compares and decodes the syndrome writing data with the parity reading data to generate a verifying comparison data. In the same read cycle, the data read/write and correction part corrects the application data according to the verifying comparison data, and writes the corrected application data back to the data memory array and outputs a corresponding output data.

Abstract: A storage system and method for crash analysis are provided. In one embodiment, a storage system comprises a memory and a controller. The controller is configured to store a crash log in a buffer in the controller; determine whether the storage system has crashed; and in response to determining that the storage system has crashed, send the crash log from the buffer in the controller to a host in communication with the storage system. Other embodiments are provided.

Abstract: A method includes detecting an error that has occurred in one or more assets of an enterprise system and generating a visual error signature of the detected error, the visual error signature comprising at least a portion of a graph-based visualization of operation of the assets. The method also includes providing the generated visual error signature for the detected error as input to a machine learning model and utilizing the machine learning model to classify the visual error signature for the detected error as belonging to at least a given one of a plurality of error classes, the machine learning model being trained using historical visual error signatures for previously-detected errors. The method further includes identifying at least one action taken to remediate each of one or more previously-detected errors of the given error class and remediating the detected error utilizing one or more of the identified actions.

Abstract: A method includes obtaining information regarding a given asset to be repaired, providing the information regarding the given asset to an encoder of a deep learning model, and receiving, from a decoder of the deep learning model, a recommendation for a troubleshooting action to be performed on the given asset. The method also includes performing the recommended troubleshooting action on the given asset, determining whether the recommended troubleshooting action results in a successful repair of the given asset and, responsive to determining that the recommended troubleshooting action does not result in a successful repair of the given asset, augmenting the information regarding the given asset based at least in part on an output vocabulary of the decoder corresponding to the recommended troubleshooting action. The method further includes repeating the providing, receiving, performing and determining steps utilizing the augmented information regarding the given asset.

Abstract: A method and an apparatus for implementing a buffer cache for a persistent file system in a non-volatile memory is provided. A set of data is maintained in one or more extents in a non-volatile random-access memory (NVRAM) of a computing device. At least one buffer header is allocated in a dynamic random-access memory (DRAM) of the computing device. In response to a read request by a first process executing on the computing device to access one or more first data blocks in a first extent of the one or more extents, the first process is granted direct read access of the first extent in the NVRAM. A reference to the first extent in the NVRAM is stored in a first buffer header. The first buffer header is associated with the first process. The first process uses the first buffer header to directly access the one or more first data blocks in the NVRAM.

Abstract: An apparatus includes a memory and a hardware processor. The memory stores a plurality of previous software errors and a plurality of solutions to the plurality of previous software errors. The processor receives a video of a user describing an error in a software application and tracks a facial feature of the user to determine an emotional intensity. The processor converts an audio portion of the video to a text file and analyzes the text file to determine the error. In response to the emotional intensity exceeding a threshold, the processor determines, based on the plurality of previous software errors, a series of steps that, when performed, replicate the error, determines, based on the series of steps and the plurality of solutions, a change to the source code of the application that fixes the error, and implements the change to the software code.

Abstract: A system controller performs collective setting processing which collectively performs setting with respect to one or more controlled devices including a medical device. The system controller judges a degree of error relating to a state of the controlled device which occurred when the collective setting processing is performed. The system controller displays an error removing screen for removing an occurred error based on a judgement result of the degree of error. A setting instruction operation is an operation which selects a desired scene from a plurality of scenes which are set in advance corresponding to a progress of a surgery. The degree of error is associated with the plurality of scenes, and the system controller judges the degree of the occurred error based on the scene which is underway of the surgery.

Abstract: Methods, non-transitory machine readable media, and computing devices that manage data storage fabric health are disclosed. With this technology, a network model is applied to network data determined from monitored network traffic exchanged between storage nodes and via network connections over a cluster fabric to generate a health score for the cluster fabric. A cause of health degradation in the cluster fabric is determined based on an analysis of the network data, when the health score indicates that health of the cluster fabric is degrading. A corrective action is automatically initiated based on the cause of health degradation in the cluster fabric. With this technology, cluster fabrics in data storage networks are more effectively monitored for health degradation and, advantageously, corrective actions can be preemptively initiated to improve performance.

Abstract: A controlled apparatus that operates as a first controlled apparatus, comprises a communication unit configured to communicate with a second controlled apparatus, a detection unit configured to detect a second controlled apparatus having a predetermined relationship with the first controlled apparatus via the communication unit, and a control unit configured to generate a first web page capable of controlling the first controlled apparatus if the detection unit has not detected the second controlled apparatus having the predetermined relationship, and generate a second web page capable of collectively controlling the first controlled apparatus and the second controlled apparatus, if the detection unit has detected the second controlled apparatus having the predetermined relationship.

Abstract: A system and method may be provided for performing code analysis on a system of remote computer nodes. Input data may be collected on a local computer system along with a request for code analysis. The input data and request may be transmitted to a network of remote nodes. The network of remote nodes may perform the code analysis task using the input data. The results of the analysis may be returned back to the local computer.

