Benchmark datasets are important in document image processing field, as they allow to analyze different approaches and compare their performances in a fair manner. There exist benchmark datasets for several alphabets such as Latin, Arabic and Chinese, but not the Hebrew alphabet. In this paper, a handwritten Hebrew dataset, HHD, is introduced. The HHD dataset is collected from hand-filled forms, and accompanied by their ground truth at character, word and text line levels. Presently, the dataset contains around 1000 document images, and we continue to further enlarge it. To the best of our knowledge, this is the first comprehensive corpus of Hebrew handwritten documents, and we believe it will help leveraging Hebrew documents processing and document processing in general. The dataset can be useful for various research applications, such as word spotting, word recognition, text line alignment, and writer identification. The initial small subset of the HDD for character classification can be downloaded from https://www.cs.bgu.ac.illr-vberatldatalhhd-dataset.zip together with the training and test sets subdivisions. We also provide baseline results for character classification on this initial subset. In the near future, the full HHD dataset will be made freely available to the research community.