Analytic observations of seminar scientific work according toward objectives

Report is Deliverable 9 of 6th FP SSA project “Environmental friendly food production system: requirements for plant breeding and seed production” (ENVIRFOOD) and includes analytic observations of seminar scientific work according toward objectives - organic plant breeding, variety testing, seed production, organic food and feed quality, exposition of organic food products

Binary Star Database (BDB): New Developments and Applications

Binary star DataBase (BDB) is the database of binary/multiple systems of various observational types. BDB contains data on physical and positional parameters of 260,000 components of 120,000 stellar systems of multiplicity 2 to more than 20, taken from a large variety of published catalogues and databases. We describe the new features in organization of the database, integration of new catalogues and implementation of new possibilities available to users. The development of the BDB index-catalogue, Identification List of Binaries (ILB), is discussed. This star catalogue provides cross-referencing between most popular catalogues of binary stars.Comment: 5 pages, 1 figur

Open Data Quality

The research discusses how (open) data quality could be described, what should be considered developing a data quality management solution and how it could be applied to open data to check its quality. The proposed approach focuses on development of data quality specification which can be executed to get data quality evaluation results, find errors in data and possible problems which must be solved. The proposed approach is applied to several open data sets to evaluate their quality. Open data is very popular, free available for every stakeholder - it is often used to make business decisions. It is important to be sure that this data is trustable and error-free as its quality problems can lead to huge losses.Comment: 10 pages, 3 figures, 13th International Baltic Conference on Databases and Information Systems & The Baltic DB&IS 2018 Doctoral Consortium (Baltic DB&IS 2018) At: Lithuania, Trakai, Volume: 2158. arXiv admin note: substantial text overlap with arXiv:2007.0469

A Provenance Tracking Model for Data Updates

For data-centric systems, provenance tracking is particularly important when the system is open and decentralised, such as the Web of Linked Data. In this paper, a concise but expressive calculus which models data updates is presented. The calculus is used to provide an operational semantics for a system where data and updates interact concurrently. The operational semantics of the calculus also tracks the provenance of data with respect to updates. This provides a new formal semantics extending provenance diagrams which takes into account the execution of processes in a concurrent setting. Moreover, a sound and complete model for the calculus based on ideals of series-parallel DAGs is provided. The notion of provenance introduced can be used as a subjective indicator of the quality of data in concurrent interacting systems.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432

MSUO Information Technology and Geographical Information Systems: Common Protocols & Procedures. Report to the Marine Safety Umbrella Operation

The Marine Safety Umbrella Operation (MSUO) facilitates the cooperation between Interreg funded Marine Safety Projects and maritime stakeholders. The main aim of MSUO is to permit efficient operation of new projects through Project Cooperation Initiatives, these include the review of the common protocols and procedures for Information Technology (IT) and Geographical Information Systems (GIS). This study carried out by CSA Group and the National Centre for Geocomputation (NCG) reviews current spatial information standards in Europe and the data management methodologies associated with different marine safety projects. International best practice was reviewed based on the combined experience of spatial data research at NCG and initiatives in the US, Canada and the UK relating to marine security service information and acquisition and integration of large marine datasets for ocean management purposes. This report identifies the most appropriate international data management practices that could be adopted for future MSUO projects

Experiences in Bayesian Inference in Baltic Salmon Management

We review a success story regarding Bayesian inference in fisheries management in the Baltic Sea. The management of salmon fisheries is currently based on the results of a complex Bayesian population dynamic model, and managers and stakeholders use the probabilities in their discussions. We also discuss the technical and human challenges in using Bayesian modeling to give practical advice to the public and to government officials and suggest future areas in which it can be applied. In particular, large databases in fisheries science offer flexible ways to use hierarchical models to learn the population dynamics parameters for those by-catch species that do not have similar large stock-specific data sets like those that exist for many target species. This information is required if we are to understand the future ecosystem risks of fisheries.Comment: Published in at http://dx.doi.org/10.1214/13-STS431 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Organic plant breeding and seed production in Baltic States: developments and challenges

In this paper the current situation in plant breeding, variety testing for organic agriculture and organic seed production in the Baltic States, tasks for future are described

Microbial diversity in Baltic Sea sediments

This thesis focuses on microbial community structures and their functions in Baltic Sea sediments. First we investigated the distribution of archaea and bacteria in Baltic Sea sediments along a eutrophication gradient. Community profile analysis of 16S rRNA genes using terminal restriction length polymorphism (T-RFLP) indicated that archaeal and bacterial communities were spatially heterogeneous. By employing statistical ordination methods we observed that archaea and bacteria were structured and impacted differently by environmental parameters that were significantly linked to eutrophication. In a separate study, we analyzed bacterial communities at a different site in the Baltic Sea that was heavily contaminated with polyaromatic hydrocarbons (PAHs) and several other pollutants. Sediment samples were collected before and after remediation by dredging in two consecutive years. A polyphasic experimental approach was used to assess growing bacteria and degradation genes in the sediments. The bacterial communities were significantly different before and after dredging of the sediment. Several isolates collected from contaminated sediments showed an intrinsic capacity for degradation of phenanthrene (a PAH model compound). Quantititative real-time PCR was used to monitor the abundance of degradation genes in sediment microcosms spiked with phenanthrene. Although both xylE and phnAc genes increased in abundance in the microcosms, the isolates only carried phnAc genes. Isolates with closest 16S rRNA gene sequence matches to Exigobacterium oxidotolerans, a Pseudomonas sp. and a Gammaproteobacterium were identified by all approaches used as growing bacteria that are capable of phenanthrene degradation. These isolates were assigned species and strain designations as follows: Exiguobacterium oxidotolerans AE3, Pseudomonas fluorescens AE1 and Pseudomonas migulae AE2. We also identified and studied the distribution of actively growing bacteria along red-ox profiles in Baltic Sea sediments. Community structures were found to be significantly different at different red-ox depths. Also, according to multivariate statistical ordination analysis organic carbon, nitrogen, and red-ox potential were crucial parameters for structuring the bacterial communities on a vertical scale. Novel lineages of bacteria were obtained by sequencing 16S rRNA genes from different red-ox depths and sampling stations indicating that bacterial diversity in Baltic Sea sediments is largely unexplored

Science and Technology Cooperation in Cross-border Regions::A Proximity Approach with Evidence for Northern Europe

Given the sheer number of cross-border regions (CBRs) within the EU, their socio-economic importance has been recognized both by policy-makers and academics. Recently, the novel concept of cross-border regional innovation system has been introduced to guide the assessment of integration processes in CBRs. A central focus of this concept is set on analyzing the impact of varying types of proximity (cognitive, technological, etc.) on cross-border cooperation. Previous empirical applications of the concept have, however, relied on individual case studies and varying methodologies, thus complicating and constraining comparisons between different CBRs. Here a broader view is provided by comparing 28 Northern European CBRs. The empirical analysis utilizes economic, science and technology (S&T) statistics to construct proximity indicators and measures S&T integration in the context of cross-border cooperation. The findings from descriptive statistics and exploratory count data regressions show that technological and cognitive proximity measures are significantly related to S&T cooperation activities (cross-border co-publications and co-patents). Taken together, our empirical approach underlines the feasibility of utilizing the proximity approach for comparative analyses in CBR settings