Linked Open Data (LOD) comprises of an unprecedented volume of structured datasets on the Web. However, these datasets are of varying quality ranging from extensively curated datasets to crowdsourced and even extracted data of relatively low quality. We present a methodology for assessing the quality of linked data resources, which comprises of a manual and a semi-automatic process. The first phase includes the detection of common quality problems and their representation in a quality problem taxonomy. In the manual process, the second phase comprises of the evaluation of a large number of individual resources, according to the quality problem taxonomy via crowdsourcing. This process is accompanied by a tool wherein a user assesses an individual resource and evaluates each fact for correctness. The semi-automatic process involves the generation and verification of schema axioms. We report the results obtained by applying this methodology to DBpedia. We identified 17 data quality problem types and 58 users assessed a total of 521 resources. Overall, 11.93% of the evaluated DBpedia triples were identified to have some quality issues. Apply- * Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. ISEM '13, September ing the semi-automatic component yielded a total of 222,982 triples that have a high probability to be incorrect. In particular, we found that problems such as object values being incorrectly extracted, irrelevant extraction of information and broken links were the most recurring quality problems. With this study, we not only aim to assess the quality of this sample of DBpedia resources but also adopt an agile methodology to improve the quality in future versions by regularly providing feedback to the DBpedia maintainers.

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Abstract-It is widely accepted that food supply and quality are major problems in the 21st century. Due to the growth of the world's population, there is a pressing need to improve the productivity of agricultural crops, which hinges on different factors such as geographical location, soil type, weather condition and particular attributes of the crops to plant. In many regions of the world, information about those factors is not readily accessible and dispersed across a multitude of different sources. One of those regions is Nepal, in which the lack of access to this knowledge poses a significant burden for agricultural planning and decision making. Making such knowledge more accessible can boot up a farmer's living standard and increase their competitiveness on national and global markets. In this article, we show how we converted several available, although not easily accessible, datasets to RDF, thereby lowering the barrier for data re-usage and integration. We describe the conversion, linking, and publication process as well as use cases, which can be implemented using the farming datasets in Nepal.

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The aim of this study was to determine temporary impacts of different fertilization systems on some labile soil biochemical and biological properties following potato monocropping under arid conditions. Field and incubation experiments were conducted to determine specifically soil organic carbon (SOC); dissolved organic carbon (DOC); dissolved organic nitrogen (DON); microbial biomass C (C mic), N (N mic), P (P mic); bacterial and fungi counts; soil resistance index (SRI); net N mineralization (N min); and some enzyme activity. Levels of SOC; DOC; N min , C mic , P mic ; bacteria and fungi counts; and soil respiration (SR) were significantly increased under organic and integrated fertilization systems compared with inorganic nano or NPK fertilization system, while levels of microbial biomass N (N mic) and DON were markedly increased under nano or fertilizers compared to organic or integrated (organic + inorganic) fertilizers. By contrast, higher values of metabolic quotient (qCO 2) were recorded in nano or fertilizer treatments suggesting that microbial biomass was less efficient under high maintenance of soil carbon. Enzyme activities of dehydrogenase (DH), β-glucosidase (βG), and acid phosphatase (Ac-P) were in the order of organic > integrated > inorganic fertilization systems, while enzyme activity of urease (UR) was in the vice versa order. Integrated fertilization system recorded greater levels of SOC; DOC; N min , C mic , P mic ; and SR relative to inorganic fertilizers even though applied at lower rates. It is, therefore, important for soils under monocropping system to poise organic and inorganic fertilization system that enhances soil health and soil organic matter build-up.

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