Abstract: A method of populating a digital environment with digital content is disclosed. Environment data describing the digital environment is accessed. Populator data describing a populator digital object is accessed. The populator data includes semantic data describing the populator digital object. The populator digital object is placed within the digital environment. A semantic map representation of the populator digital object is generated. The semantic map representation is divided into a plurality of cells. A target cell of the plurality of cells is selected as a placeholder in the digital environment for a digital object that is optionally subsequently instantiated. The selecting of the target cell is based on an analysis of the environment data, the populator data, and the semantic map representation. Placeholder data is recorded in the semantic map representation. The placeholder data includes properties corresponding to the digital object that is optionally subsequently instantiated.

Abstract: A method of determining a suggested digital object to place into a 3D environment is disclosed. Scene data within a frustum volume of a camera within a 3D environment is determined. The scene data includes a set of digital objects that are located within the frustum volume. A set of traits is determined based on the scene data. At least one suggested digital object is suggested for placing into the 3D environment based on a correlation between the suggested digital object and the set of traits.

Abstract: A method of intelligently transforming a digital asset for a target environment is disclosed. Asset data describing the digital asset is received. The received asset data is analyzed to determine a classification type for the digital asset. A database is communicated with to request additional data associated with the determined classification type. The additional data includes semantic data associated with the classification type. The additional data is compared to the received asset data. The comparing includes determining missing data and conflicting data. The missing data includes data from the additional data which is absent from the asset data. The missing data is added to the asset data.

Abstract: A method of populating a digital environment with digital content is disclosed. Environment data describing the digital environment is accessed. Populator data describing a populator digital object is accessed. The populator data includes semantic data describing the populator digital object. The populator digital object is placed within the digital environment. A semantic map representation of the populator digital object is generated. The semantic map representation is divided into a plurality of cells. A target cell of the plurality of cells is selected as a placeholder in the digital environment for a digital object that is optionally subsequently instantiated. The selecting of the target cell is based on an analysis of the environment data, the populator data, and the semantic map representation. Placeholder data is recorded in the semantic map representation. The placeholder data includes properties corresponding to the digital object that is optionally subsequently instantiated.

Abstract: A method of populating a digital environment with digital content is disclosed. Environment data describing the digital environment is accessed. Populator data describing a populator digital object is accessed. The populator data includes semantic data describing the populator digital object. The populator digital object is placed within the digital environment. A semantic map representation of the populator digital object is generated. The semantic map representation is divided into a plurality of cells. A target cell of the plurality of cells is selected as a placeholder in the digital environment for a digital object that is optionally subsequently instantiated. The selecting of the target cell is based on an analysis of the environment data, the populator data, and the semantic map representation. Placeholder data is recorded in the semantic map representation. The placeholder data includes properties corresponding to the digital object that is optionally subsequently instantiated.

Abstract: A method of determining a suggested digital object to place into a 3D environment is disclosed. Scene data within a frustum volume of a camera within a 3D environment is determined. The scene data includes a set of digital objects that are located within the frustum volume. A set of traits is determined based on the scene data. At least one suggested digital object is suggested for placing into the 3D environment based on a correlation between the suggested digital object and the set of traits.

Abstract: A method of populating a digital environment with digital content is disclosed. Environment data describing the digital environment is accessed. Populator data describing a populator digital object is accessed. The populator data includes semantic data describing the populator digital object. The populator digital object is placed within the digital environment. A semantic map representation of the populator digital object is generated. The semantic map representation is divided into a plurality of cells. A target cell of the plurality of cells is selected as a placeholder in the digital environment for a digital object that is optionally subsequently instantiated. The selecting of the target cell is based on an analysis of the environment data, the populator data, and the semantic map representation. Placeholder data is recorded in the semantic map representation. The placeholder data includes properties corresponding to the digital object that is optionally subsequently instantiated.

Abstract: A method of intelligently transforming a digital asset for a target environment is disclosed. Asset data describing the digital asset is received. The received asset data is analyzed to determine a classification type for the digital asset. A database is communicated with to request additional data associated with the determined classification type. The additional data includes semantic data associated with the classification type. The additional data is compared to the received asset data. The comparing includes determining missing data and conflicting data. The missing data includes data from the additional data which is absent from the asset data. The missing data is added to the asset data.