Data Integrity Issues Research Articles

A survey of protein interaction data and multigenic inherited disorders

BackgroundMultigenic diseases are often associated with protein complexes or interactions involved in the same pathway. We wanted to estimate to what extent this is true given a consolidated protein interaction data set. The study stresses data integration and data representation issues.ResultsWe constructed 497 multigenic disease groups from OMIM and tested for overlaps with interaction and pathway data. A total of 159 disease groups had significant overlaps with protein interaction data consolidated by iRefIndex. A further 68 disease overlaps were found only in the KEGG pathway database. No single database contained all significant overlaps thus stressing the importance of data integration. We also found that disease groups overlapped with all three interaction data types: n-ary, spoke-represented complexes and binary data – thus stressing the importance of considering each of these data types separately.ConclusionsAlmost half of our multigenic disease groups could potentially be explained by protein complexes and pathways. However, the fact that no database or data type was able to cover all disease groups suggests that no single database has systematically covered all disease groups for potential related complex and pathway data. This survey provides a basis for further curation efforts to confirm and search for overlaps between diseases and interaction data. The accompanying R script can be used to reproduce the work and track progress in this area as databases change. Disease group overlaps can be further explored using the iRefscape plugin for Cytoscape.

Data Integrity Issue in Asset-Intensive Industry

Fixed asset management is a critical competitive differentiator in asset intensive industries, but the literature on the management of fixed assets focuses on technical issues rather than operational and human concerns. Utilizing an in-depth case study method involving systems demonstrations and interviews, this research assesses that current state of fixed asset management in another of blue chip companies across 5 industry sectors. We conducted a comparative benchmarking assessment that focused on the existing capabilities and completeness of vision for the future of asset management in the asset intensive companies. The research identifies major difficulties with the current methods, technologies used in fixed asset management in these companies, and provides a range of improvements based on the case study data and cross-industry comparison, focusing on people, processes and technology.

Achieving data integrity by forming the digital signature using RSA and SHA-1 algorithm

Technology has been touching our lives in almost every domain. With the advent of modern technologies, the need of enhancing its security also arises. Data security has become one of the most important issues of concern. Data security is achieved with the help of adapting certain security measures. Here, in this paper we have analyzed the various cryptographic concepts. Encryption and decryption are two most important aspects of cryptography and data security. The special light has been thrown on data integrity and protection issues. The RSA algorithm has been explained. The implementation of the algorithm has also been given with the help of proving a graphical interface. The data integrity has been established at the client and receiver end by not limiting it to a standalone application.

Towards a monitoring smart home for the elderly: One experience in retrofitting a sensor network into an existing home

There has been a lot of research interest in research smart homes for behaviour recognition and related tasks supporting the elderly living alone. Amongst the many challenges of such research are the selection of sensors and the secure storage of data. However, there are other important issues such as reliable data collection, acceptance of sensor systems into the inhabitant's life, and ensuring that the sensor system does not create hazards in the house.In this paper we report on our experiences retrofitting a set of wireless sensors into the house of an elderly person living alone and an exploration of some of the data integrity issues faced.

Proteomics: from single molecules to biological pathways

The conventional reductionist approach to cardiovascular research investigates individual candidate factors or linear signalling pathways but ignores more complex interactions in biological systems. The advent of molecular profiling technologies that focus on a global characterization of whole complements allows an exploration of the interconnectivity of pathways during pathophysiologically relevant processes, but has brought about the issue of statistical analysis and data integration. Proteins identified by differential expression as well as those in protein–protein interaction networks identified through experiments and through computational modelling techniques can be used as an initial starting point for functional analyses. In combination with other ‘-omics’ technologies, such as transcriptomics and metabolomics, proteomics explores different aspects of disease, and the different pillars of observations facilitate the data integration in disease-specific networks. Ultimately, a systems biology approach may advance our understanding of cardiovascular disease processes at a ‘biological pathway’ instead of a ‘single molecule’ level and accelerate progress towards disease-modifying interventions.

