% This data is distributed under the terms of the Open Data Commons Attribution License (ODC-By) v1.0 - See more at: http://opendatacommons.org/licenses/by/1-0/
    @Article{OJIS_2016v3i1n02_Marinette,
        title     = {A NoSQL-Based Framework for Managing Home Services},
        author    = {Marinette Bouet and
                     Michel Schneider},
        journal   = {Open Journal of Information Systems (OJIS)},
        issn      = {2198-9281},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {1--28},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194810},
        urn       = {urn:nbn:de:101:1-201705194810},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Individuals and companies have an increasing need for services by specialized suppliers in their homes or premises. These services can be quite different and can require different amounts of resources. Service suppliers have to specify the activities to be performed, plan those activities, allocate resources, follow up after their completion and must be able to react to any unexpected situation. Various proposals were formulated to model and implement these functions; however, there is no unified approach that can improve the efficiency of software solutions to enable economy of scale. In this paper, we propose a framework that a service supplier can use to manage geo-localized activities. The proposed framework is based on a NoSQL data model and implemented using the MongoDB system. We also discuss the advantages and drawbacks of a NoSQL approach.}
    }
    @Article{OJDB_2016v3i1n01_Menninghaus,
        title     = {High-Dimensional Spatio-Temporal Indexing},
        author    = {Mathias Menninghaus and
                     Martin Breunig and
                     Elke Pulverm{\"u}ller},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {1--20},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194635},
        urn       = {urn:nbn:de:101:1-201705194635},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {There exist numerous indexing methods which handle either spatio-temporal or high-dimensional data well. However, those indexing methods which handle spatio-temporal data well have certain drawbacks when confronted with high-dimensional data. As the most efficient spatio-temporal indexing methods are based on the R-tree and its variants, they face the well known problems in high-dimensional space. Furthermore, most high-dimensional indexing methods try to reduce the number of dimensions in the data being indexed and compress the information given by all dimensions into few dimensions but are not able to store now - relative data. One of the most efficient high-dimensional indexing methods, the Pyramid Technique, is able to handle high-dimensional point-data only. Nonetheless, we take this technique and extend it such that it is able to handle spatio-temporal data as well. We introduce a technique for querying in this structure with spatio-temporal queries. We compare our technique, the Spatio-Temporal Pyramid Adapter (STPA), to the RST-tree for in-memory and on-disk applications. We show that for high dimensions, the extra query-cost for reducing the dimensionality in the Pyramid Technique is clearly exceeded by the rising query-cost in the RST-tree. Concluding, we address the main drawbacks and advantages of our technique.}
    }
    @Article{OJIS_2016v3i1n02_Harwardt,
        title     = {Criteria of Successful IT Projects from Management's Perspective},
        author    = {Mark Harwardt},
        journal   = {Open Journal of Information Systems (OJIS)},
        issn      = {2198-9281},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {29--54},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194797},
        urn       = {urn:nbn:de:101:1-201705194797},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The aim of this paper is to compile a model of IT project success from management's perspective. Therefore, a qualitative research approach is proposed by interviewing IT managers on how their companies evaluate the success of IT projects. The evaluation of the survey provides fourteen success criteria and four success dimensions. This paper also thoroughly analyzes which of these criteria the management considers especially important and which ones are being missed in daily practice. Additionally, it attempts to identify the relevance of the discovered criteria and dimensions with regard to the determination of IT project success. It becomes evident here that the old-fashioned Iron Triangle still plays a leading role, but some long-term strategical criteria, such as value of the project, customer perspective or impact on the organization, have meanwhile caught up or pulled even.}
    }
    @Article{OJCC_2016v3i1n02_YingweiWang,
        title     = {Definition and Categorization of Dew Computing},
        author    = {Yingwei Wang},
        journal   = {Open Journal of Cloud Computing (OJCC)},
        issn      = {2199-1987},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {1--7},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194546},
        urn       = {urn:nbn:de:101:1-201705194546},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Dew computing is an emerging new research area and has great potentials in applications. In this paper, we propose a revised definition of dew computing. The new definition is: Dew computing is an on-premises computer software-hardware organization paradigm in the cloud computing environment where the on-premises computer provides functionality that is independent of cloud services and is also collaborative with cloud services. The goal of dew computing is to fully realize the potentials of on-premises computers and cloud services. This definition emphasizes two key features of dew computing: independence and collaboration. Furthermore, we propose a group of dew computing categories. These categories may inspire new applications.}
