POIESIS: A tool for quality-aware ETL process redesign

We present a tool, called POIESIS, for automatic ETL process enhancement. ETL processes are essential data-centric activities in modern business intelligence environments and they need to be examined through a viewpoint that concerns their quality characteristics (e.g., data quality, performance, manageability) in the era of Big Data. POIESIS responds to this need by providing a user-centered environment for quality-aware analysis and redesign of ETL flows. It generates thousands of alternative flows by adding flow patterns to the initial flow, in varying positions and combinations, thus creating alternative design options in a multidimensional space of different quality attributes. Through the demonstration of POIESIS we introduce the tool's capabilities and highlight its efficiency, usability and modifiability, thanks to its polymorphic design. © 2015, Copyright is with the authors.Peer ReviewedPostprint (published version

Representing Dataset Quality Metadata using Multi-Dimensional Views

Data quality is commonly defined as fitness for use. The problem of identifying quality of data is faced by many data consumers. Data publishers often do not have the means to identify quality problems in their data. To make the task for both stakeholders easier, we have developed the Dataset Quality Ontology (daQ). daQ is a core vocabulary for representing the results of quality benchmarking of a linked dataset. It represents quality metadata as multi-dimensional and statistical observations using the Data Cube vocabulary. Quality metadata are organised as a self-contained graph, which can, e.g., be embedded into linked open datasets. We discuss the design considerations, give examples for extending daQ by custom quality metrics, and present use cases such as analysing data versions, browsing datasets by quality, and link identification. We finally discuss how data cube visualisation tools enable data publishers and consumers to analyse better the quality of their data.Comment: Preprint of a paper submitted to the forthcoming SEMANTiCS 2014, 4-5 September 2014, Leipzig, German

Nitrogen, Phosphorus, and Suspended Solids Concentrations in Tributaries to the Great Bay Estuary Watershed in 2014

Nitrogen, phosphorus, and sediment loads to the Great Bay Estuary are a constant concern. The Piscataqua Region Estuaries Partnership (PREP) calculates the nitrogen load from tributaries to the Great Bay Estuary for its State of Our Estuaries reports. Therefore, the purpose of this study was to collect representative data on nitrogen, phosphorus, and suspended sediment concentrations in tributaries to the Great Bay Estuary in 2014. The study design followed the tributary sampling design which was implemented by the New Hampshire Department of Environmental Services between 2001 and 2007 and sustained by the University of New Hampshire from 2008 to the present, so as to provide comparable data to the previous loading estimates. The purpose of this memorandum is to document the results of quality assurance checks on the 2014 water quality data collected by UNH, so that PREP can calculates the nitrogen load from tributaries to the Great Bay Estuary. DES reviewed these data to ensure that they met data quality objectives for PREP and for Section 305b water quality assessment

Layout area models for high-level synthesis

Traditionally, the common cost functions, the number of functional units, registers and selector inputs, are used in high level synthesis as quality measures. However, these traditional design quality measures may not reflect the real physical design. To establish quality measures based on the physical designs, we propose layout estimation models for two commonly used data path and control layout architectures. The results show that quality measures deriving from our models give an accurate prediction of the final layout. The results also show that traditional cost functions are not good indicators for optimization in high level synthesis

Bullcoming v. New Mexico: Revisiting Analyst Testimony After Melendez-Diaz

Wallyfy is planned to be a social webmagazine with a focus on good content, with a quality check and moderation of the published content. The author of the study provides Wallyfy with thoughts and ideas about the website content and functionality. The main problem of the study was to explore what makes good content in social media for the potential users of Wallyfy, also using this insight to provide Wallyfy with directions for making decisions regarding both functionality and content.   The theory of the study is being used as a starting point for understanding the phenomenom social media and to easier grasp the problem. The method of the study is based on user- centered thinking in design, where the author seeks to understand the participant’s emotions, values and dreams. Design probes (tasks for the participants) have been used to aid the first steps of the quality data collection, enabling the 5 participants of the study to be a part of the idea generation and to familiarize them with social media. The participants then attended a workshop based on the quality data from the design probes. Further quality data were then derived from the discussion and the creative participation in the workshop.   The relevant data parts were then compiled and orginanised to be presented as the data collection result in the study. The main theme from the data was that the participants valued content more if a personal connection between the user and the content could be made. From a discussion of the data and theory, recommendations and requirements regarding content and functionally for Wallyfy was produced.2014-06-03 14:15, John von Neumann</p

Quality of life and building design in residential and nursing homes for older people

Older people living in residential and nursing care homes spend a large proportion of their time within the boundaries of the home, and may depend on the environment to compensate for their physical or cognitive frailties. Regulations and guidelines on the design of care buildings have accumulated over time with little knowledge of their impact on the quality of life of building users. The Design in Caring Environments Study (DICE) collected cross-sectional data on building design and quality of life in 38 care homes in and near Sheffield, Yorkshire. Quality of life was assessed using methods which included all residents regardless of their frailty, and staff morale was also assessed. The physical environment was measured on 11 user-related domains using a new tool, the Sheffield Care Environment Assessment Matrix (SCEAM). Significant positive associations were found between several aspects of the built environment and the residents' quality of life. There was evidence that a focus on safety and health requirements could be creating risk-averse environments which act against quality of life, particularly for the least frail residents. Staff morale was associated with attributes of a non-institutional environment for residents rather than with the facilities provided for the staff. The new tool for assessing building design has potential applications in further research and for care providers