We present a cloud-computing environment, referred to as AtomPy, based on Google-Drive Sheets and Pandas (Python Data Analysis Library) DataFrames to promote community-driven curation of atomic data for astrophysical applications, a stage beyond database development. The atomic model for each ionic species is contained in a multi-sheet workbook, tabulating representative sets of energy levels, A-values and electron impact effective collision strengths from different sources. The relevant issues that AtomPy intends to address are: (i) data quality by allowing open access to both data producers and users; (ii) comparisons of different datasets to facilitate accuracy assessments; (iii) downloading to local data structures (i.e., Pandas DataFrames) for further manipulation and analysis by prospective users; and (iv) data preservation by avoiding the discard of outdated sets. Data processing workflows are implemented by means of IPython Notebooks, and collaborative software developments are encouraged and managed within the GitHub social network. The facilities of AtomPy are illustrated with the critical assessment of the transition probabilities for ions in the hydrogen and helium isoelectronic sequences with atomic number Z ≤ 10.