    }
    @Article{OJDB_2016v3i1n02_Werner,
        title     = {Runtime Adaptive Hybrid Query Engine based on FPGAs},
        author    = {Stefan Werner and
                     Dennis Heinrich and
                     Sven Groppe and
                     Christopher Blochwitz and
                     Thilo Pionteck},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {21--41},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194645},
        urn       = {urn:nbn:de:101:1-201705194645},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper presents the fully integrated hardware-accelerated query engine for large-scale datasets in the context of Semantic Web databases. As queries are typically unknown at design time, a static approach is not feasible and not flexible to cover a wide range of queries at system runtime. Therefore, we introduce a runtime reconfigurable accelerator based on a Field Programmable Gate Array (FPGA), which transparently incorporates with the freely available Semantic Web database LUPOSDATE. At system runtime, the proposed approach dynamically generates an optimized hardware accelerator in terms of an FPGA configuration for each individual query and transparently retrieves the query result to be displayed to the user. During hardware-accelerated execution the host supplies triple data to the FPGA and retrieves the results from the FPGA via PCIe interface. The benefits and limitations are evaluated on large-scale synthetic datasets with up to 260 million triples as well as the widely known Billion Triples Challenge.	}
    }
    @Article{OJWT_2016v3i1n02_Meghini,
        title     = {Query Processing in a P2P Network of Taxonomy-based Information Sources},
        author    = {Carlo Meghini and
                     Anastasia Analyti},
        journal   = {Open Journal of Web Technologies (OJWT)},
        issn      = {2199-188X},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {1--25},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705291402},
        urn       = {urn:nbn:de:101:1-201705291402},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In this study we address the problem of answering queries over a peer-to-peer system of taxonomy-based sources. A taxonomy states subsumption relationships between negation-free DNF formulas on terms and negation-free conjunctions of terms. To the end of laying the foundations of our study, we first consider the centralized case, deriving the complexity of the decision problem and of query evaluation. We conclude by presenting an algorithm that is efficient in data complexity and is based on hypergraphs. We then move to the distributed case, and introduce a logical model of a network of taxonomy-based sources. On such network, a distributed version of the centralized algorithm is then presented, based on a message passing paradigm, and its correctness is proved. We finally discuss optimization issues, and relate our work to the literature.}
    }
    @Article{OJIOT_2016v2i1n02_Yamaguchi,
        title     = {A 24 GHz FM-CW Radar System for Detecting Closed Multiple Targets and Its Applications in Actual Scenes},
        author    = {Kazuhiro Yamaguchi and
                     Mitumasa Saito and
                     Takuya Akiyama and
                     Tomohiro Kobayashi and
                     Naoki Ginoza and
                     Hideaki Matsue},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2016},
        volume    = {2},
        number    = {1},
        pages     = {1--15},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704245003},
        urn       = {urn:nbn:de:101:1-201704245003},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper develops a 24 GHz band FM-CW radar system to detect closed multiple targets in a small displacement environment, and its performance is analyzed by computer simulation. The FM-CW radar system uses a differential detection method for removing any signals from background objects and uses a tunable FIR filtering in signal processing for detecting multiple targets. The differential detection method enables the correct detection of both the distance and small displacement at the same time for each target at the FM-CW radar according to the received signals. The basic performance of the FM-CW radar system is analyzed by computer simulation, and the distance and small displacement of a single target are measured in field experiments. The computer simulations are carried out for evaluating the proposed detection method with tunable FIR filtering for the FM-CW radar and for analyzing the performance according to the parameters in a closed multiple targets environment. The results of simulation show that our 24 GHz band FM-CW radar with the proposed detection method can effectively detect both the distance and the small displacement for each target in multiple moving targets environments. Moreover, we develop an IoT-based application for monitoring several targets at the same time in actual scenes.}
    }
    @Article{OJSW_2016v3i1n01_Peixoto,
        title     = {Hierarchical Multi-Label Classification Using Web Reasoning for Large Datasets},
        author    = {Rafael Peixoto and
                     Thomas Hassan and
                     Christophe Cruz and
                     Aur\'{e}lie Bertaux and
                     Nuno Silva},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {1--15},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194907},
