Keyword search is the foremost approach for searching information and it has been successfully applied for retrieving non-structured documents such as text and multimedia files. Nonetheless, retrieving information from (unstructured or semi-structured) documents is intrinsically different from querying structured data sources with either an explicit schema, as relational databases or triple stores, or an implicit one, as tables in textual documents and on the Web. Consequently this model has left out the structured data sources which are typically accessed through structured queries, e.g. Structured Query Language (SQL) queries over relational databases or SPARQL Protocol and RDF Query Language (SPARQL) queries over Linked Data graphs. Structured queries are not end-user oriented and far away from a natural expression of users' information needs by means of keywords, given that their formulation is based on a quite complex syntax and requires some knowledge about the structure of the data to be queried. Over the past several years, these facts triggered the research community and big data technology vendors to put a lot of effort into developing new approaches for keyword search over structured databases and it is still a primary research and industrial concern.
There are three main issues currently hampering the design and development of next generation systems for keyword search over structured data able to effectively address the needs described above: 
(i) the lack of systemic approaches considering all of the issues of keyword search from the formulation and interpretation of the user needs, to the computation, retrieval, ranking and presentation of the results as well as the model by which iterative refinement is supported; 
(ii) the wide variety of tasks and domains (product to financial, public-record, health and drugs, scientific publications, hobby-related, and government, …) which keyword search techniques need to address and which require the development of customized specific solutions. This make the design of a “general purpose” keyword search application a complex task;
(iii) the absence of a shared and complete evaluation methodology measuring user satisfaction, achieved utility, both effectiveness and efficiency, as well as required user effort for carrying out informative tasks on keyword-search systems on structured data.
The aim of this multidisciplinary workshop is to bring together researchers from Databases, Information Retrieval, Natural Language Processing, Semantic Web, Human-Computer Interaction, and to combine their perspectives and research to address the above-mentioned issues. 
In particular, we wish to encourage researchers to discuss the opportunities, challenges, results obtained in the development and evaluation of “complete”, “ready-to-market” keyword search applications over structured data. We are in particular interested in proposal dealing with systemic approaches which manage all the phases of the keyword search, from the management of the data, query formulation, interpretation, computation, ranking and visualization of the results, as well as rigorous evaluation methodologies for such systems.