A central challenge in science is to understand how systems behaviors emerge from complex networks. This often requires aggregating, reusing, and integrating heterogeneous information. Supplementary spreadsheets to articles are a key data source. Spreadsheets are popular because they are easy to read and write. However, spreadsheets are often difficult to reanalyze because they capture data ad hoc without schemas that define the objects, relationships, and attributes that they represent. To help researchers reuse and compose spreadsheets, we developed ObjTables, a toolkit that makes spreadsheets human- and machine-readable by combining spreadsheets with schemas and an object-relational mapping system. ObjTables includes a format for schemas; markup for indicating the class and attribute represented by each spreadsheet and column; numerous data types for scientific information; and high-level software for using schemas to read, write, validate, compare, merge, revision, and analyze spreadsheets. By making spreadsheets easier to reuse, ObjTables could enable unprecedented secondary meta-analyses. By making it easy to build new formats and associated software for new types of data, ObjTables can also accelerate emerging scientific fields.