BibTex:

    @Article{OJDB-v1i2n02_Abramova,
        title     = {Which NoSQL Database? A Performance Overview},
        author    = {Veronika Abramova and
                     Jorge Bernardino and
                     Pedro Furtado},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {17--24},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194607},
        urn       = {urn:nbn:de:101:1-201705194607},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {NoSQL data stores are widely used to store and retrieve possibly large amounts of data, typically in a key-value format. There are many NoSQL types with different performances, and thus it is important to compare them in terms of performance and verify how the performance is related to the database type. In this paper, we evaluate five most popular NoSQL databases: Cassandra, HBase, MongoDB, OrientDB and Redis. We compare those databases in terms of query performance, based on reads and updates, taking into consideration the typical workloads, as represented by the Yahoo! Cloud Serving Benchmark. This comparison allows users to choose the most appropriate database according to the specific mechanisms and application needs.}
    }

BibTex:

    @Article{OJWT-v1i2n01_Hoernig,
        title     = {A Comparative Evaluation of Current HTML5 Web Video Implementations},
        author    = {Martin Hoernig and
                     Andreas Bigontina and
                     Bernd Radig},
        journal   = {Open Journal of Web Technologies (OJWT)},
        issn      = {2199-188X},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {1--9},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705291328},
        urn       = {urn:nbn:de:101:1-201705291328},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {HTML5 video is the upcoming standard for playing videos on the World Wide Web. Although its specification has not been fully adopted yet, all major browsers provide the HTML5 video element and web developers already rely on its functionality. But there are differences between implementations and inaccuracies that trouble the web developer community. To help to improve the current situation we draw a comparison between the most important web browsers. We focus on the event mechanism, since it is essential for interacting with the video element. Furthermore, we compare the seeking accuracy, which is relevant for more specialized applications. Our tests reveal varieties of differences between browser interfaces and show that even simple software solutions may still need third-party plugins in today's browsers.}
    }

BibTex:

    @Article{OJIOT_2015v1i2n03_Cho,
        title     = {Accurate Distance Estimation between Things: A Self-correcting Approach},
        author    = {Ho-sik Cho and
                     Jianxun Ji and
                     Zili Chen and
                     Hyuncheol Park and
                     Wonsuk Lee},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2015},
        volume    = {1},
        number    = {2},
        pages     = {19--27},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244959},
        urn       = {urn:nbn:de:101:1-201704244959},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper suggests a method to measure the physical distance between an IoT device (a Thing) and a mobile device (also a Thing) using BLE (Bluetooth Low-Energy profile) interfaces with smaller distance errors. BLE is a well-known technology for the low-power connectivity and suitable for IoT devices as well as for the proximity with the range of several meters. Apple has already adopted the technique and enhanced it to provide subdivided proximity range levels. However, as it is also a variation of RSS-based distance estimation, Apple's iBeacon could only provide immediate, near or far status but not a real and accurate distance. To provide more accurate distance using BLE, this paper introduces additional self-correcting beacon to calibrate the reference distance and mitigate errors from environmental factors. By adopting self-correcting beacon for measuring the distance, the average distance error shows less than 10\% within the range of 1.5 meters. Some considerations are presented to extend the range to be able to get more accurate distances.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n03_Ziehn,
        title     = {IoT-PMA: Patient Health Monitoring in Medical IoT Ecosystems},
        author    = {Ariane Ziehn and
                     Christian Mandel and
                     Kathrin Stich and
                     Rolf Dembinski and
                     Karin Hochbaum and
                     Steffen Zeuch and
                     Volker Markl},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {20--31},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515501651013147},
        urn       = {urn:nbn:de:101:1-2022090515501651013147},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The emergence of the Internet of Things (IoT) and the increasing number of cheap medical devices enable geographically distributed healthcare ecosystems of various stakeholders. Such ecosystems contain different application scenarios, e.g., (mobile) patient monitoring using various vital parameters such as heart rate signals. The increasing number of data producers and the transfer of data between medical stakeholders introduce several challenges to the data processing environment, e.g., heterogeneity and distribution of computing and data, lowlatency processing, as well as data security and privacy. Current approaches propose cloud-based solutions introducing latency bottlenecks and high risks for companies dealing with sensitive patient data. In this paper, we address the challenges of medical IoT applications by proposing an end-to-end patient monitoring application that includes NebulaStream as the data processing system, an easy-to-use UI that provides ad-hoc views on the available vital parameters, and the integration of ML models to enable predictions on the patients' health state. Using our end-to-end solution, we implement a real-world patient monitoring scenario for hemodynamic and pulmonary decompensations, which are dynamic and life-threatening deteriorations of lung and cardiovascular functions. Our application provides ad-hoc views of the vital parameters and derived decompensation severity scores with continuous updates on the latest data readings to support timely decision-making by physicians. Furthermore, we envision the infrastructure of an IoT ecosystem for a multi-hospital scenario that enables geo-distributed medical participants to contribute data to the application in a secure, private, and timely manner.}
    }

BibTex:

    @Article{OJBD_2022v6i1n02_Laue,
        title     = {A SIEM Architecture for Advanced Anomaly Detection},
        author    = {Tim Laue and
                     Timo Klecker and
                     Carsten Kleiner and
                     Kai-Oliver Detken},
        journal   = {Open Journal of Big Data (OJBD)},
        issn      = {2365-029X},
        year      = {2022},
        volume    = {6},
        number    = {1},
        pages     = {26--42},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022070319330522943055},
        urn       = {urn:nbn:de:101:1-2022070319330522943055},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Dramatic increases in the number of cyber security attacks and breaches toward businesses and organizations have been experienced in recent years. The negative impacts of these breaches not only cause the stealing and compromising of sensitive information, malfunctioning of network devices, disruption of everyday operations, financial damage to the attacked business or organization itself, but also may navigate to peer businesses/organizations in the same industry. Therefore, prevention and early detection of these attacks play a significant role in the continuity of operations in IT-dependent organizations. At the same time detection of various types of attacks has become extremely difficult as attacks get more sophisticated, distributed and enabled by Artificial Intelligence (AI). Detection and handling of these attacks require sophisticated intrusion detection systems which run on powerful hardware and are administered by highly experienced security staff. Yet, these resources are costly to employ, especially for small and medium-sized enterprises (SMEs). To address these issues, we developed an architecture -within the GLACIER project- that can be realized as an in-house operated Security Information Event Management (SIEM) system for SMEs. It is affordable for SMEs as it is solely based on free and open-source components and thus does not require any licensing fees. Moreover, it is a Self-Contained System (SCS) and does not require too much management effort. It requires short configuration and learning phases after which it can be self-contained as long as the monitored infrastructure is stable (apart from a reaction to the generated alerts which may be outsourced to a service provider in SMEs, if necessary). Another main benefit of this system is to supply data to advanced detection algorithms, such as multidimensional analysis algorithms, in addition to traditional SIEMspecific tasks like data collection, normalization, enrichment, and storage. It supports the application of novel methods to detect security-related anomalies. The most distinct feature of this system that differentiates it from similar solutions in the market is its user feedback capability. Detected anomalies are displayed in a Graphical User Interface (GUI) to the security staff who are allowed to give feedback for anomalies. Subsequently, this feedback is utilized to fine-tune the anomaly detection algorithm. In addition, this GUI also provides access to network actors for quick incident responses. The system in general is suitable for both Information Technology (IT) and Operational Technology (OT) environments, while the detection algorithm must be specifically trained for each of these environments individually.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n06_Cimmino,
        title     = {WoTHive: Enabling Syntactic and Semantic Discovery in the Web of Things},
        author    = {Andrea Cimmino and
                      Ra\'{u}l Garc\'{i}a-Castro},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {54--65},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515503251402854},
        urn       = {urn:nbn:de:101:1-2022090515503251402854},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In the last decade the Internet of Things (IoT) has experienced a significant growth and its adoption has become ubiquitous in either business and private life. As a result, several initiatives have emerged for addressing specific challenges and provide a standard or a specification to address them; like CoRE, Web of Things (WoT), oneM2M, or OGC among others. One of these challenges revolves around the discovery procedures to find IoT devices within IoT infrastructures and whether the discovery performed is semantic or syntactic. This article focusses on the WoT initiative and reports the benefits that Semantic Web technologies bring to discovery in WoT. In particular, one of the implementations for the WoT discovery is presented, which is named WoTHive and provides syntactic and semantic discovery capabilities. WoTHive is the only candidate implementation that addresses at the same time the syntactic and semantic functionalities specified in the discovery described by WoT. Several experiments have been carried out to test WoTHive; these advocate that the implementation is technically sound for CRUD operations and that its semantic discovery outperforms the syntactic one implemented. Furthermore, an experiment has been carried out to compare whether syntactic discovery is faster than semantic discovery using the Link Smart implementation for syntactic discovery and WoTHive for semantic.}
    }

