Abstract: A method for calculating a confidence score for a data element that includes substantive technical data in a computer interpretable form and is adapted to be utilized by a knowledge management system. The method includes the steps of encoding substantive technical data in the data element, tracking a plurality of component factors for the data element, calculating a plurality of component scores for the data element wherein each individual component score corresponds to an individual component factor, and calculating the confidence score for the data element based at least in part on the plurality of component scores.

Abstract: A camera includes a primary housing that has a cylindrical exterior surface and an opening located at a front end. The camera also includes a rotatable housing that has a spherical exterior surface and an aperture, where the rotatable housing is disposed in the opening of the primary housing and is rotatably mounted to the primary housing. The camera also includes an image sensor that is located in the rotatable housing for rotation in unison with the rotatable housing, where the image sensor receives light through the aperture of the rotatable housing.

Abstract: A method includes receiving information identifying a first knowledge element from a plurality of knowledge elements. The method also includes, for a plurality of similar knowledge elements, for each of a plurality of similar knowledge elements determining a first value based on actions taken by a user with respect to a respective knowledge element from the plurality of similar knowledge elements, determining a second value that represents similarity of the first knowledge element to the respective knowledge element, and determining an expertise component value for the respective knowledge element based at least in part on a multiplicative product of the first value and the second value. The method also includes determining an expertise value that represents the user's expertise level relative to a subject matter described by the first knowledge element based on the expertise component values for the plurality of similar knowledge elements.

Abstract: A method for calculating a confidence score for a data element that includes substantive technical data in a computer interpretable form and is adapted to be utilized by a knowledge management system. The method includes the steps of encoding substantive technical data in the data element, tracking a plurality of component factors for the data element, calculating a plurality of component scores for the data element wherein each individual component score corresponds to an individual component factor, and calculating the confidence score for the data element based at least in part on the plurality of component scores.

Abstract: An interface method for a knowledge management system server. The method includes receiving a symbolic identification of an object classification from a first user system, retrieving a definition of the object classification from a database, and retrieving one or more data elements that are included within the definition of the object classification from the database. The data elements include one or more input parameters, and an initial list of the input parameters is transmitted to the first user system. The method further includes receiving object parameters from the first user system, and transmitting an updated list of the input parameters in response to a change in the input parameters caused by at least one of a change to the definition of the object classification, a change to one or more of the data elements, or receipt of the object parameters from the first user system.

Abstract: A method for ranking experts in a knowledge management system. A plurality of data elements are stored in a database, the data elements having substantive technical data and bibliographic information encoded therein. A result set is produced from the database in response to a user query, the result set including data elements having technical data encoded therein that corresponds to the query. An expert list is produced based on the bibliographic information for the data elements contained in the result set. Each expert in the expert list is ranked based on criteria associated with the result set to produce a ranked expert list.