Physicists performing LHC data analyses, are required to be well-versed in programming and the particular analysis framework of the associated experiment. The steep learning curve related to these erects a barrier between the data and the physicist who may simply wish to try out an analysis idea.
The abundance of inexpensive, powerful, easy to use computing power leads to a fundamental shift in data analysis. The development of a full-fledged text-based analysis algorithm description language (ADL), incorporating also logic and mathematical expressions, would eliminate all kinds of programming difficulties and errors, consequently allowing the scientist to focus on the goal, but not on the tool. This presentation discusses the guiding principles of such an ADL and gives CutLang as an example. A number of LHC analyses of various complexities will also be shown to illustrate the advantages of a human readable ADL.