Navy Commander helps military patients near and far

The Department of Defense (DoD) Pharmacoeconomic Center is a hive of buzzing activity and a melting pot of various health care personnel from the U.S. Army, U.S. Navy, U.S. Air Force, U.S. Public Health Service, DoD civil servants, and private contractors. Located in San Antonio and operating within the Military Health System, pharmacists at the center, affectionately dubbed the PEC, manage numerous facets of a world-class pharmacy benefit program. From helping deployed patients in remote locations, to analyzing a wealth of pharmacy and medication data, to overseeing a standardized formulary that stretches across three points of care, the PEC is a diverse environment for pharmacy practice.

Understanding RFID Technology within a Business Intelligence Framework

Radio Frequency Identification (RFID) technology provides new and exciting opportunities for increasing organizational, financial, and operational performance. With its focus on organizational efficiency and effectiveness, RFID technology is superior to barcodes in its ability to provide source automation features that increase the speed and volume of data collection for analysis. Today, applications that employ RFID are growing rapidly and this technology is in a continuous state of evolution and growth. As it continues to progress, RFID provides us with new opportunities to use business intelligence (BI) to monitor organizational operations and learn more about markets, as well as consumer attitudes, behaviors, and product preferences. This technology can even be used to prevent potentially faulty or spoiled products from ending up in the hands of consumers. However, RFID offers significant challenges to organizations that attempt to employ this technology. Most significantly, there exists the potential for RFID to overwhelm data collection and BI analytic efforts if organizations fail to effectively address RFID data integration issues. To this end, the purpose of this article is to explicate the dynamic technology of RFID and how it is being used today. Additionally, this article will provide insights into how RFID technology is evolving and how this technology relates to BI and issues related to data integration. This knowledge has never been more essential. While IT academic research into RFID development and issues has declined in recent years, RFID continues to be a vital area of exploration, especially as it relates to BI in the 21st century.

Looking Back, Looking Forward, and Transformation in Information Ethics

This issue represents a unique perspective in at this moment in time. There is a change occurring; indeed, a transition has been under way for some time, from those who set path, those who defined this field, to a newly minted body of scholars who see context for parameters of in a vastly different way. We, this field of ethics, still grapple with same fundamental definitions of as were presented in 1980s, inception of this discipline. We still think about issues of creation, access, control, and dissemination of information. Yet, what constitutes definition of information and what constitutes those activities around is dramatically different. James Moor was one of first to call attention to different nature of data, describing it as greased and malleable; he called attention to policy vacuums and conceptual muddles created by digital data. Those characteristics articulated in 1980s have indeed proven true, and even Moor may be surprised at extent to which those very characteristics have transformed not only research and scholarship but individuals and societies themselves. We have seen such arguments for everything is miscellaneous, and the world is flat-those are indicative of collapsing parameters resultant from ways in which we create, use, and disseminate in this moment. This forces us to a broader question.Where is of ethics? It is increasingly diffused. It is, simultaneously more important and less important than ever. It is ever important because every essentially grapples now with issues, and because of that, its significance as a stand- alone discipline is called into question. Scholars from across an array of disciplines are engaging more directly with issues of data integrity, ethical research practices, privacy, autonomy, identity, trust, reality, data sharing, data manipulation, fragmentation, orientation. Information ethicists have made these issues explicit over years, but increasingly, specificity is collapsing and these issues certainly do not reside in any one clear domain. This is happening because of nature of digital data which is causing every scholar, researcher, bureaucrat, and individual to think differently about their relationship with world, in both physical and virtual realms. Information scholarship is changing, pushing boundaries in its scope and reach. A physicist, Vlatko Vedra, recently described theory of quantum information, that everything, universe itself, is information. Information is superior. If we follow his lead, everything, then, is ethics? With that, one might also argue that nothing is ethics, a stance I do not support.Information has co- existed along with other ethics for many years: computer ethics, business ethics, bioethics. Each of these has a corresponding disciplinary home. Information has had a rocky home in library and studies, and it is notable to consider Enright's perspectives on this. It is also notable to consider numbers of LIS programs that still have no course; there is an implicit assumption that because of accreditation standards, will be interwoven across curriculum, an assumption I question. Ethics is often seen as an afterthought in professional programs, accreditation standards notwithstanding. Other disciplines, for example, those in Science, Technology, Engineering, and Mathematics (STEM), debate heartily what mode is best for education-stand alone courses or infusion models. I have not seen same curricular debates in LIS. More commonly, LIS are introduced through standard codes of ethics. Professional are symbolically embodied in codes-codes of ethics, as Zaiane, presents, are universal guiding documents, but do not ensure ethical behavior or professionalism. …