BibTex:

    @Article{OJCC_2023v8i1n01_Baun,
        title     = {Closing the Gap between Web Applications and Desktop Applications by Designing a Novel Desktop-as-a-Service (DaaS) with Seamless Support for Desktop Applications},
        author    = {Christian Baun and
                     Johannes Bouche},
        journal   = {Open Journal of Cloud Computing (OJCC)},
        issn      = {2199-1987},
        year      = {2023},
        volume    = {8},
        number    = {1},
        pages     = {1--19},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2023111918330784257276},
        urn       = {urn:nbn:de:101:1-2023111918330784257276},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {An increasing transformation from locally deployed applications to remote web applications has occurred for about two decades. Nevertheless, abandoning established and essential Windows or Linux desktop applications is in many scenarios impossible. This paper describes and evaluates existing Desktop-as-a-Service solutions and the components required for developing a novel DaaS. Based on the conclusions and findings of this analysis, the paper describes a novel approach for a  Desktop-as-a-Service solution that enables, as a unique characteristic, the deployment of non-modified Linux and Windows applications. The interaction with these applications is done entirely through a browser which is unusual for remote interaction with Windows or Linux desktop applications but brings many benefits from the user's point of view because installing any additional client software or local virtualization solution becomes unnecessary. A solution, as described in this paper, has many advantages and offers excellent potential for use in academia, research, industry, and administration.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n08_Paasche,
        title     = {Generating SPARQL-Constraints for Consistency Checking in Industry 4.0 Scenarios},
        author    = {Simon Paasche and
                     Sven Groppe},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {80--90},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515504409042979},
        urn       = {urn:nbn:de:101:1-2022090515504409042979},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {A smart manufacturing line consists of multiple connected machines. These machines communicate with each other over a network, to solve a common task. Such a scenario can be located in the Internet of Things (IoT) area. An individual machine can be perceived as an IoT device. Due to machine to machine communication, a huge amount of data is generated during manufacturing. This emerging data flow is an essential part of today's industry, as analyzing data helps improving processes and thus, product quality. To adequately make use of the collected data, we require a high level of data quality. In our work, we address the issue of inconsistent data in smart manufacturing and present an approach to automatically generate SPARQL queries for validation.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n04_Yuan,
        title     = {3D Histogram Based Anomaly Detection for Categorical Sensor Data in Internet of Things},
        author    = {Peng Yuan and
                     Lu-An Tang and
                     Haifeng Chen and
                     Moto Sato and
                     Kevin Woodward},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {32--43},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515502212539652},
        urn       = {urn:nbn:de:101:1-2022090515502212539652},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The applications of Internet-of-things (IoT) deploy massive number of sensors to monitor the system and environment. Anomaly detection on streaming sensor data is an important task for IoT maintenance and operation. In real IoT applications, many sensors report categorical values rather than numerical readings. Unfortunately, most existing anomaly detection methods are designed only for numerical sensor data. They cannot be used to monitor the categorical sensor data. In this study, we design and develop a 3D Histogram based Categorical Anomaly Detection (HCAD) solution to monitor categorical sensor data in IoT. HCAD constructs the histogram model by three dimensions: categorical value, event duration, and frequency. The histogram models are used to profile normal working states of IoT devices. HCAD automatically determines the range of normal data and anomaly threshold. It only requires very limit parameter setting and can be applied to a wide variety of different IoT devices. We implement HCAD and integrate it into an online monitoring system. We test the proposed solution on real IoT datasets such as telemetry data from satellite sensors, air quality data from chemical sensors, and transportation data from traffic sensors. The results of extensive experiments show that HCAD achieves higher detecting accuracy and efficiency than state-of-the-art methods.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n05_Misev,
        title     = {Space Cubes: Satellite On-Board Processing of Datacube Queries},
        author    = {Dimitar Misev and
                     Peter Baumann},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {44--53},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515502699550987},
        urn       = {urn:nbn:de:101:1-2022090515502699550987},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Datacubes form an accepted cornerstone for analysis- and visualization-ready spatio-temporal data offerings. The increase in user friendliness is achieved by abstracting away from the zillions of files in provider-specific organization. Datacube query languages additionally establish actionable datacubes, enabling users to ask "any query, any time" with zero coding. However, typically datacube deployments are aiming at large scale, data center environments accommodating Big Data and massive parallel processing capabilities for achieving decent performance. In this contribution, we conversely report about a downscaling experiment. In the ORBiDANSE project a datacube engine, rasdaman, has been ported to a cubesat, ESA OPS-SAT, and is operational in space. Effectively, the satellite thereby becomes a datacube service offering the standards-based query capabilities of the OGC Web Coverage Processing (WCPS) geo datacube analytics language. We believe this will pave the way for on-board ad-hoc processing and filtering on Big EO Data, thereby unleashing them to a larger audience and in substantially shorter time.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n01e_VLIOT2022,
        title     = {Contributions to the 6th Workshop on Very Large Internet of Things (VLIoT 2022)},
        author    = {Sven Groppe and
                     Sanju Tiwari and
                     Shui Yu},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {1--6},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515500516853039},
        urn       = {urn:nbn:de:101:1-2022090515500516853039},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The concept of the Internet of Things, where small things become available in the Internet and get connected with each other for the purpose of advanced applications, raises many new open challenges to research. This even increases when considering large-scale Internet-of-Things (IoT) configurations, which is the focus of our Very Large Internet of Things (VLIoT) workshop. We recognize that the IoT research community is very active and the industry continuously develops novel IoT applications for daily live. Hence we received many high-quality submissions, from which we accepted 7 to be introduced in this editorial.}
    }

