This is a sample piece from a dataset of interaction logs recorded from software company employees. The data set is recorded at an overseas branch office of a Japanese software development company. The subjects are 18 employees of this branch office, who have varying qualifications and responsibilities. The data collection campaign is carried out with the consent of the company. The subjects are informed in a clear manner about the nature and method of the research, and agreed to participate in the experiments. The data set is composed of the employees' interactions logs, which are basically a registry of their interaction with the GUI. The recording software is a user activity monitoring tool called TaskPit [1], which is designed to be deployed particularly at software development companies. Specifically, it registers a log file containing the name of the active application (i.e. exe name), start and end time of its deployment, its window title, and number of left clicks, right clicks, and key strokes on the active window. We consider each line of the log file to arise from an action of the subject. Moreover, each action is considered to be associated with a single task of the subject (e.g. Programming) and the tasks associated with those actions are exactly what our study intends to unveil. A coder, who is a senior student at the department of computer science of Okayama University, carried out manual annotation by assigning a single task to each action (i.e. each line of the log file). To that end, he evaluated the information contained in the columns of the log file and selected one task from the set of potential tasks. Here, by taking into account the background information of the subjects (i.e. being employees of software development company) and the expectations and requirements of our corporate partner, the set of potential tasks is tailored to be comprised of Programming, Test, Documentation, Administration, and Leisure. Note that by documentation we refer to reading, writing or editing of project documentation. The data set is used to test the task estimation method proposed in our article submitted to Empirical Software Engineering (currently under review) [2]. The codes generated during the current study are publicly available at our repository [3]. References: [1] Suthipornopas P, Leelaprute P, Monden A, Uwano H, Kamei Y, Ubayashi N, Araki K, Yamada K, Matsumoto K (2017) Industry application of software development task measurement system: Taskpit. IEICE Transactions on Information and Systems (3):462–472 [2] Pellegrin F, Yücel Z, Monden A., Leelaprute P. , Estimating tasks of software company employees based on computer interaction logs, Empirical Software Engineering (under review) [3] Yücel Z, Software applications and custom codes. https://github.com/yucelzeynep/Task-estimation-from-activity-logs, 2020