Mapping “infected” real estate property

PurposeIn 2009, the research team of Unger and Nelen was requested to study the scale of entwinement between money laundering activities and the Dutch real estate sector. For this, the team developed a data mining framework to detect real estate property at risk of being part of a money laundering scheme. Part of this study involved a criminological testing of the developed framework which resulted in the statement that improvements and alterations are necessary to increase the framework's validity and reliability. This paper aims to review this framework and generate refinements.Design/methodology/approachThis paper is concerned with a review – on the basis of data mining theory – with respect to the original framework in order to generate refinements for a future model.FindingsIn general, three major shortcomings were identified, being: the use of unspecified detection clusters; the theoretical nature of some of the risk indicators in combination with data integrity issues; and the use of speculative/arbitrary risk indicators.Originality/valueAddressing these shortcomings in a future data mining framework will very likely increase its effectiveness and so, increase the ability of law enforcement agencies to counter money laundering activities more effectively and efficiently.

Monitoring and Data Quality Assessment for the ATLAS Liquid Argon Calorimeter at the LHC

The ATLAS detector at the Large Hadron Collider, in full operation since fall 2009, is expected to collect an unprecedented wealth of data at a completely new energy scale. In particular, its Liquid Argon (LAr) electromagnetic and hadronic calorimeters will play an essential role in measuring final states with electrons and photons and in contributing to the measurement of jets and missing transverse energy. The ATLAS LAr calorimeter is a system of three sampling calorimeters with LAr as sensitive medium. It is composed by 182,468 readout channels and covers a pseudorapidity ( η = − ln ( θ / 2 ) ) region up to 4.9. Efficient monitoring will be crucial from the earliest data taking onward and at multiple levels of the electronic readout and triggering systems. Detection of serious data integrity issues along the readout chain during data taking will be essential so that quick actions can be taken. Moreover, by providing essential information about the performance of each subdetector, the quality of the data collected (hot or dead channels, calibration problems, timing problems...) and their impact on physics measurables, the monitoring will be critical in guaranteeing that data are ready for physics analysis in due time. Software tools and general data quality policy, developed and tuned since 2006 and first ATLAS cosmic runs, are discussed. A special emphasis on the monitoring procedures during the first LHC collisions run will be given. The roadmap to achieve a fully automated system will be finally mentioned.

Meta-data Driven Data Chunk Based Secure Data Storage for SaaS

Software-as-a-Service, i.e. SaaS, is an emergin g model that allows t enants t o out source computation a nd sto rage of their sensitive data to ext ernal service provid ers. Although Saa S mo del provides many b enefits, it introduce s new security conce rns in dat a s torage. Untrustworthy service providers might violate tenants’ da ta priva cy or maliciously delete, mod ify and falsify tenants’ data due to some reason, which hinders wider adoption of SaaS model. With regard to data storage security issue of S aaS model, this paper gives the c oncept of data combination privacy and data integrity for SaaS, and th en presents a novel data storage protection mechanism which combines the data privacy protection issue and secure data possession issues based on a meta-data driven data chunk based data storage model. For data privacy issue in SaaS, this paper uses the data fragmentation technology to hidden t he ass ociation between data att ributes based on dat a co mbination privacy c oncept, wh ich protects the privacy of data. For secure d ata possession issue in SaaS, this paper gives the concept of data i ntegrity, considers secure data poss ession in term s of du rable i ntegrity, corre ct int egrity and provenance in tegrity, proposes a nove l secure dat a stora ge verifica tion mecha nism based on da ta chunk for Saa S model . B ased on a met a-data d riven da ta chun k based dat a-sharing stora ge mod el, data privacy and data integrity issues could be solved together well. We demonstrate the correctness and effectiveness of this mechanism through the experiments in this paper.