BibTex:

    @Article{OJCC_2015v2i1n03_Skala,
        title     = {Scalable Distributed Computing Hierarchy: Cloud, Fog and Dew Computing},
        author    = {Karolj Skala and
                     Davor Davidovic and
                     Enis Afgan and
                     Ivan Sovic and
                     Zorislav Sojat},
        journal   = {Open Journal of Cloud Computing (OJCC)},
        issn      = {2199-1987},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {16--24},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194519},
        urn       = {urn:nbn:de:101:1-201705194519},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The paper considers the conceptual approach for organization of the vertical hierarchical links between the scalable distributed computing paradigms: Cloud Computing, Fog Computing and Dew Computing. In this paper, the Dew Computing is described and recognized as a new structural layer in the existing distributed computing hierarchy. In the existing computing hierarchy, the Dew computing is positioned as the ground level for the Cloud and Fog computing paradigms. Vertical, complementary, hierarchical division from Cloud to Dew Computing satisfies the needs of high- and low-end computing demands in everyday life and work. These new computing paradigms lower the cost and improve the performance, particularly for concepts and applications such as the Internet of Things (IoT) and the Internet of Everything (IoE). In addition, the Dew computing paradigm will require new programming models that will efficiently reduce the complexity and improve the productivity and usability of scalable distributed computing, following the principles of High-Productivity computing.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n07_Khaled,
        title     = {IoT Hub as a Service (HaaS): Data-Oriented Environment for Interactive Smart Spaces},
        author    = {Ahmed E. Khaled and
                     Rousol Al Goboori},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {66--79},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515503839588667},
        urn       = {urn:nbn:de:101:1-2022090515503839588667},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Smart devices around us produce a considerable volume of data and interact in a wide range of scenarios that guide the evolution of the Internet of Things (IoT). IoT adds informative and interactive aspects to our living spaces, converting them into smart spaces. However, the development of applications is challenged by the fragmented nature due to the vast number of different IoT things, the format of reported information, communication standards, and the techniques used to design applications. This paper introduces IoT Hub as a Service (HaaS), a data-oriented framework to enable communication interoperability between the ecosystem's entities. The framework abstracts things' information, reported data items, and developers' applications into programmable objects referred to as Cards. Cards represent specific entities and interactions of focus with meta-data. The framework then indexes cards' meta-data to enable interoperability, data management, and application development. The framework allows users to create virtual smart spaces (VSS) to define cards' accessibility and visibility. Within VSS, users can identify accessible data items, things to communicate, and authorized applications. The framework, in this paper, defines four types of Cards to represent: participating IoT things, data items, VSS, and applications. The proposed framework enables the development of synchronous and asynchronous applications. The framework dynamically creates, updates, and links the cards throughout the life-cycle of the different entities. We present the details of the proposed framework and show how our framework is advantageous and applicable.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n02_Leon,
        title     = {Development and Evaluation of a Publish/Subscribe IoT Data Sharing Model with LoRaWAN},
        author    = {Juan Leon and
                     Yacoub Hanna and
                     Kemal Akkaya},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {7--19},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515501014226277},
        urn       = {urn:nbn:de:101:1-2022090515501014226277},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Publish/subscribe architectures are becoming very common for many IoT environments such as power grid, manufacturing and factory automation. In these architectures, many different communication standards and middleware can be supported to ensure interoperability. One of the widely used publish/subscribe protocol is MQTT where a broker acts among publishers and subscribers to relay data on certain topics. While MQTT can be easily setup on cloud environments to perform research experiments, its large-scale and quick deployment for IoT environments with a widely used wireless MAC layer protocol such as LoRaWAN has not been thoroughly tested. Therefore, in this paper we develop and present a simulation framework in NS-3 to offer MQTT-based on publish/subscribe architecture that can also support LoRaWAN communication standard. To this end, we utilize NS-3's LoRaWAN library and integrate it with a broker that connects to other types of publishers/subscribers. We enable unicast capability from the broker to LoRaWAN end-devices while supporting multiple topics at the broker. We tested several scenarios under this IoT architecture to demonstrate its feasibility while assessing the performance at scale.}
    }

BibTex:

    @Article{OJDB-v1i1n03_Elbushra,
        title     = {Eventual Consistent Databases: State of the Art},
        author    = {Mawahib Musa Elbushra and
                     Jan Lindstr{\"o}m},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {26--41},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194582},
        urn       = {urn:nbn:de:101:1-201705194582},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {One of the challenges of cloud programming is to achieve the right balance between the availability and consistency in a distributed database. Cloud computing environments, particularly cloud databases, are rapidly increasing in importance, acceptance and usage in major applications, which need the partition-tolerance and availability for scalability purposes, but sacrifice the consistency side (CAP theorem). In these environments, the data accessed by users is stored in a highly available storage system, thus the use of paradigms such as eventual consistency became more widespread. In this paper, we review the state-of-the-art database systems using eventual consistency from both industry and research. Based on this review, we discuss the advantages and disadvantages of eventual consistency, and identify the future research challenges on the databases using eventual consistency.}
    }

BibTex:

    @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.}
    }

BibTex:

    @Article{OJDB_2015v2i1n02_Elbushra,
        title     = {Causal Consistent Databases},
        author    = {Mawahib Musa Elbushra and
                     Jan Lindstr{\"o}m},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {17--35},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194619},
        urn       = {urn:nbn:de:101:1-201705194619},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Many consistency criteria have been considered in databases and the causal consistency is one of them. The causal consistency model has gained much attention in recent years because it provides ordering of relative operations. The causal consistency requires that all writes, which are potentially causally related, must be seen in the same order by all processes. The causal consistency is a weaker criteria than the sequential consistency, because there exists an execution, which is causally consistent but not sequentially consistent, however all executions satisfying the sequential consistency are also causally consistent. Furthermore, the causal consistency supports non-blocking operations; i.e. processes may complete read or write operations without waiting for global computation. Therefore, the causal consistency overcomes the primary limit of stronger criteria: communication latency. Additionally, several application semantics are precisely captured by the causal consistency, e.g. collaborative tools. In this paper, we review the state-of-the-art of causal consistent databases, discuss the features, functionalities and applications of the causal consistency model, and systematically compare it with other consistency models. We also discuss the implementation of causal consistency databases and identify limitations of the causal consistency model.}
    }

BibTex:

