Plants exude a plethora of compounds, both above- and below ground, to communicate with their environment. Although much is known about this communication above ground, we are only beginning to fathom the identity, level of variation, and role of below-ground chemical signals in a plant’s life. There have been many challenges associated with establishing a standardized methodology for studying root-exuded compounds, thus their role in plant-environment communication is still not well described. Here, we develop an interdisciplinary workflow to explore the natural variation in root exudate chemical composition of the model plant Arabidopsis thaliana. We highlight key challenges associated with sampling strategies and develop a framework for analyzing narrow and broad-scale patterns in root exudate composition of a large sample set of natural A. thaliana accessions. Our method consists of in vitro cultivation of individual seedlings inside a plastic mesh followed by a short hydroponic sampling period in micro quantities of ultrapure water. The mesh eases handling individual plants of varying sizes, thus making this setup advantageous for large-scale characterization of root exudates of individual plants in axenic conditions, and can be easily extended for prolonged temporal exudate collection experiments. Furthermore, a short sampling duration minimizes the experiment duration from days to mere hours, and is validated by yielding sufficient signal even with the small volume of sampling solution. An untargeted metabolic profiling analytical approach using ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-QTOF-MS), followed by compound identification using open access software MZMine3 and SIRIUS 5, was used to capture a broad picture of the root exudate composition of A. thaliana accessions. This methodology can be broadly applied for investigating the role of root exudates as signals involved in plant belowground interactions. We report the first findings from the analysis here with results from Columbia genotype. We include here In Raw datafiles: The raw datasets obtained from MZMine 3 analysis, which contains aligned features of Columbia genotypes (Sheet1) as well as control samples (Sheet2). The dataset consists of feature (row)ID, average (mass-to-charge ratios) m/z and retention times (RT) across samples for individual features. It also includes sample-specific information including feature status, name, m/z, RT, feature peak height, and area. We also include a filtered datasheet excluding the features obtained in control as well as samples (Sheet3). In Supplementary tables: The 354 metabolites obtained after filtering out control features with their mass-to-charge ratios and retention times (Supplementary table 1). The 313 features identified by SIRIUS are listed with their mass-to-charge ratios, retention times, chemical formula, chemical annotations, and probabilities scored by SIRIUS in Supplementarty table 2.