The success of a recommendation system for NPMs is, however, predicated on structured, open databases of NPMs and their adsorption properties. One such database is the NIST/ARPA-E Database of Novel and Emerging Adsorbent Materials (NIST-ISODB) that has collected and compiled gas adsorption measurements in NPMs from the literature, for both experimental and simulation sources, for a variety of gases at a wide range of conditions. We originally set out to develop a recommendation system using Henry coefficients extracted from this experimental data, but we found the resultant recommendation system was unable to reliably rank NPMs according to their adsorption properties. Particularly, we found the recommendation system with an interaction term included could not outperform the baseline material offset model. We propose four explanations for the poor performance of our recommendation system based on an NPM-adsorption-property matrix from NIST-ISODB; the explanations include both data-centric and model-centric concerns. First, the Henry coefficient matrix we constructed based on NIST-ISODB was only ∼20 % complete (i.e., too many missing values), which may have limited the success of recommendations for the remainder of the matrix. (Recall that the COF-adsorption-property matrix needed to be at least 40 % complete to satisfactorily make recommendations for the remainder of the matrix. This benchmark for the COF recommender system may not generalize to a broad set of NPMs and properties, but is nonetheless informative.) Second, the NPM-adsorption-property matrix may have included too much noise for a successful recommendation. It is known from meta-analyses of isotherms catalogued in NIST-ISODB that experimentally measured gas adsorption isotherms in NPMs exhibit high variance; this variance is ultimately manifested as noise that limits the success of the recommendation system. Third, the accuracy and reliability of Henry coefficients obtained from isotherms in NIST-ISODB are naturally limited by the source of data in the database itself. NIST-ISODB is primarily constructed from manual extraction of isotherm data from graphical figures in literature articles, since it is not common practice in the adsorption community to provide gas adsorption measurements as raw tabular data in publications. (As of the time of writing this work, only 1.3 % of isotherms in NIST-ISODB were from tabular data sources.) Consequently, the adsorption isotherm data loses precision first when the data is plotted graphically and second by human error when the graphical figure is digitized back to numerical data. This loss of precision particularly affects the generation of Henry coefficients from figures, as those coefficients are especially dependent on low-pressure data, which is often difficult to extract from isotherms plotted on a linear pressure scale. Fourth, our low rank model in eqn. 1 is linear; a non-linear model of the matrix may be able to capture relationships between the adsorption properties and achieve better performance. The third issue can be addressed by community adoption of the practice of releasing raw adsorption isotherm data in standardized, structured formats (cf. the CIF standard for crystallography ), which has been discussed previously .