Benchmarking Big Data solutions has been gaining a lot of attention from research and industry. BigBench is one of the most popular benchmarks in this area which was adopted by the TPC as TPCx-BB. BigBench, however, has key shortcomings. The structured component of the data model is the same as the TPC-DS data model which is a complex snowflake-like schema. This is contrary to the simple star schema Big Data models in real life. BigBench also treats the semi-structured web-logs more or less as a structured table. In real life, web-logs are modeled as key-value pairs with unknown schema. Specific keys are captured at query time - a process referred to as late binding. In addition, eleven (out of thirty) of the BigBench queries are TPC-DS queries. These queries are complex SQL applied on the structured part of the data model which again is not typical of Big Data workloads. In this paper1, we present BigBench V2 to address the aforementioned limitations of the original BigBench. BigBench V2 is completely independent of TPC-DS with a new data model and an overhauled workload. The new data model has a simple structured data model. Web-logs are modeled as key-value pairs with a substantial and variable number of keys. BigBench V2 mandates late binding by requiring query processing to be done directly on key-value web-logs rather than a pre-parsed form of it. A new scale factor-based data generator is implemented to produce structured tables, key-value semistructured web-logs, and unstructured data. We implemented and executed BigBench V2 on Hive. Our proof of concept shows the feasibility of BigBench V2 and outlines different ways of implementing late binding.

The interest to become a data scientist or related professions in data science domain is rapidly growing. To meet such a demand, we propose a novel educational service that aims to provide a tailored learning paths for data science. Our target user is one who aims to be an expert in data science. Our approach is to analyze the background of the practitioner and match the learning units. A critical feature is that we use gamification to reinforce the practitioner engagement. We believe that our work provides a practical guideline for those who wants to learn data science.

SUMMARY A Web user is exposed to a large number of information services available from different sources. Online news is offered combined with relevant service attributes such as pictures, small text, users' recommendations, etc. We previously investigated the Web user's choice of online news, focusing on the trade‐offs between reputation and other service attributes, which may explain the user's choice of an unknown source, such as a blog. In the present study, we investigate the Web user's choice of online news in a multi‐attribute context. Our findings indicate that the most important service attribute is the accompanying text, followed by the source's reputation, then the percentage of readers recommending or having read the link, and then the picture. We further explore the trade‐offs between the attributes through simulations. These findings provide useful insights to practitioners on how to use the service attributes in the framing strategies in order to increase the probability of the choice of online news. Copyright © 2011 John Wiley & Sons, Ltd.

SUMMARY Big Web companies, traditional enterprises, physical science researchers, social scientists, are all experiencing (or anticipating) unprecedented growth in the amount of data available in their domain. There are new opportunities and great untapped value in analyzing ‘Big Data’.Copyright © 2012 John Wiley & Sons, Ltd.

In this paper we present a framework analysis for managing the feedback explicitly given by visitors of a Web site. We introduce the concepts of scope, filtering, and relevance profiles for managing users' feedback, and show their applicability by using Gugubarra as a reference system, a prototype developed by DBIS at the Goethe University of Frankfurt, for creating and managing user profiles of Web visitors.

Abstract Current trends on the Internet indicate an increasing supply of content from anonymous users (e.g. blogs), which may become popular among website visitors. Motivated by these Internet trends, the present study explores the tradeoffs between the source's reputation and the way content is displayed or offered on the web page as well as the effects of both on the Internet user's choice of information services. The study builds upon behavioral economics and focuses on the interaction between background and local context effects on the individual's choice. In particular, the study investigates the tradeoffs between the source's reputation, representing the background context and the provision of enriched content (e.g. source bundled with a picture or a video) representing local context. The research involved a set of experiments based on hypothetical choice or matching tasks. The main findings indicate that there are significant interaction effects between reputation and enriched content, in the form of content related pictures, video and users' recommendations, which affect the user's choice of information services. Copyright © 2009 John Wiley & Sons, Ltd.