        urn       = {urn:nbn:de:101:1-201705194907},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Extracting valuable data among large volumes of data is one of the main challenges in Big Data. In this paper, a Hierarchical Multi-Label Classification process called Semantic HMC is presented. This process aims to extract valuable data from very large data sources, by automatically learning a label hierarchy and classifying data items.The Semantic HMC process is composed of five scalable steps, namely Indexation, Vectorization, Hierarchization, Resolution and Realization. The first three steps construct automatically a label hierarchy from statistical analysis of data. This paper focuses on the last two steps which perform item classification according to the label hierarchy. The process is implemented as a scalable and distributed application, and deployed on a Big Data platform. A quality evaluation is described, which compares the approach with multi-label classification algorithms from the state of the art dedicated to the same goal. The Semantic HMC approach outperforms state of the art approaches in some areas.}
    }
    @Article{OJSW_2016v3i1n02_Tatu,
        title     = {A Semantic Question Answering Framework for Large Data Sets},
        author    = {Marta Tatu and
                     Mithun Balakrishna and
                     Steven Werner and
                     Tatiana Erekhinskaya and
                     Dan Moldovan},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {16--31},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194921},
        urn       = {urn:nbn:de:101:1-201705194921},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Traditionally, the task of answering natural language questions has involved a keyword-based document retrieval step, followed by in-depth processing of candidate answer documents and paragraphs. This post-processing uses semantics to various degrees. In this article, we describe a purely semantic question answering (QA) framework for large document collections. Our high-precision approach transforms the semantic knowledge extracted from natural language texts into a language-agnostic RDF representation and indexes it into a scalable triplestore. In order to facilitate easy access to the information stored in the RDF semantic index, a user's natural language questions are translated into SPARQL queries that return precise answers back to the user. The robustness of this framework is ensured by the natural language reasoning performed on the RDF store, by the query relaxation procedures, and the answer ranking techniques. The improvements in performance over a regular free text search index-based question answering engine prove that QA systems can benefit greatly from the addition and consumption of deep semantic information.}
    }
    @Article{OJSW_2016v3i1n03_Smid,
        title     = {OnGIS: Semantic Query Broker for Heterogeneous Geospatial Data Sources},
        author    = {Marek Smid and
                     Petr Kremen},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {32--50},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194936},
        urn       = {urn:nbn:de:101:1-201705194936},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Querying geospatial data from multiple heterogeneous sources backed by different management technologies poses an interesting problem in the data integration and in the subsequent result interpretation. This paper proposes broker techniques for answering a user's complex spatial query: finding relevant data sources (from a catalogue of data sources) capable of answering the query, eventually splitting the query and finding relevant data sources for the query parts, when no single source suffices. For the purpose, we describe each source with a set of prototypical queries that are algorithmically arranged into a lattice, which makes searching efficient. The proposed algorithms leverage GeoSPARQL query containment enhanced with OWL 2 QL semantics. A prototype is implemented in a system called OnGIS.}
    }
    @Article{OJBD_2016v2i101_Moon,
        title     = {Conformance of Social Media as Barometer of Public Engagement},
        author    = {Songchun Moon},
        journal   = {Open Journal of Big Data (OJBD)},
        issn      = {2365-029X},
        year      = {2016},
        volume    = {2},
        number    = {1},
        pages     = {1--10},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194393},
        urn       = {urn:nbn:de:101:1-201705194393},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {There have been continuously a number of expectations: Social media may play a role of indicator that shows the degree of engagement and preference of choices of users toward music or movies. However, finding appropriate software tools in the market to verify this sort of expectation is too costly and complicated in their natures, and this causes a number of difficulties to attempt technical experimentation. A convenient and easy tool to facilitate such experimentation was developed in this study and was used successfully for performing various measurements with regard to user engagement in music and movies.}
    }
    @Article{OJDB_2016v3i1n03_Koch,
        title     = {XML-based Execution Plan Format (XEP)},
        author    = {Christoph Koch},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {42--52},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194654},
        urn       = {urn:nbn:de:101:1-201705194654},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Execution plan analysis is one of the most common SQL tuning tasks performed by relational database administrators and developers. Currently each database management system (DBMS) provides its own execution plan format, which supports system-specific details for execution plans and contains inherent plan operators. This makes SQL tuning a challenging issue. Firstly, administrators and developers often work with more than one DBMS and thus have to rethink among different plan formats. In addition, the analysis tools of execution plans only support single DBMSs, or they have to implement separate logic to handle each specific plan format of different DBMSs. To address these problems, this paper proposes an XML-based Execution Plan format (XEP), aiming to standardize the representation of execution plans of relational DBMSs. Two approaches are developed for transforming DBMS-specific execution plans into XEP format. They have been successfully evaluated for IBM DB2, Oracle Database and Microsoft SQL.}