    @Article{OJSW-v1i2n01_Li,
        title     = {Developing Knowledge Models of Social Media: A Case Study on LinkedIn},
        author    = {Jinwu Li and
                     Vincent Wade and
                     Melike Sah},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {1--24},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194841},
        urn       = {urn:nbn:de:101:1-201705194841},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {User Generated Content (UGC) exchanged via large Social Network is considered a very important knowledge source about all aspects of the social engagements (e.g. interests, events, personal information, personal preferences, social experience, skills etc.). However this data is inherently unstructured or semi-structured. In this paper, we describe the results of a case study on LinkedIn Ireland public profiles. The study investigated how the available knowledge could be harvested from LinkedIn in a novel way by developing and applying a reusable knowledge model using linked open data vocabularies and semantic web. In addition, the paper discusses the crawling and data normalisation strategies that we developed, so that high quality metadata could be extracted from the LinkedIn public profiles. Apart from the search engine in LinkedIn.com itself, there are no well known publicly available endpoints that allow users to query knowledge concerning the interests of individuals on LinkedIn. In particular, we present a system that extracts and converts information from raw web pages of LinkedIn public profiles into a machine-readable, interoperable format using data mining and Semantic Web technologies. The outcomes of our research can be summarized as follows: (1) A reusable knowledge model which can represent LinkedIn public users and company profiles using linked data vocabularies and structured data, (2) a public SPARQL endpoint to access structured data about Irish industry and public profiles, (3) a scalable data crawling strategy and mashup based data normalisation approach. The proposed data mining and knowledge representation proposed in this paper are evaluated in four ways: (1) We evaluate metadata quality using automated techniques, such as data completeness and data linkage. (2) Data accuracy is evaluated via user studies. In particular, accuracy is evaluated by comparison of manually entered metadata fields and the metadata which was automatically extracted. (3) User perceived metadata quality is measured by asking users to rate the automatically extracted metadata in user studies. (4) Finally, the paper discusses how the extracted metadata suits for a user interface design. Overall, the evaluations show that the extracted metadata is of high quality and meets the requirements of a data visualisation user interface.}
    }

BibTex:

    @Article{OJIOT_2015v1i1n03_Rosa,
        title     = {The Potential of Printed Electronics and Personal Fabrication in Driving the Internet of Things},
        author    = {Paulo Rosa and
                     Ant\'{o}nio C\^{a}mara and
                     Cristina Gouveia},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2015},
        volume    = {1},
        number    = {1},
        pages     = {16--36},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244933},
        urn       = {urn:nbn:de:101:1-201704244933},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In the early nineties, Mark Weiser, a chief scientist at the Xerox Palo Alto Research Center (PARC), wrote a series of seminal papers that introduced the concept of Ubiquitous Computing. Within this vision, computers and others digital technologies are integrated seamlessly into everyday objects and activities, hidden from our senses whenever not used or needed. An important facet of this vision is the interconnectivity of the various physical devices, which creates an Internet of Things. With the advent of Printed Electronics, new ways to link the physical and digital worlds became available. Common printing technologies, such as screen, flexography, and inkjet printing, are now starting to be used not only to mass-produce extremely thin, flexible and cost effective electronic circuits, but also to introduce electronic functionality into objects where it was previously unavailable. In turn, the growing accessibility to Personal Fabrication tools is leading to the democratization of the creation of technology by enabling end-users to design and produce their own material goods according to their needs. This paper presents a survey of commonly used technologies and foreseen applications in the field of Printed Electronics and Personal Fabrication, with emphasis on the potential to drive the Internet of Things.}
    }

BibTex:

    @Article{OJSW-v1i2n02_Groppe,
        title     = {P-LUPOSDATE: Using Precomputed Bloom Filters to Speed Up SPARQL Processing in the Cloud},
        author    = {Sven Groppe and
                     Thomas Kiencke and
                     Stefan Werner and
                     Dennis Heinrich and
                     Marc Stelzner and
                     Le Gruenwald},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {25--55},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194858},
        urn       = {urn:nbn:de:101:1-201705194858},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Increasingly data on the Web is stored in the form of Semantic Web data. Because of today's information overload, it becomes very important to store and query these big datasets in a scalable way and hence in a distributed fashion. Cloud Computing offers such a distributed environment with dynamic reallocation of computing and storing resources based on needs. In this work we introduce a scalable distributed Semantic Web database in the Cloud. In order to reduce the number of (unnecessary) intermediate results early, we apply bloom filters. Instead of computing bloom filters, a time-consuming task during query processing as it has been done traditionally, we precompute the bloom filters as much as possible and store them in the indices besides the data. The experimental results with data sets up to 1 billion triples show that our approach speeds up query processing significantly and sometimes even reduces the processing time to less than half.}
    }

BibTex:

    @Article{OJWT_2014v1i2n02_Kusserow,
        title     = {Getting Indexed by Bibliographic Databases in the Area of Computer Science},
        author    = {Arne Kusserow and
                     Sven Groppe},
        journal   = {Open Journal of Web Technologies (OJWT)},
        issn      = {2199-188X},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {10--27},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705291343},
        urn       = {urn:nbn:de:101:1-201705291343},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Every author and publisher is interested in adding their publications to the widely used bibliographic databases freely accessible in the world wide web: This ensures the visibility of their publications and hence of the published research. However, the inclusion requirements of publications in the bibliographic databases are heterogeneous even on the technical side. This survey paper aims in shedding light on the various data formats, protocols and technical requirements of getting indexed by widely used bibliographic databases in the area of computer science and provides hints for maximal database inclusion. Furthermore, we point out the possibilities to utilize the data of bibliographic databases, and describes some personal and institutional research repository systems with special regard to the support of inclusion in bibliographic databases.}
    }

BibTex:

    @Article{OJBD_2015v1i2n04_UjjalMarjit,
        title     = {Data Transfers in Hadoop: A Comparative Study},
        author    = {Ujjal Marjit and
                     Kumar Sharma and
                     Puspendu Mandal},
        journal   = {Open Journal of Big Data (OJBD)},
        issn      = {2365-029X},
        year      = {2015},
        volume    = {1},
        number    = {2},
        pages     = {34--46},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194373},
        urn       = {urn:nbn:de:101:1-201705194373},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Hadoop is an open source framework for processing large amounts of data in distributed computing environment. It plays an important role in processing and analyzing the Big Data. This framework is used for storing data on large clusters of commodity hardware. Data input and output to and from Hadoop is an indispensable action for any data processing job. At present, many tools have been evolved for importing and exporting Data in Hadoop. In this article, some commonly used tools for importing and exporting data have been emphasized. Moreover, a state-of-the-art comparative study among the various tools has been made. With this study, it has been decided that where to use one tool over the other with emphasis on the data transfer to and from Hadoop system. This article also discusses about how Hadoop handles backup and disaster recovery along with some open research questions in terms of Big Data transfer when dealing with cloud-based services.}
    }

BibTex:

    @Article{OJIS-v1i1n02_Kessler,
        title     = {Pattern-sensitive Time-series Anonymization and its Application to Energy-Consumption Data},
        author    = {Stephan Kessler and
                     Erik Buchmann and
                     Thorben Burghardt and
                     Klemens B{\"o}hm},
        journal   = {Open Journal of Information Systems (OJIS)},
        issn      = {2198-9281},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {3--22},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194696},
        urn       = {urn:nbn:de:101:1-201705194696},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Time series anonymization is an important problem. One prominent example of time series are energy consumption records, which might reveal details of the daily routine of a household. Existing privacy approaches for time series, e.g., from the field of trajectory anonymization, assume that every single value of a time series contains sensitive information and reduce the data quality very much. In contrast, we consider time series where it is combinations of tuples that represent personal information. We propose (n; l; k)-anonymity, geared to anonymization of time-series data with minimal information loss, assuming that an adversary may learn a few data points. We propose several heuristics to obtain (n; l; k)-anonymity, and we evaluate our approach both with synthetic and real data. Our experiments confirm that it is sufficient to modify time series only moderately in order to fulfill meaningful privacy requirements.}
    }