Abstract: A technique is described for evaluating code at a local computing device before deploying the code to a cloud computing platform to be compiled. In an example embodiment, class files including the code in a programming language associated with the cloud computing environment are loaded by a local computer system, for example, associated with a software developer. The local computer system then parses the code to identify elements in the code and checks the identified elements. Errors in the code are identified based on the checking and are displayed to a user (e.g., the developer), for example, via a graphical user interface of a code editor application.

Abstract: Systems and methods for identifying a computer security threat based on communication via a computer network.

Abstract: A new alert associated with a computer information technology item is received. The new alert is evaluated, including by determining application fingerprints of applications executing on a server associated with the new alert. Matching previous alerts similar to the new alert are identified, including by comparing the application fingerprints of the server associated with the new alert with corresponding application fingerprints of servers associated with previous alerts. The matching previous alerts are sorted based at least in part on the comparison of the application fingerprints.

Abstract: A method for recording memory errors includes the following steps: upon detecting a current correctable error that occurred in a volatile memory device, determining whether a count value corresponding to the current correctable error exceeds a predetermined value; and when it is determined that the count value corresponding to the current correctable error thus detected does not exceed the predetermined value, sending update event information corresponding to the current correctable error to a BMC, in order for the BMC to record information of the current correctable error.

Abstract: Systems and methods are disclosed herein for improving data migration operations including testing and setup of computing environments. In one example, the method may include receiving data for one or more application programming interfaces (APIs). The method may further include generating one or more tests to test the one or more APIs in a first computing environment, testing the APIs, storing the results in a database, and performing a change data capture operation. The method may further include augmenting the one or more tests with the CDC data to generate an updated test. The method may further include testing, using the updated test, a second set of the one or more APIs and comparing the test results. The method may also include outputting a confidence score indicating a correlation between the first environment and the second environment.

Abstract: The disclosed examples relate to arranging graph data for display on a display device. One example provides, on a computing device, a method comprising determining one or more connected groups of nodes in directed acyclic graph data, for each connected group of nodes, determining a reachability from each node with no inputs to each of one or more nodes with no outputs to determine a plurality of initial node/terminal node pairs, and for each initial node/terminal node pair, determining a path from the initial node to the terminal node. The method further comprises initializing a grid based upon the determined paths, placing each node at a corresponding initial grid location, and placing edges between nodes based upon the determined paths to form an initial grid representation, modifying the initial grid representation via a cost function to form a modified grid representation, and outputting the modified grid representation for display.

Abstract: There are provided a defect inspection apparatus, method, and program for, in a case of using an image of an inspection-target industrial product (test object) to conduct an inspection to check whether defects are present, allowing an image interpreter to precisely and efficiently detect defects. A possible-defect image D3 indicating a crack-like defect and a simulation result image P3 indicating the predicted growth of the crack-like defect are displayed. Sliders L1 and L2 and checkboxes CB1 are used to enable selection of possible defects and simulation results to be displayed. An image interpreter can use the checkboxes CB1 to select a type of possible defect to be displayed, and can use the sliders L1 and L2 to select possible defects to be displayed on the basis of the wall thickness of portions in which possible defects are detected and the size of possible defects.

Abstract: A network log time alignment method and an apparatus are provided. The method includes: obtaining log data stored in multiple network devices; parsing the log data to obtain features of each network device; determining associated features of the multiple network devices according to the features of each network device, where the associated features are features that are of the network devices and that have an association in space; and then, performing alignment on log time in multiple pieces of log data according to the associated features. Therefore, associated features of related devices of a network fault can be found, and log time are automatically aligned according to the associated features, thereby improving the efficiency and the accuracy of the fault location and sectionalization.

Abstract: One or more non-transitory computer readable media contain program instructions that, when executed by one or more processors, cause the one or more processors to perform operations including: creating and managing a plurality of smart entities, each of the smart entities including a plurality of attributes; receiving inbound data from one or more enterprise applications; translating the inbound data into values for one or more of the plurality of attributes; writing the plurality of attributes to the smart entities; reading the plurality of attributes from the smart entities; translating the plurality of attributes into outbound data; and providing the outbound data to the one or more enterprise applications.

Abstract: A method of location-behavioral monitoring is provided. The method comprising: storing an access list associated with an identification credential; collecting historical location parameters associated with the identification credential; receiving schedule parameters associated with the identification credential; determining a predicted location schedule associated with the identification credential in response to the historical location parameters and schedule parameters; collecting location parameters associated with identification credential; and determining a risk rating associated with each location parameter in response to the predicted location schedule, location parameters, and the access list.

Abstract: A Remote Metadata Center provides Disaster Recovery (DR) testing and metadata backup services to multiple business organizations. Metadata associated with local data backups performed at business organizations is transmitted to the Remote Metadata Center. Corresponding backup data is stored in a data storage system that is either stored locally at the business organization or at a data storage facility that is at a different location than the Remote Metadata Center and the business organization. DR testing can be staged from the Remote Data Center using the metadata received and optionally with assistance from an operator at the business organization and/or the data storage facility.

