24. A network computer for managing data over a network, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and a processor device that executes instructions that perform actions, including: providing source data to the network computer from one or more separate data sources; providing a plurality of particular types of indices that are separate and optimized for one or more different content-types, wherein the particular types of indices include one or more of n-gram indices, temporal indices, or geo-spatial indices; generating a raw data graph from the source data, wherein the structure of the raw data graph is based on the structure of the source data; mapping one or more elements of the raw data graph to a concept graph; generating one or more concept instances based on at least the concept graph, the raw data graph, and the source data; generating one or more model-identifiers (MIDs) that correspond to the one or more concept instances, wherein the one or more MIDs include at least a path in the concept graph and one or more value keys that correspond to one or more portions of the source data; indexing values from the source data that correspond to the one or more MIDs in one or more indices that are selected from the plurality of indices based on a content-type of the source data that is associated with the one or more MIDs; and responsive to a query, generating a result set that includes one or more result MIDs based on one or more indices of the plurality of indices, wherein a content-type of at least one portion of the query is employed to select the one or more indices used to generate the result set.
24. A network computer for managing data over a network, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and a processor device that executes instructions that perform actions, including: providing source data to the network computer from one or more separate data sources; providing a plurality of particular types of indices that are separate and optimized for one or more different content-types, wherein the particular types of indices include one or more of n-gram indices, temporal indices, or geo-spatial indices; generating a raw data graph from the source data, wherein the structure of the raw data graph is based on the structure of the source data; mapping one or more elements of the raw data graph to a concept graph; generating one or more concept instances based on at least the concept graph, the raw data graph, and the source data; generating one or more model-identifiers (MIDs) that correspond to the one or more concept instances, wherein the one or more MIDs include at least a path in the concept graph and one or more value keys that correspond to one or more portions of the source data; indexing values from the source data that correspond to the one or more MIDs in one or more indices that are selected from the plurality of indices based on a content-type of the source data that is associated with the one or more MIDs; and responsive to a query, generating a result set that includes one or more result MIDs based on one or more indices of the plurality of indices, wherein a content-type of at least one portion of the query is employed to select the one or more indices used to generate the result set. 29. The network computer of claim 24 , wherein mapping the one or more elements of the raw data graph to a concept graph, further comprises, determining one or more raw data graph elements based on one or more annotations that one or more classifiers added to the one or more raw data graph elements.