This review provides a comprehensive overview of recent advances in data-independent acquisition (DIA) proteomics, covering data acquisition schemes, analysis strategies, and software tools. DIA has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. The review categorizes DIA data acquisition schemes into three major types: full-scan DIA, windowed DIA, and unconventional methods. Full-scan DIA isolates all precursors across the entire m/z range, while windowed DIA partitions the m/z range into segments for multiple MS2 scans per cycle. Unconventional methods include mixed-mode DIA and direct-infusion DIA. Windowed DIA is further divided into wide-window, narrow-window, overlapping-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation (PASEF)-enhanced DIA. The review discusses the evolution and recent advances of these methods, highlighting their advantages and challenges. For example, narrow-window DIA improves precursor selectivity but requires careful optimization to maintain appropriate cycle times. Overlapping-window DIA enhances selectivity by using computational demultiplexing regions for data interpretation. The review also covers the generation and optimization of spectral libraries, which are critical resources for DIA analysis. Publicly available benchmark datasets are summarized to facilitate performance evaluation of various software tools and analysis workflows. The review highlights the development of various DIA data acquisition schemes, including full-scan DIA, windowed DIA, and unconventional methods. It also discusses the strategies for DIA data analysis, including spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. The review introduces various software tools implementing these strategies, with details on their overall workflows and scoring approaches at different steps. The review also discusses the recent development of PASEF-enhanced DIA methods, including Synchro-PASEF, Slice-PASEF, and midiaPASEF, which enable precursor ions to be selected in varied windows. These methods allow for dynamic window arrangements with a pre-defined scheme, enhancing the resolution and sensitivity of DIA data analysis. The review also discusses unconventional methods, including mixed-mode DIA, which incorporate additional schemes like DDA and targeted acquisition alongside DIA. The review concludes by emphasizing the importance of DIA in proteomics and the need for continued advances and synergistic developments of versatile components in DIA workflows to further enhance the power of DIA-based proteomics.This review provides a comprehensive overview of recent advances in data-independent acquisition (DIA) proteomics, covering data acquisition schemes, analysis strategies, and software tools. DIA has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. The review categorizes DIA data acquisition schemes into three major types: full-scan DIA, windowed DIA, and unconventional methods. Full-scan DIA isolates all precursors across the entire m/z range, while windowed DIA partitions the m/z range into segments for multiple MS2 scans per cycle. Unconventional methods include mixed-mode DIA and direct-infusion DIA. Windowed DIA is further divided into wide-window, narrow-window, overlapping-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation (PASEF)-enhanced DIA. The review discusses the evolution and recent advances of these methods, highlighting their advantages and challenges. For example, narrow-window DIA improves precursor selectivity but requires careful optimization to maintain appropriate cycle times. Overlapping-window DIA enhances selectivity by using computational demultiplexing regions for data interpretation. The review also covers the generation and optimization of spectral libraries, which are critical resources for DIA analysis. Publicly available benchmark datasets are summarized to facilitate performance evaluation of various software tools and analysis workflows. The review highlights the development of various DIA data acquisition schemes, including full-scan DIA, windowed DIA, and unconventional methods. It also discusses the strategies for DIA data analysis, including spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. The review introduces various software tools implementing these strategies, with details on their overall workflows and scoring approaches at different steps. The review also discusses the recent development of PASEF-enhanced DIA methods, including Synchro-PASEF, Slice-PASEF, and midiaPASEF, which enable precursor ions to be selected in varied windows. These methods allow for dynamic window arrangements with a pre-defined scheme, enhancing the resolution and sensitivity of DIA data analysis. The review also discusses unconventional methods, including mixed-mode DIA, which incorporate additional schemes like DDA and targeted acquisition alongside DIA. The review concludes by emphasizing the importance of DIA in proteomics and the need for continued advances and synergistic developments of versatile components in DIA workflows to further enhance the power of DIA-based proteomics.