BibTex:

    @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.	}
    }

BibTex:

    @Article{OJDB_2015v2i1n03_Groppe,
        title     = {PatTrieSort - External String Sorting based on Patricia Tries},
        author    = {Sven Groppe and
                     Dennis Heinrich and
                     Stefan Werner and
                     Christopher Blochwitz and
                     Thilo Pionteck},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {36--50},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194627},
        urn       = {urn:nbn:de:101:1-201705194627},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {External merge sort belongs to the most efficient and widely used algorithms to sort big data: As much data as fits inside is sorted in main memory and afterwards swapped to external storage as so called initial run. After sorting all the data in this way block-wise, the initial runs are merged in a merging phase in order to retrieve the final sorted run containing the completely sorted original data. Patricia tries are one of the most space-efficient ways to store strings especially those with common prefixes. Hence, we propose to use patricia tries for initial run generation in an external merge sort variant, such that initial runs can become large compared to traditional external merge sort using the same main memory size. Furthermore, we store the initial runs as patricia tries instead of lists of sorted strings. As we will show in this paper, patricia tries can be efficiently merged having a superior performance in comparison to merging runs of sorted strings. We complete our discussion with a complexity analysis as well as a comprehensive performance evaluation, where our new approach outperforms traditional external merge sort by a factor of 4 for sorting over 4 billion strings of real world data.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n05_Ruta,
        title     = {Semantic Blockchain to Improve Scalability in the Internet of Things},
        author    = {Michele Ruta and
                     Floriano Scioscia and
                     Saverio Ieva and
                     Giovanna Capurso and
                     Eugenio Di Sciascio},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {46--61},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613488},
        urn       = {urn:nbn:de:101:1-2017080613488},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Generally scarce computational and memory resource availability is a well known problem for the IoT, whose intrinsic volatility makes complex applications unfeasible. Noteworthy efforts in overcoming unpredictability (particularly in case of large dimensions) are the ones integrating Knowledge Representation technologies to build the so-called Semantic Web of Things (SWoT). In spite of allowed advanced discovery features, transactions in the SWoT still suffer from not viable trust management strategies. Given its intrinsic characteristics, blockchain technology appears as interesting from this perspective: a semantic resource/service discovery layer built upon a basic blockchain infrastructure gains a consensus validation. This paper proposes a novel Service-Oriented Architecture (SOA) based on a semantic blockchain for registration, discovery, selection and payment. Such operations are implemented as smart contracts, allowing distributed execution and trust. Reported experiments early assess the sustainability of the proposal.}
    }

BibTex:

    @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.}
    }

BibTex:

    @Article{OJCC-v1i2n01_Groppe,
        title     = {A Self-Optimizing Cloud Computing System for Distributed Storage and Processing of Semantic Web Data},
        author    = {Sven Groppe and
                     Johannes Blume and
                     Dennis Heinrich and
                     Stefan Werner},
        journal   = {Open Journal of Cloud Computing (OJCC)},
        issn      = {2199-1987},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {1--14},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194478},
        urn       = {urn:nbn:de:101:1-201705194478},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Clouds are dynamic networks of common, off-the-shell computers to build computation farms. The rapid growth of databases in the context of the semantic web requires efficient ways to store and process this data. Using cloud technology for storing and processing Semantic Web data is an obvious way to overcome difficulties in storing and processing the enormously large present and future datasets of the Semantic Web. This paper presents a new approach for storing Semantic Web data, such that operations for the evaluation of Semantic Web queries are more likely to be processed only on local data, instead of using costly distributed operations. An experimental evaluation demonstrates the performance improvements in comparison to a naive distribution of Semantic Web data.}
    }

BibTex:

    @Article{OJIS-2014v1i2n01_Stackelberg,
        title     = {Detecting Data-Flow Errors in BPMN 2.0},
        author    = {Silvia von Stackelberg and
                     Susanne Putze and
                     Jutta M{\"u}lle and
                     Klemens B{\"o}hm},
        journal   = {Open Journal of Information Systems (OJIS)},
        issn      = {2198-9281},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {1--19},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017052611934},
        urn       = {urn:nbn:de:101:1-2017052611934},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Data-flow errors in BPMN 2.0 process models, such as missing or unused data, lead to undesired process executions. In particular, since BPMN 2.0 with a standardized execution semantics allows specifying alternatives for data as well as optional data, identifying missing or unused data systematically is difficult. In this paper, we propose an approach for detecting data-flow errors in BPMN 2.0 process models. We formalize BPMN process models by mapping them to Petri Nets and unfolding the execution semantics regarding data. We define a set of anti-patterns representing data-flow errors of BPMN 2.0 process models. By employing the anti-patterns, our tool performs model checking for the unfolded Petri Nets. The evaluation shows that it detects all data-flow errors identified by hand, and so improves process quality.}
    }

BibTex:

    @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.}
    }

BibTex:

    @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.}
    }

BibTex:

    @Article{OJIOT_2015v1i2n02_Gaur,
        title     = {Evidential Sensor Data Fusion in a Smart City Environment},
        author    = {Aditya Gaur and
                     Bryan W. Scotney and
                     Gerard P. Parr and
                     Sally I. McClean},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2015},
        volume    = {1},
        number    = {2},
        pages     = {1--18},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244969},
        urn       = {urn:nbn:de:101:1-201704244969},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Wireless sensor networks have increasingly become contributors of very large amounts of data. The recent deployment of wireless sensor networks in Smart City infrastructures have led to very large amounts of data being generated each day across a variety of domains, with applications including environmental monitoring, healthcare monitoring and transport monitoring. The information generated through the wireless sensor nodes has made possible the visualization of a Smart City environment for better living. The Smart City offers intelligent infrastructure and cogitative environment for the elderly and other people living in the Smart society. Different types of sensors are present that help in monitoring inhabitants' behaviour and their interaction with real world objects. To take advantage of the increasing amounts of data, there is a need for new methods and techniques for effective data management and analysis, to generate information that can assist in managing the resources intelligently and dynamically. Through this research a Smart City ontology model is proposed, which addresses the fusion process related to uncertain sensor data using semantic web technologies and Dempster-Shafer uncertainty theory. Based on the information handling methods, such as Dempster-Shafer theory (DST), an equally weighted sum operator and maximization operation, a higher level of contextual information is inferred from the low-level sensor data fusion process. In addition, the proposed ontology model helps in learning new rules that can be used in defining new knowledge in the Smart City system.}
    }

BibTex:

