In recent years, data storage has emerged as an important research field driven by the demand for scalable structures and technologies to satisfy the growing needs of massive data management and processing. Big Data challenges storage systems with more capacity, scalability and efficient accessibility. Dispersing a huge data object in a large-scale distributed storage system is necessary to enhance data reliability and availability. By introducing redundancy in the system, we can protect data integrity from node failures. As node failures occur frequently in large-scale storage systems, a considerable volume of network traffic is dedicated to the repair of failed storage nodes. Several classes of distributed storage codes, such as regenerating codes, locally repairable codes, have been introduced recently to reduce this overhead and disk input/output cost. However, there still remains substantial research work for advancing distributed storage coding and systems in both theory and applications. This workshop will provide an excellent platform for researchers and practitioners from academia and industry to exchange ideas and experiences that distributed storage systems can offer to Big Data applications, and to understand the challenges that we need tackle to realize the full potential.