The PREVIEW Global Risk Data Platform: a geoportal to serve and share global data on risk to natural hazards

Abstract. With growing world population and concentration in urban and coastal areas, the exposure to natural hazards is increasing and results in higher risk of human and economic losses. Improving the identification of areas, population and assets potentially exposed to natural hazards is essential to reduce the consequences of such events. Disaster risk is a function of hazard, exposure and vulnerability. Modelling risk at the global level requires accessing and processing a large number of data, from numerous collaborating centres. These data need to be easily updated, and there is a need for centralizing access to this information as well as simplifying its use for non GIS specialists. The Hyogo Framework for Action provides the mandate for data sharing, so that governments and international development agencies can take appropriate decision for disaster risk reduction. Timely access and easy integration of geospatial data are essential to support efforts in Disaster Risk Reduction. However various issues in data availability, accessibility and integration limit the use of such data. In consequence, a framework that facilitate sharing and exchange of geospatial data on natural hazards should improve decision-making process. The PREVIEW Global Risk Data Platform is a highly interactive web-based GIS portal supported by a Spatial Data Infrastructure that offers free and interoperable access to more than 60 global data sets on nine types of natural hazards (tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions) and related exposure and risk. This application portrays an easy-to-use online interactive mapping interface so that users can easily work with it and seamlessly integrate data in their own data flow using fully compliant OGC Web Services (OWS).

The ACGT project in retrospect: Lessons learned and future outlook

Abstract The objective of the ACGT (Advancing Clinico-Genomic Trials on Cancer: Open Grid Services for improving Medical Knowledge Discovery, www.eu-acgt.org ) project that has recently concluded successfully was the development of a semantically rich infrastructure facilitating seamless and secure access and analysis, of multi-level clinical and genomic data enriched with high-performing knowledge discovery operations and services in support of multicentric, post-genomic clinical trials. In this paper we describe the way the ACGT consortium has approached important challenges in the design and the execution of the clinical trials such as the issues of data integration, semantics based data fusion, data processing and knowledge extraction, privacy and security, etc. Furthermore we provide a number of key “lessons learned” during the process and give directions for further developments in the future.

A labeled-tree approach to semantic and structural data interoperability applied in hydrology domain

The issues of data integration and interoperability pose significant challenges in scientific hydrological and environmental studies, due largely to the inherent semantic and structural heterogeneities of massive datasets and non-uniform autonomous data sources. To address these data integration challenges, we propose a unified data integration framework, called Hydrological Integrated Data Environment (HIDE). HIDE is based on a labeled-tree data integration model referred to as DataNode tree. Using this framework, characteristics of datasets gathered from diverse data sources – with different logical and access organizations – can be extracted and classified as Time–Space–Attribute (TSA) labels and are subsequently arranged in a DataNode tree. The uniqueness of our approach is that it effectively combines the semantic aspects of the scientific domain with diverse datasets having different logical organizations to form a unified view. Further, we also adopt a metadata-based approach for specifying the TSA-DataNode tree in order to achieve flexibility and extensibility. The search engine of our HIDE prototype system evaluates a simple user query systematically on the TSA-DataNode tree, presenting integrated results in a standardized format that facilitates both effective and efficient data integration.

Network infrastructure security

Research on Internet security over the past few decades has focused mainly on information assurance, issues of data confidentiality and integrity as explored through cryptograph algorithms, digital signature, authentication code, etc. Unlikeotherbooks onnetwork information security, Network Infrastructure Security by Angus Wong and Alan Yeungaddresses the emerging concern with better detecting and preventing routers and other network devices from being attacked or compromised. Attacks to network infrastructure affect large portions of the Internet at a time and create large amounts of service disruption, due to breaches such as IP spoofing, routing table poisoning and routing loops. Daily operations around the world highly depend on the availability and reliability of the Internet, which makes the security of this infrastructure a top priority issue in the field. Network Infrastructure Security is a book that bridges the gap between the study of the traffic flow of networks and the study of the actual network configuration. This book makes effective use of examples and figures to illustrate network infrastructure attacks from a theoretical point of view. The book includes conceptual examples that show how network attacks can be run, along with appropriate countermeasures and solutions. About the authors Angus Kin-Yeung Wong obtained his BSc and PhD degrees from City University of Hong Kong and is currently an associate professor at Macao Polytechnic Institute. Alan Kai-Hau Yeung obtained his BSc and PhD degrees from the Chinese University of Hong Kong and is currently an associate professor at City University of Hong Kong. Wong and Yeung have been collaborating in network-related research for over 10 years.