    @Article{OJBD_2015v1i2n02_Neves,
        title     = {Big Data in the Cloud: A Survey},
        author    = {Pedro Caldeira Neves and
                     Jorge Bernardino},
        journal   = {Open Journal of Big Data (OJBD)},
        issn      = {2365-029X},
        year      = {2015},
        volume    = {1},
        number    = {2},
        pages     = {1--18},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194365},
        urn       = {urn:nbn:de:101:1-201705194365},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Big Data has become a hot topic across several business areas requiring the storage and processing of huge volumes of data. Cloud computing leverages Big Data by providing high storage and processing capabilities and enables corporations to consume resources in a pay-as-you-go model making clouds the optimal environment for storing and processing huge quantities of data. By using virtualized resources, Cloud can scale very easily, be highly available and provide massive storage capacity and processing power. This paper surveys existing databases models to store and process Big Data within a Cloud environment. Particularly, we detail the following traditional NoSQL databases: BigTable, Cassandra, DynamoDB, HBase, Hypertable, and MongoDB. The MapReduce framework and its developments Apache Spark, HaLoop, Twister, and other alternatives such as Apache Giraph, GraphLab, Pregel and MapD - a novel platform that uses GPU processing to accelerate Big Data processing - are also analyzed. Finally, we present two case studies that demonstrate the successful use of Big Data within Cloud environments and the challenges that must be addressed in the future.}
    }

BibTex:

    @Article{OJCC-v1i1n02_Puzio,
        title     = {Block-level De-duplication with Encrypted Data},
        author    = {Pasquale Puzio and
                     Refik Molva and
                     Melek {\"O}nen and
                     Sergio Loureiro},
        journal   = {Open Journal of Cloud Computing (OJCC)},
        issn      = {2199-1987},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {10--18},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194448},
        urn       = {urn:nbn:de:101:1-201705194448},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Deduplication is a storage saving technique which has been adopted by many cloud storage providers such as Dropbox. The simple principle of deduplication is that duplicate data uploaded by different users are stored only once. Unfortunately, deduplication is not compatible with encryption. As a scheme that allows deduplication of encrypted data segments, we propose ClouDedup, a secure and efficient storage service which guarantees blocklevel deduplication and data confidentiality at the same time. ClouDedup strengthens convergent encryption by employing a component that implements an additional encryption operation and an access control mechanism. We also propose to introduce an additional component which is in charge of providing a key management system for data blocks together with the actual deduplication operation. We show that the overhead introduced by these new components is minimal and does not impact the overall storage and computational costs.}
    }

BibTex:

    @Article{OJIOT_2015v1i1n02_Syarifah,
        title     = {Modelling the Integrated QoS for Wireless Sensor Networks with Heterogeneous Data Traffic},
        author    = {Syarifah Ezdiani and
                     Adnan Al-Anbuky},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2015},
        volume    = {1},
        number    = {1},
        pages     = {1--15},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244946},
        urn       = {urn:nbn:de:101:1-201704244946},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The future of Internet of Things (IoT) is envisaged to consist of a high amount of wireless resource-constrained devices connected to the Internet. Moreover, a lot of novel real-world services offered by IoT devices are realized by wireless sensor networks (WSNs). Integrating WSN to the Internet has therefore brought forward the requirements of an end-to-end quality of service (QoS) guarantee. In this paper, the QoS requirements for the WSN-Internet integration are investigated by first distinguishing the Internet QoS from the WSN QoS. Next, this study emphasizes on WSN applications that involve traffic with different levels of importance, thus the way realtime traffic and delay-tolerant traffic are handled to guarantee QoS in the network is studied. Additionally, an overview of the integration strategies is given, and the delay-tolerant network (DTN) gateway, being one of the desirable approaches for integrating WSNs to the Internet, is discussed. Next, the implementation of the service model is presented, by considering both traffic prioritization and service differentiation. Based on the simulation results in OPNET Modeler, it is observed that real-time traffic achieve low bound delay while delay-tolerant traffic experience a lower packet dropped, hence indicating that the needs of real-time and delay-tolerant traffic can be better met by treating both packet types differently. Furthermore, a vehicular network is used as an example case to describe the applicability of the framework in a real IoT application environment, followed by a discussion on the future work of this research.}
    }

BibTex:

    @Article{OJDB-2015v2i1n01_Buchmann,
        title     = {Deriving Bounds on the Size of Spatial Areas},
        author    = {Erik Buchmann and
                     Patrick Erik Bradley and
                     Klemens B{\"o}hm},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {1--16},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194566},
        urn       = {urn:nbn:de:101:1-201705194566},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Many application domains such as surveillance, environmental monitoring or sensor-data processing need upper and lower bounds on areas that are covered by a certain feature. For example, a smart-city infrastructure might need bounds on the size of an area polluted with fine-dust, to re-route combustion-engine traffic. Obtaining such bounds is challenging, because in almost any real-world application, information about the region of interest is incomplete, e.g., the database of sensor data contains only a limited number of samples. Existing approaches cannot provide upper and lower bounds or depend on restrictive assumptions, e.g., the area must be convex. Our approach in turn is based on the natural assumption that it is possible to specify a minimal diameter for the feature in question. Given this assumption, we formally derive bounds on the area size, and we provide algorithms that compute these bounds from a database of sensor data, based on geometrical considerations. We evaluate our algorithms both with a real-world case study and with synthetic data.}
    }

BibTex:

    @Article{OJDB-v1i2n01_Mortensen,
        title     = {Using Business Intelligence to Improve DBA Productivity},
        author    = {Eric A. Mortensen and
                     En Cheng},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {1--16},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194595},
        urn       = {urn:nbn:de:101:1-201705194595},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The amount of data collected and used by companies has grown rapidly in size over the last decade.  Business leaders are now using Business Intelligence (BI) systems to make effective business decisions against large amounts of data. The growth in the size of data has been a major challenge for Database Administrators (DBAs). The increase in the number and size of databases at the speed they have grown has made it difficult for DBA teams to provide the same level of service that the business requires they provide. The methods that DBAs have used in the last several decades can no longer be performed with the efficiency needed over all of the databases they administer. This paper presents the first BI system to improve DBA productivity and providing important data metrics for Information Technology (IT) managers. The BI system has been well received by Sherwin Williams Database Administrators.  It has i) enabled the DBA team to quickly determine which databases needed work by a DBA without manually logging into the system; ii) helped the DBA team and its management to easily answer other business users' questions without using DBAs' time to research the issue; and iii) helped the DBA team to provide the business data for unanticipated audit request.}
    }

BibTex:

    @Article{OJWT-v1i1n02_Belk,
        title     = {Integrating Human Factors and Semantic Mark-ups in Adaptive Interactive Systems},
        author    = {Marios Belk and
                     Panagiotis Germanakos and
                     Efi Papatheocharous and
                     Panayiotis Andreou and
                     George Samaras},
        journal   = {Open Journal of Web Technologies (OJWT)},
        issn      = {2199-188X},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {15--26},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017052611313},
        urn       = {urn:nbn:de:101:1-2017052611313},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper focuses on incorporating individual differences in cognitive processing and semantic mark-ups in the context of adaptive interactive systems. In particular, a semantic Web-based adaptation framework is proposed that enables Web content providers to enrich content and functionality of Web environments with semantic mark-ups. The Web content is created using a Web authoring tool and is further processed and reconstructed by an adaptation mechanism based on cognitive factors of users. Main aim of this work is to investigate the added value of personalising content and functionality of Web environments based on the unique cognitive characteristics of users. Accordingly, a user study has been conducted that entailed a psychometric-based survey for extracting the users' cognitive characteristics, combined with a real usage scenario of an existing commercial Web environment that was enriched with semantic mark-ups and personalised based on different adaptation effects. The paper provides interesting insights in the design and development of adaptive interactive systems based on cognitive factors and semantic mark-ups.}
    }