Abstract: Apparatus and methods for remotely monitoring a plurality of distributed devices is provided. The apparatus and methods determine logging conditions which define a state of a device at which recording of the state of the device should begin prior to an event, in order to identify a sequences of actions which occur at the devices prior to the event.

Abstract: A data analytics system stores a data file that includes an ordered set of data blocks. The data blocks can be parsed out of order. An error management module of the data analytics system detects a parse error occurring during parsing of a data block and generates an error message for the parse error. The error message includes unresolved location information indicating a location of the detected parse error in the data block. The error management module resolves the unresolved location information after determining that one or more additional data blocks preceding the data block in the ordered set have been parsed. The error management module generates resolved location information that indicates a location of the parse error in the data file. The error management module updates the error message with the resolved location information and outputs the updated error message.

Abstract: A monitoring apparatus is coupled to a sensor configured to observe a behavior of a monitoring target, and is accessible a storage device being configured to store: a database stored a phenomenon data group; stability information; and operation history information. The monitoring apparatus is configured to: calculate a stability of input phenomenon data; determine whether the stability of the input phenomenon data is a stability indicating a specific behavior; retrieve from the database, when the stability of the input phenomenon data is a stability, similar phenomenon data that is similar to the input phenomenon data; generate, by acquiring from the stability information a stability of subsequent phenomenon data continuous with the similar phenomenon data, similar case data combining the similar phenomenon data and the subsequent phenomenon data; identify, from the operation history information, operation content; and output the similar case data and the operation content.

Abstract: Systems and methods may be used to perform a software failure mode and effects analysis (SW FMEA) for a software component. The SW FMEA may include a quantitative approach, for example based on a risk priority number for the software component. The risk priority number may be based on a severity of a failure in the software component, an occurrence likelihood of a failure in the software component, or a detectability of a failure in the software component. A safety integrity level may be determined for the software component based on the risk priority number.

Abstract: Information reduction in data processing environments includes at least one of: one or more Error Correcting Codes that decode n-vectors into k-vectors and utilize said decoding to information-reduce data from a higher dimensional space into a lower dimensional space. The information reduction further provides for a hierarchy of information reduction allowing a variety of information reductions. Transformations are provided to utilize available data space, and data may be transformed using several techniques including windowing functions, filters in the time and frequency domains, or any numeric processing on the data.

Abstract: Concepts for logging and retrieving diagnostic information relating to a computer system that implements a runtime stack when executing a program are presented. One example comprises, determining a depth value, the depth value being configured to identify a level of diagnostic tracing for the runtime stack. For each stack frame of the runtime stack: the depth value is compared with a counter value associated with the stack frame, and data is then retrieved from the stack frame based on the comparison result.

Abstract: Embodiments for representing the operational state of a distributed computing system are provided. Relationships within a distributed computing system are identified. Each of the identified relationships is associated with communication between two of a plurality of computing nodes within the distributed computing system. At least one difference between a healthy state of the distributed computing system and an impaired state of the distributed computing system is determined based on the identifying of the relationships. A representation of the determined at least one difference between the healthy state and the impaired state of the distributed computing system is generated based on information associated with a user.

Abstract: An information handling system includes a dual in-line memory module (DIMM) coupled to a memory controller. The memory controller provides interrupts to a processor each time a read transaction from the DIMM results in a correctable read error. The processor instantiates a failure predictor that receives the interrupts, accumulates a count of the interrupts, and provides an error indication when the count exceeds an error threshold. In accumulating the count, the failure predictor increments the count each time the predictor receives a particular interrupt and decrements the count in accordance with an error leak rate. The error leak rate has a first value when a training coefficient for the DIMM is greater than a deviation threshold, and has a second value when the training coefficient for the DIMM is less than the deviation threshold.

Abstract: A method includes executing, multiple times, a target application with at least one test input dataset to obtain multiple test output datasets. The test output data sets each include multiple field values for multiple fields. The method further includes comparing the field values with at least one validated output dataset to assign the fields into a match class, an ignore class, and an unknown class, extracting, from the comparing, a field property for a first subset of the fields in the match class, and generating a test result by adding, to the test result, whether a first subset of the field values corresponding to the first subset of the fields satisfies a corresponding field property, and ignoring a second subset of the a second subset of fields classified in the ignore class. The method further includes presenting the test result.

Abstract: A computer-implemented method of carrying out an image-based search for information available over a network includes serving to a client computer a web page containing a set of knowledge models in response to a search request message received at a server over the network from the client computer. The knowledge models are interlinked, through a crowd-sourced schema, in a knowledgebase. The web page is structured so that graphically selecting one of the knowledge models in the web page displayed on the client computer causes display of a set of knowledge assets interlinked with the selected knowledge model.