Research on relational-algebra-based schema mapping of data integration

Integrated mapping is one of the basic issues in data integration,while it still has some deficiencies such as low repetition reducing rate,lack of accuracy,etc. Based on the research of Global-As-View (GAV) an d Local-As-View (LAV),two fundamental mapping modes of data integration,and the mode matching,in connection with the questions in integrated mapping like repetition reducing and the transformation between boolean element value and semantic value,the article extended the existing theory of relational algebra. A mapping program of source-objective mode was designed. In such a program,the object congregation and relation congregation of source mode were expanded,and then objective mode was to be obtained through processing the expanded mode with expanded relational algebra,and the specific derivation process during the operation was represented. The feasibility of the program is verified through illustrating examples.

Constructing Ontology-Based Petroleum Exploration Database for Knowledge Discovery

Volumes of petroleum resources data are archived in different companies. Complex geospatial heterogeneous data structures complicate the accessibility and presentation of data in petroleum industries. Objectives of the current research are to integrate the data from different sources and connect them intelligently and semantically. Petroleum exploration databases provide a central focus for scientific communities as well as providing useful resources to aide research. However, such resources require constant curation and often become outdated and discontinued. In this research work, we develop an ontology-based system for managing petroleum exploration data that addresses the issues of data integration and information sharing. Ontology approach ensures petroleum data validity that will support petroleum knowledge discovery process.

Web ontology data matching for integration: method and framework

PurposeMatching relevant ontology data for integration is vitally important as the amount of ontology data increases along with the evolving Semantic web, in which data are published from different individuals or organizations in a decentralized environment. For any domain that has developed a suitable ontology, its ontology annotated data (or simply ontology data) from different sources often overlaps and needs to be integrated. The purpose of this paper is to develop intelligent web ontology data matching method and framework for data integration.Design/methodology/approachThis paper develops an intelligent matching method to solve the issue of ontology data matching. Based on the matching method, it also proposes a flexible peer‐to‐peer framework to address the issue of ontology data integration in a distributed Semantic web environment.FindingsThe proposed matching method is different from existing data matching or merging methods applied to data warehouse in that it employs a machine learning approach and more similarity measurements by exploring ontology features.Research limitations/implicationsThe proposed method and framework will be further tested for some more complicated real cases in the future.Originality/valueThe experiments show that this proposed intelligent matching method increases ontology data matching accuracy.

Thought for Food: A New Dataset on Innovation for Agricultural Use

Summary The global number of agricultural-use patents has grown fairly steadily over the past thirty years, but the world total hides some volatility nation by nation. Figure 1 shows t he number of patents for some key nations, arranged by the year of application. The precipitous decline after 2001 is mostly an artifice of the data, as we used patents granted before December of 2006, and many applications from the preceding 5 years were not yet granted to make our dataset. Notice the rise of China’s importance in the last seven year of the period, regardless of this lag problem (evidence of even greater importance once all applications have time to be granted). Japan has slowly climbed to match the US as the single national leader (although remember that post-1996 Japanese values are projected due to data integrity issues). One very interesting story is the importance of the ‘rest of the world’, nations which are not among the top five patenting authorities. Figure 1: Patent Counts by Nation over Time

Special issue devoted to papers presented at the first international conference on information systems technology and management, New Delhi, March 12–13, 2007

The First International Conference on Information Systems Technology and Management was held in New Delhi in March, 2007. The conference was organized jointly by the University of Florida, USA and the Institute of Management and Technology, Ghaziabad, India. Forty-seven papers, divided into three tracks, were presented at the conference. The tracks were: Information Systems, Information Technology and Information Management. For this special issue, devoted to ICISTM-07, nine papers were submitted for consideration, of which two have been accepted for publication. The first paper, titled, ‘Reactivity Based Model to Study Online Auctions Dynamics,’ by Pereira et al. addresses bidder behavior issues in online auction environments. The paper develops a new characterization model for online auctions. In this model, they take into account the change in a bidder’s behavior motivated by events during the course of an auction. The new model is applied to actual datasets of eBay auctions to understand specific online auction negotiation patterns. The model has implications for the design of more complete automatic agents. The second paper titled ‘Computing Full Disjunction Using COJO’ by Kumar et al. addresses the issue of data integration in a relational database management environment. The authors propose a ‘Correct Outer Join Ordering’ strategy which results in full disjunction of relations resulting in a better database design compared to existing strategies.