We have introduced the concept of non-obvious user profiles (NOPs) to capture the hypothetical interest of Web users. In this paper we present the design principles and rules of our Gugubarra engine, which is a tool to calculate and visualize these non-obvious user profiles

A seamless approach to the incremental design and reuse of object oriented methods and query specifications is presented. We argue for avoiding or minimizing the effort required for manually reprogramming methods and queries due to schema modifications, and demonstrate how the role of polymorphic reuse mechanisms is exploited for enhancing the adaptiveness of database programs against schema evolution in an object oriented database. The salient features of our approach are the use of propagation patterns and a mechanism for propagation pattern refinement. Propagation patterns are employed as an interesting specification formalism for modeling operational requirements. They encourage the reuse of operational specifications against the structural modification of an object oriented schema. Propagation pattern refinement is suited for the specification of reusable operational modules. It promotes the reusability of propagation patterns toward the operational requirement changes. This approach has a formal basis and emphasizes structural derivation of specifications. The main innovations are in raising the level of abstraction for behavioral schema design, and for making possible the derivation of operational semantics from structural specifications. As a result, both the modularity and reusability of object oriented schemas are increased.

A polymorphic approach to the incremental design and reuse of object-oriented methods and query specifications is presented. Using this approach, the effort required for manually reprogramming methods and queries due to schema modifications can be avoided or minimized. The salient features of of our approach are the use of propagation patterns and a mechanism for propagation pattern refinement. Propagation patterns can be employed as an interesting specification formalism for modeling operational requirements in object-oriented database systems. They encourage the reuse of operational specifications against the structural modification of an object-oriented schema. Propagation pattern refinement is suited for the specification of reusable operational modules, and for achieving reusability of propagation patterns towards the operational requirement changes.>

A 'reasonable' minimal set of primitives for updating an object-oriented (O/sub 2/) database schema is defined and the problems which need to be solved in order to obtain a usable schema update mechanism are shown. The distinction between structural and behavioral consistency for the O/sub 2/ system is described in some detail and it is demonstrated how updates could be performed by invoking an interactive tool. Updates are classified in three categories. Each category is explained in detail.>

LOGRES is a new project for the development of extended database systems which is based on the integration of the object-oriented data modelling paradigm and of the rule-based approach for the specification of queries and updates.

We describe a data model for structured office information objects, which we generically call “documents,” and a practically useful algebraic language for the retrieval and manipulation of such objects. Documents are viewed as hierarchical structures; their layout (presentation) aspect is to be treated separately. The syntax and semantics of the language are defined precisely in terms of the formal model, an extended relational algebra. The proposed approach has several new features, some of which are particularly useful for the management of office information. The data model is based on nested sequences of tuples rather than nested relations. Therefore, sorting and sequence operations and the explicit handling of duplicates can be described by the model. Furthermore, this is the first model based on a many-sorted instead of a one-sorted algebra, which means that atomic data values as well as nested structures are objects of the algebra. As a consequence, arithmetic operations, aggregate functions, and so forth can be treated inside the model and need not be introduced as query language extensions to the model. Many-sorted algebra also allows arbitrary algebra expressions (with Boolean result) to be admitted as selection or join conditions and the results of arbitrary expressions to be embedded into tuples. In contrast to other formal models, this algebra can be used directly as a rich query language for office documents with precisely defined semantics.

The problem of translating view updates to database updates is considered. Both databases and views are modeled as data abstractions. A data abstraction consists of a set of states and of a set of primitive update operators representing state transition functions. It is shown how complex update programs can be built from primitive update operators and how view update programs are translated into database update programs. Special attention is paid to a class of views that we call “consistent.” Loosely speaking, a consistent view is a view with the following property: If the effect of a view update program on a view state is determined, then the effect of the corresponding database update is unambiguously determined. Thus, in order to know how to translate a given view update into a database update, it is sufficient to be aware of a functional specification of such a program. We show that consistent views have a number of interesting properties with respect to the concurrency of (high-level) update transactions. Moreover we show that the class of consistent views includes as a subset the class of views that translate updates under maintenance of a constant complement. However, we show that there exist consistent views that do not translate under constant complement. The results of Bancilhon and Spyratos [6] are generalized in order to capture the update semantics of the entire class of consistent views. In particular we show that the class of consistent views is obtained if we relax the requirement of a constant complement by allowing the complement to decrease according to a suitable partial order.