# A Scalable and Semantic Data as a Service Marketplace for Enhancing Cloud-Based Applications
## 1 Introduction  
### General Concepts  
One of the most-used expressions regarding data-driven IT is \"data are the new oil\". Given the gravity of this statement, many concepts and technologies have arisen in order to address the needs of this new era. More specifically, this paper revolves around two main concepts; Data as a Service (DaaS) and the Data Marketplace. In order to fully exploit the data produced by any given sector, there is a need to streamline the process of collection, storage, access, utilization and, finally, delivery to the end user. DaaS aims at creating a service-based model that will cover the complete lifecycle of the data through distributed interconnected services that address the requirements of each aforementioned step of the streamlined process. To better understand the involvement of DaaS in the lifecycle of data, it is important to mention the main characteristics of a DaaS solution. It is important that a DaaS solution can provide data and deliver them at different levels of granularity depending on the end users' needs. Given the heterogeneity of the data delivered, even from a single data producer, it is necessary to be able to handle different data sources with different types of datain terms of content, schema, and type of delivery (e.g., streaming, batch). Network heterogeneity, as well as the addition and reduction of data sources, are strongly considered in this type of solution. Last but not least it is necessary to have a monitoring and evaluation mechanism in order to maintain the expected Quality of Service (QoS) and Quality of Data (QoD). Despite the requirement coverage of the data lifecycle from the DaaS model, data still need to be discoverable and presented to the end user in a uniform way. The Data Marketplace concept aims at creating a marketplace in which users are able to discover data with the desired content and quality. In order to create a Data Marketplace, the most important step is to describe and deliver the data as a product. Converting data into a product is a procedure that is well defined by the DaaS model, as described in the previous paragraph. In order to sell data as product specific, metrics must derive from them. Potential buyers need to know the volume, cost, value, quality, and other important metrics that evaluate the data [1]. Although there is significant work on the conversion of data as a product in the context of Data Marketplaces (also described in Section 2), in many sectors (critical infrastructure, edge, cloud, and fog computing) the data are evolving in a direction where static data degenerate to hold no value. These types of sectors require a service-based model for data delivery in order to explore the huge amount of data that is created and processed in real time [2]. This new era of data has created the need for Data Marketplaces that not only deliver data as a product but most importantly create DaaS products [1]. DaaS product creation requires not only the definition of data as a product but also the definition of the service that delivers the data, as a product. The most important characteristic of the service that is needed to be identified and described in order to achieve this goal is the definition of the QoS of the service that delivers the data. As far as the DaaS Marketplace is concerned the QoD metric production, as well as delivery, is firmly established. One of the less evolved procedures is the QoS part of the product creation. This paper aims at describing and establishing specific software components in order to enable the delivery of DaaS products. The enhancements proposed in the context of the DaaS Marketplace are based on three main needs identified for these types of marketplace:  
* Content discovery: A semantically enhanced content discovery component that aids the data buyer to find the most suitable data as far as the content is concerned. Also, aids the data provider to better describe their data in order to make them more easily discoverable.