    }
    @Article{OJCC_2016v3i1n02_Fisher,
        title     = {Doing More with the Dew: A New Approach to Cloud-Dew Architecture},
        author    = {David Edward Fisher and
                     Shuhui Yang},
        journal   = {Open Journal of Cloud Computing (OJCC)},
        issn      = {2199-1987},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {8--19},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194535},
        urn       = {urn:nbn:de:101:1-201705194535},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {While the popularity of cloud computing is exploding, a new network computing paradigm is just beginning. In this paper, we examine this exciting area of research known as dew computing and propose a new design of cloud-dew architecture. Instead of hosting only one dew server on a user's PC - as adopted in the current dewsite application - our design promotes the hosting of multiple dew servers instead, one for each installed domain. Our design intends to improve upon existing cloud-dew architecture by providing significantly increased freedom in dewsite development, while also automating the chore of managing dewsite content based on the user's interests and browsing habits. Other noteworthy benefits, all at no added cost to dewsite users, are briefly explored as well.}
    }
    @Article{OJIOT-2016v2i1n02_Aubonnet,
        title     = {Controlled Components for Internet of Things As-A-Service},
        author    = {Tatiana Aubonnet and
                     Amina Boubendir and
                     Fr\'{e}d\'{e}ric Lemoine and
                     N{\"o}emie Simoni},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2016},
        volume    = {2},
        number    = {1},
        pages     = {16--33},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244995},
        urn       = {urn:nbn:de:101:1-201704244995},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In order to facilitate developers willing to create future Internet of Things (IoT) services incorporating the nonfunctional aspects, we introduce an approach and an environment based on controlled components. Our approach allows developers to design an IoT "as-a-service", to build the service composition and to manage it. This is important, because the IoT allows us to observe and understand the real world in order to have decision-making information to act on reality. It is important to make sure that all these components work according to their mission, i.e. their Quality of Service (QoS) contract. Our environment provides the modeling, generates Architecture Description Language (ADL) formats, and uses them in the implementation phase on an open-source platform.}
    }
    @Article{OJBD_2016v2i1n02_Groppe,
        title     = {Constructing Large-Scale Semantic Web Indices for the Six RDF Collation Orders},
        author    = {Sven Groppe and
                     Dennis Heinrich and
                     Christopher Blochwitz and
                     Thilo Pionteck},
        journal   = {Open Journal of Big Data (OJBD)},
        issn      = {2365-029X},
        year      = {2016},
        volume    = {2},
        number    = {1},
        pages     = {11--25},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194418},
        urn       = {urn:nbn:de:101:1-201705194418},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Semantic Web community collects masses of valuable and publicly available RDF data in order to drive the success story of the Semantic Web. Efficient processing of these datasets requires their indexing. Semantic Web indices make use of the simple data model of RDF: The basic concept of RDF is the triple, which hence has only 6 different collation orders. On the one hand having 6 collation orders indexed fast merge joins (consuming the sorted input of the indices) can be applied as much as possible during query processing. On the other hand constructing the indices for 6 different collation orders is very time-consuming for large-scale datasets. Hence the focus of this paper is the efficient Semantic Web index construction for large-scale datasets on today's multi-core computers. We complete our discussion with a comprehensive performance evaluation, where our approach efficiently constructs the indices of over 1 billion triples of real world data.}
    }
    @Article{OJBD_2016v2i1n03e_Chang,
        title     = {New Areas of Contributions and New Addition of Security},
        author    = {Victor Chang},
        journal   = {Open Journal of Big Data (OJBD)},
        issn      = {2365-029X},
        year      = {2016},
        volume    = {2},
        number    = {1},
        pages     = {26--28},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194405},
        urn       = {urn:nbn:de:101:1-201705194405},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Open Journal of Big Data (OJBD) (www.ronpub.com/ojbd) is an open access journal, which addresses the aspects of Big Data, including new methodologies, processes, case studies, poofs-of-concept, scientific demonstrations, industrial applications and adoption. This editorial presents two articles published in the first issue of the second volume of OJBD. The first article is about the investigation of social media for the public engagement. The second article looks into large-scale semantic web indices for six RDF collation orders. OJBD has an increasingly improved reputation thanks to the support of research communities. We will set up the Second International Conference on Internet of Things, Big Data and Security (IoTBDS 2017), in Porto, Portugal, between 24 and 26 April 2017. OJBD is published by RonPub (www.ronpub.com), which is an academic publisher of online, open access, peer-reviewed journals.}
    }