Towards a service-oriented e-infrastructure for multidisciplinary environmental research

Research e-infrastructures are considered to have generic and thematic parts. The generic part provids high-speed networks, grid (large-scale distributed computing) and database systems (digital repositories and data transfer systems) applicable to all research commnities irrespective of discipline. Thematic parts are specific deployments of e-infrastructures to support diverse virtual research communities. The needs of a virtual community of multidisciplinary envronmental researchers are yet to be investigated. We envisage and argue for an e-infrastructure that will enable environmental researchers to develop environmental models and software entirely out of existing components through loose coupling of diverse digital resources based on the service-oriented achitecture. We discuss four specific aspects for consideration for a future e-infrastructure: 1) provision of digital resources (data, models & tools) as web services, 2) dealing with stateless and non-transactional nature of web services using workflow management systems, 3) enabling web servce discovery, composition and orchestration through semantic registries, and 4) creating synergy with existing grid infrastructures

Modelling the Determinants of Organic Farming

Analysis of scientific literature lead to the conclusion that academic society, politicians and producers of agricultural products more and more realize the importance and significance of organic farming on the development of society through the prism of the sustainable development and understand that organic farming creates the preconditions for the solution of environmental, economic and social problems in agriculture. The analysis of the previous methodologies and results regarding the factors of organic farming has enabled the following conclusions to be drawn: • the quantitative researches based on the farmers’ opinions dominated. The opinion of consumers was used rarely, and the qualitative experimental researches were ever so seldom. It is likely, that the reason of such a situation was the said assumption that the decision to change the method of production was the prerogative of the farmer and his family; • already the initial period (until the seventies of the last century) of the studies on the factors of conventional farming has revealed that the respondents named many factors encouraging them to run the agricultural activity. This encouraged in later researches to classify the factors of organic farming by different characteristics. It should be noted that the conclusions of studies of the said initial period stressed the importance of the external factors such as the market of organic products, promotional policy, consumer opinion. In the results of slightly later studies the prominence was given to the personal characteristics of the farmers, and were stressed the elements of farming systems, the significance of their interaction and links with the external environment, i.e. it was an attempt to emphasize the significance of the factors of the farm internal environment. Eventually, the studies started to treat as significant both the internal and external factors. It all goes to cause the mixed matrix of the identified factors; • for quite a long time it was an attempt to identify the organic farming influencing factors analyzing the organic farmers as a homogeneous group, i. e. as an alternative to the conventional farmers. Only since mid-nineties of the last century it was started to search for the dividing line among the respondents farming organically classifying them by certain features, i. e. by different characteristics of the surveyed farmers or their farms. However, for this reason the matrix of the identified factors has become even more mixed, and the opinions of researchers on the factors’ significance to the farmers have divided even more. The analysis has showed and supposed the grounds for the classification of organic farmers into different groups by priority of activity independent of the duration of the development of organic farming and on this basis to identify the significance of the determinants of organic farming. The model for research of the determinants of organic farming includes two groups of factors (the external and internal) affecting the farmers’ decision to farm organically and four subgroups (respectively, the government and the market, and the farm and the personality of farmer). The research model was tested on the opinions of the respondents engaged in organic farming. The results of the empiric research proved the rightness of the theoretical model and enabled to clarify that in Lithuania under the present conditions the respondents engaged in organic farming assessed the groups of determinants differently. The cluster analysis of the empiric research enabled to identify two groups of organic respondents depending on statistically significant differences of activity priorities: profit-oriented and organic-oriented lifestyle (in the beginning of the clustering process 24 cluster groups of the respondents were formed). This shows that the clustering enabled the elimination of the socio-economic heterogeneity of organic farms while identifying the organic farming encouraging factors. The results of the empiric research have showed that in the opinion of the respondents engaged in organic farming the external factors are more significant than the internal; the external determinants are more encouraging but not limiting organic farming. The regressive analysis of the factors of organic farming has revealed that for both cluster groups of the respondents (profit-oriented and organic-oriented lifestyle) the external and internal determinants have different significance. The assessment of the determinants of organic farming depending on their importance and significance in the both identified cluster groups of the respondents has revealed the following differences: • the majority of the determinants encouraging organic farming the respondents of organic-oriented lifestyle assessed more favorably than the profit-oriented respondents; • the opinion of both groups’ respondents was the most different concerning the importance of the environmental issues (soil, water resources, etc.) on the farm

Designing Traceability into Big Data Systems

Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such Items across the spectrum of business use rather than from any specific application view. The design philosophy advocated in this paper is to drive the design process using a so-called description-driven approach which enriches models with meta-data and description and focuses the design process on Item re-use, thereby promoting traceability. Details are given of the description-driven design of big data systems at CERN, in health informatics and in business process management. Evidence is presented that the approach leads to design simplicity and consequent ease of management thanks to loose typing and the adoption of a unified approach to Item management and usage.Comment: 10 pages; 6 figures in Proceedings of the 5th Annual International Conference on ICT: Big Data, Cloud and Security (ICT-BDCS 2015), Singapore July 2015. arXiv admin note: text overlap with arXiv:1402.5764, arXiv:1402.575

Join Execution Using Fragmented Columnar Indices on GPU and MIC

The paper describes an approach to the parallel natural join execution on computing clusters with GPU and MIC Coprocessors. This approach is based on a decomposition of natural join relational operator using the column indices and domain-interval fragmentation. This decomposition admits parallel executing the resource-intensive relational operators without data transfers. All column index fragments are stored in main memory. To process the join of two relations, each pair of index fragments corresponding to particular domain interval is joined on a separate processor core. Described approach allows efficient parallel query processing for very large databases on modern computing cluster systems with many-core accelerators. A prototype of the DBMS coprocessor system was implemented using this technique. The results of computational experiments for GPU and Xeon Phi are presented. These results confirm the efficiency of proposed approach

The Semantic Grid: A future e-Science infrastructure

e-Science offers a promising vision of how computer and communication technology can support and enhance the scientific process. It does this by enabling scientists to generate, analyse, share and discuss their insights, experiments and results in an effective manner. The underlying computer infrastructure that provides these facilities is commonly referred to as the Grid. At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. To bridge this practice–aspiration divide, this paper presents a research agenda whose aim is to move from the current state of the art in e-Science infrastructure, to the future infrastructure that is needed to support the full richness of the e-Science vision. Here the future e-Science research infrastructure is termed the Semantic Grid (Semantic Grid to Grid is meant to connote a similar relationship to the one that exists between the Semantic Web and the Web). In particular, we present a conceptual architecture for the Semantic Grid. This architecture adopts a service-oriented perspective in which distinct stakeholders in the scientific process, represented as software agents, provide services to one another, under various service level agreements, in various forms of marketplace. We then focus predominantly on the issues concerned with the way that knowledge is acquired and used in such environments since we believe this is the key differentiator between current grid endeavours and those envisioned for the Semantic Grid