BibTex:

    @Article{OJSW-v1i1n02_Garcia,
        title     = {MapReduce-based Solutions for Scalable SPARQL Querying},
        author    = {Jos\'{e} M. Gim\'{e}nez-Garcia and
                     Javier D. Fern\'{a}ndez and
                     Miguel A. Mart\'{i}nez-Prieto},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {1--18},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194824},
        urn       = {urn:nbn:de:101:1-201705194824},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The use of RDF to expose semantic data on the Web has seen a dramatic increase over the last few years. Nowadays, RDF datasets are so big and rconnected that, in fact, classical mono-node solutions present significant scalability problems when trying to manage big semantic data. MapReduce, a standard framework for distributed processing of great quantities of data, is earning a place among the distributed solutions facing RDF scalability issues. In this article, we survey the most important works addressing RDF management and querying through diverse MapReduce approaches, with a focus on their main strategies, optimizations and results.}
    }

BibTex:

    @Article{OJDB_2019v6i1n03_Schiff,
        title     = {Ontology-Based Data Access to Big Data},
        author    = {Simon Schiff and
                     Ralf M{\"o}ller and
                     {\"O}zg{\"u}r L. {\"O}zcep},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2019},
        volume    = {6},
        number    = {1},
        pages     = {21--32},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018122318334350985847},
        urn       = {urn:nbn:de:101:1-2018122318334350985847},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Recent approaches to ontology-based data access (OBDA) have extended the focus from relational database systems to other types of backends such as cluster frameworks in order to cope with the four Vs associated with big data: volume, veracity, variety and velocity (stream processing). The abstraction that an ontology provides is a benefit from the enduser point of view, but it represents a challenge for developers because high-level queries must be transformed into queries executable on the backend level. In this paper, we discuss and evaluate an OBDA system that uses STARQL (Streaming and Temporal ontology Access with a Reasoning-based Query Language), as a high-level query language to access data stored in a SPARK cluster framework. The development of the STARQL-SPARK engine show that there is a need to provide a homogeneous interface to access both static and temporal as well as streaming data because cluster frameworks usually lack such an interface. The experimental evaluation shows that building a scalable OBDA system that runs with SPARK is more than plug-and-play as one needs to know quite well the data formats and the data organisation in the cluster framework.}
    }

BibTex:

    @Article{OJWT-v1i1n01_Furini,
        title     = {SIWeb: understanding the Interests of the Society through Web data Analysis},
        author    = {Marco Furini and
                     Simone Montangero},
        journal   = {Open Journal of Web Technologies (OJWT)},
        issn      = {2199-188X},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {1--14},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705291334},
        urn       = {urn:nbn:de:101:1-201705291334},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The high availability of user-generated contents in the Web scenario represents a tremendous asset for understanding various social phenomena. Methods and commercial products that exploit the widespread use of the Web as a way of conveying personal opinions have been proposed, but a critical thinking is that these approaches may produce a partial, or distorted, understanding of the society, because most of them focus on definite scenarios, use specific platforms, base their analysis on the sole magnitude of data, or treat the different Web resources with the same importance. In this paper, we present SIWeb (Social Interests through Web Analysis), a novel mechanism designed to measure the interest the society has on a topic (e.g., a real world phenomenon, an event, a person, a thing). SIWeb is general purpose (it can be applied to any decision making process), cross platforms (it uses the entire Webspace, from social media to websites, from tags to reviews), and time effective (it measures the time correlatio between the Web resources). It uses fractal analysis to detect the temporal relations behind all the Web resources (e.g., Web pages, RSS, newsgroups, etc.) that talk about a topic and combines this number with the temporal relations to give an insight of the the interest the society has about a topic. The evaluation of the proposal shows that SIWeb might be helpful in decision making processes as it reflects the interests the society has on a specific topic.}
    }

BibTex:

    @Article{OJSW_2015v2i1n04_Groppe,
        title     = {Distributed Join Approaches for W3C-Conform SPARQL Endpoints},
        author    = {Sven Groppe and
                     Dennis Heinrich and
                     Stefan Werner},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {30--52},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194910},
        urn       = {urn:nbn:de:101:1-201705194910},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Currently many SPARQL endpoints are freely available and accessible without any costs to users: Everyone can submit SPARQL queries to SPARQL endpoints via a standardized protocol, where the queries are processed on the datasets of the SPARQL endpoints and the query results are sent back to the user in a standardized format. As these distributed execution environments for semantic big data (as intersection of semantic data and big data) are freely accessible, the Semantic Web is an ideal playground for big data research. However, when utilizing these distributed execution environments, questions about the performance arise. Especially when several datasets (locally and those residing in SPARQL endpoints) need to be combined, distributed joins need to be computed. In this work we give an overview of the various possibilities of distributed join processing in SPARQL endpoints, which follow the SPARQL specification and hence are "W3C conform". We also introduce new distributed join approaches as variants of the Bitvector-Join and combination of the Semi- and Bitvector-Join. Finally we compare all the existing and newly proposed distributed join approaches for W3C conform SPARQL endpoints in an extensive experimental evaluation.}
    }

BibTex:

    @Article{OJIS-v1i1n03_Iivari,
        title     = {Perceived Sociability of Use and Individual Use of Social Networking Sites - A Field Study of Facebook Use in the Arctic},
        author    = {Juhani Iivari},
        journal   = {Open Journal of Information Systems (OJIS)},
        issn      = {2198-9281},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {23--53},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194708},
        urn       = {urn:nbn:de:101:1-201705194708},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper investigates determinants of individual use of social network sites (SNSs). It introduces a new construct, Perceived Sociability of Use (PSOU), to explain the use of such computer mediated communication applications. Based on a field study of 113 Facebook users it shows that PSOU in the sense of maintaining social contacts is a significant predictor of Perceived Benefits (PB), Perceived Enjoyment (PE), attitude toward use and intention to use. Inspired by Benbasat and Barki, this paper also attempts to answer questions "what makes the system useful", "what makes the system enjoyable to use" and "what makes the system sociable to use". As a consequence it pays special focus on systems characteristics of IT applications as potential predictors of PSOU, PB and PE, introducing seven such designable qualities (user-to-user interactivity, user identifiability, system quality, information quality, usability, user-to-system interactivity, and aesthetics). The results indicate that especially satisfaction with user-to-user interactivity is a significant determinant of PSOU, and that satisfactions with six of these seven designable qualities have significant paths in the proposed nomological network.}
    }

BibTex:

    @Article{OJCC_2015v2i1n02_Hamid,
        title     = {An Analytical Model of Multi-Core Multi-Cluster Architecture (MCMCA)},
        author    = {Norhazlina Hamid and
                     Robert John Walters and
                     Gary B. Wills},
        journal   = {Open Journal of Cloud Computing (OJCC)},
        issn      = {2199-1987},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {4--15},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194487},
        urn       = {urn:nbn:de:101:1-201705194487},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Multi-core clusters have emerged as an important contribution in computing technology for provisioning additional processing power in high performance computing and communications. Multi-core architectures are proposed for their capability to provide higher performance without increasing heat and power usage, which is the main concern in a single-core processor. This paper introduces analytical models of a new architecture for large-scale multi-core clusters to improve the communication performance within the interconnection network. The new architecture will be based on a multi - cluster architecture containing clusters of multi-core processors.}
    }

BibTex:

    @Article{OJCC_2018v5i1n01_Akinrolabu,
        title     = {Cyber Supply Chain Risks in Cloud Computing - Bridging the Risk Assessment Gap},
        author    = {Olusola Akinrolabu and
                     Steve New and
                     Andrew Martin},
        journal   = {Open Journal of Cloud Computing (OJCC)},
        issn      = {2199-1987},
        year      = {2018},
        volume    = {5},
        number    = {1},
        pages     = {1--19},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201712245432},
        urn       = {urn:nbn:de:101:1-201712245432},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Cloud computing represents a significant paradigm shift in the delivery of information technology (IT) services. The rapid growth of the cloud and the increasing security concerns associated with the delivery of cloud services has led many researchers to study cloud risks and risk assessments. Some of these studies highlight the inability of current risk assessments to cope with the dynamic nature of the cloud, a gap we believe is as a result of the lack of consideration for the inherent risk of the supply chain. This paper, therefore, describes the cloud supply chain and investigates the effect of supply chain transparency in conducting a comprehensive risk assessment. We conducted an industry survey to gauge stakeholder awareness of supply chain risks, seeking to find out the risk assessment methods commonly used, factors that hindered a comprehensive evaluation and how the current state-of-the-art can be improved. The analysis of the survey dataset showed the lack of flexibility of the popular qualitative assessment methods in coping with the risks associated with the dynamic supply chain of cloud services, typically made up of an average of eight suppliers. To address these gaps, we propose a Cloud Supply Chain Cyber Risk Assessment (CSCCRA) model, a quantitative risk assessment model which is supported by decision support analysis and supply chain mapping in the identification, analysis and evaluation of cloud risks.}
    }

BibTex:

    @Article{OJIS_2015v2i1n01_Malaga,
        title     = {Using Nuisance Telephone Denial of Service to Combat Online Sex Trafficking},
        author    = {Ross A. Malaga},
        journal   = {Open Journal of Information Systems (OJIS)},
        issn      = {2198-9281},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {1--8},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194736},
        urn       = {urn:nbn:de:101:1-201705194736},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Over the past few years, sex trafficking has been linked to online classified ads sites such as Craigslist.com and Backpage.com. However, to date technology-based solutions have not been used to attack classified ad sites or the advertisers. This paper proposes and tests a new approach to combating online sex trafficking promulgated via online classified ad sites - nuisance telephone denial of service (TDoS) attacks on the advertisers. The method of attack is described and implications are discussed.}
    }

BibTex:

    @Article{OJBD_2015v1i1n02_Teli,
        title     = {An Efficient Approach for Cost Optimization of the Movement of Big Data},
        author    = {Prasad Teli and
                     Manoj V. Thomas and
                     K. Chandrasekaran},
        journal   = {Open Journal of Big Data (OJBD)},
        issn      = {2365-029X},
        year      = {2015},
        volume    = {1},
        number    = {1},
        pages     = {4--15},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194335},
        urn       = {urn:nbn:de:101:1-201705194335},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {With the emergence of cloud computing, Big Data has caught the attention of many researchers in the area of cloud computing. As the Volume, Velocity and Variety (3 Vs) of big data are growing exponentially, dealing with them is a big challenge, especially in the cloud environment. Looking at the current trend of the IT sector, cloud computing is mainly used by the service providers to host their applications. A lot of research has been done to improve the network utilization of WAN (Wide Area Network) and it has achieved considerable success over the traditional LAN (Local Area Network) techniques. While dealing with this issue, the major questions of data movement such as from where to where this big data will be moved and also how the data will be moved, have been overlooked. As various applications generating the big data are hosted in geographically distributed data centers, they individually collect large volume of data in the form of application data as well as the logs. This paper mainly focuses on the challenge of moving big data from one data center to other. We provide an efficient algorithm for the optimization of cost in the movement of the big data from one data center to another for offline environment. This approach uses the graph model for data centers in the cloud and results show that the adopted mechanism provides a better solution to minimize the cost for data movement.}
    }

BibTex:

    @Article{OJBD_2015v1i2n03_YuehzeLi,
        title     = {Statistical Machine Learning in Brain State Classification using EEG Data},
        author    = {Yuezhe Li and
                     Yuchou Chang and
                     Hong Lin},
        journal   = {Open Journal of Big Data (OJBD)},
        issn      = {2365-029X},
        year      = {2015},
        volume    = {1},
        number    = {2},
        pages     = {19--33},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194354},
        urn       = {urn:nbn:de:101:1-201705194354},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In this article, we discuss how to use a variety of machine learning methods, e.g. tree bagging, random forest, boost, support vector machine, and Gaussian mixture model, for building classifiers for electroencephalogram (EEG) data, which is collected from different brain states on different subjects. Also, we discuss how training data size influences misclassification rate. Moreover, the number of subjects that contributes to the training data affects misclassification rate. Furthermore, we discuss how sample entropy contributes to building a classifier. Our results show that classification based on sample entropy give the smallest misclassification rate. Moreover, two data sets were collected from one channel and seven channels respectively. The classification results of each data set show that the more channels we use, the less misclassification we have. Our results show that it is promising to build a self-adaptive classification system by using EEG data to distinguish idle from active state.}
    }

BibTex:

    @Article{OJIS_2015v2i1n02_Cunha,
        title     = {IT Governance Practices for Electric Utilities: Insights from Brazil and Europe},
        author    = {Paulo Rupino da Cunha and
                     Luiz Mauricio Martins and
                     Ant\~{a}o Moura and
                     Ant\'{o}nio Dias de Figueiredo},
        journal   = {Open Journal of Information Systems (OJIS)},
        issn      = {2198-9281},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {9--28},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194743},
        urn       = {urn:nbn:de:101:1-201705194743},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {We propose a framework of 14 IT governance practices tailored for the electric utilities sector. They were selected and ranked as "essential", "important", or "good" by top executives and IT staff from two multi-billion dollar companies - one in Brazil and another in Europe - from a generic set of 83 collected in the literature and in the field. Our framework addresses a need of electric utilities for which specific guidance was lacking. We have also uncovered a significant impact of social issues in IT governance, whose depth seems to be missing in the current research. As a byproduct of our work, the larger generic framework from which we have departed and the tailoring method that we have proposed can be used to customize the generic framework to different industries.}
    }

BibTex:

    @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.}
    }