Towards data abstraction in networked information retrieval systems

Networked information retrieval aims at the interoperability of heterogeneous information retrieval (IR) systems. In this paper, we show how differences concerning search operators and database schemas can be handled by applying data abstraction concepts in combination with uncertain inference. Different data types with vague predicates are required to allow for queries referring to arbitrary attributes of documents. Physical data independence separates search operators from access paths, thus solving text search problems related to noun phrases, compound words and proper nouns. Projection and inheritance on attributes support the creation of unified views on a set of IR databases. Uncertain inference allows for query processing even on incompatible database schemas.     

Storage and retrieval considerations of binary data bases

A binary approach to data storage and retrieval is introduced. It views the data base as a two-dimensional matrix that relates entities to all possible values the attributes of these entities may take. As such, it provides a unified solution to the two conflicting types of data base transactions—operational and managerial. An analytical investigation of the feasibility of binary storage and a compression method for reducing meaningless areas of the matrix are presented. Storage efficiencies of binary and conventional inverted file methods are compared and evaluated. An analysis of retrieval considerations associated with the binary matrix is given, particularly the issue of going from high to low orders of compression. Results of these analyses indicate that the binary data base's efficiency increases with increases in query complexity. Future research directions are sited and discussed.     

Frequency and impact of spelling errors in bibliographic data bases

Using a composite sample of over 3600 index terms drawn from 11 different machine-readable bibliographic data bases, estimates were made of the spelling error frequencies of each of these data bases, as well as the frequency of posting to misspelled terms. The terms studied included assigned index terms as well as some terms from titles and abstracts. The frequency of index term misspellings ranged from a high of almost 23% for one data base to a low of less than $\text{1}\text{2}\text{\%}$ for another data base. The frequency of posting to misspelled terms ranged from about one posting in 8000 citations for one data base, to about one posting in 160 citations in another data base. The impact of these error rates is discussed for the tape supplier, tape user and end user. Some suggestions are given regarding search strategry.     

Management innovation through standardization: Consultants as standardizers of organizational practice

Management innovation and the consultants who promote and support it are both typically associated with the ‘new’, with departures from the norm and from standard approaches. Indeed, standardization is often seen as an impediment to innovation, especially in the current ‘post-bureaucratic’ era. This article challenges such a view, arguing that consultant-led management innovation is often highly standardized. Based upon qualitative research into internal consultancy in large business organizations, both standardizing agendas and standardized methods are identified from a range of consultant-led management innovation programs. The analysis then points to some of the structural and cultural features of organizations that lead to managers favouring incremental, standardized approaches to change, even if these are often contested. In conclusion, the article points to the need to consider a range of different dimensions in the relationship between standardization and management innovation.     

数据挖掘—大数据时代的重要工具

介绍了数据挖掘的定义、过程以及数据挖掘的功能、应用和发展前景。     

A comparison of data bases for retrieving references to the literature on drugs

The main indexes to recent drug literature have been studied using a file of nearly 400 references to a new class of drugs, the histamine H₂-receptor antagonists. The results are analysed with reference to the inclusion of references in the data bases, retrieval by searches for non-proprietary names, and timeliness. It has been found that the systems examined—ASCA, Ringdoc, Drugdoc, BIOSIS, Chemical Abstracts and Medlars/Index Medicus—differ considerably in their coverage of conference abstracts and their indexing of general articles, although they all retrieve most of the main pharmacological papers. Attention is drawn to the high proportion of conference abstracts in the literature of this expanding field.     

青稞标准化生产技术规程

通过粮油作物易学易用丰产栽培技术项目的实施,研究和探讨了青稞标准化生产技术,提出了青稞标准化生产技术规程.     

Computer-aided searching of bibliographic data bases: Online estimation of the value of information

The study presents and synthesizes the results of a series of five experiments on human information-seeking behavior in three different information-seeking environments. The first three experiments utilized a highly-controlled, simulated information-seeking task developed to study human search strategies in citation networks. Emphasis in the fourth and fifth experiments was placed on assessing the value of information for humans in realistic search environments. Subjects search on a topic of their own choice in a data base of fiction in Experiment Four and a data base of technical literature in Experiment Five. After summarizing the experimental results, a conceptual model of how humans value information is presented. The model is then used as a basis for a broad interpretation of the empirical results. Implications of both the empirical and modeling results are considered for the areas of information retrieval logic, system flexibility, retrieval methods, types of aiding, online estimation of information value, and computerizing versus computer-aiding.     

The impact of machine-readable data bases on library and information services

Library and information services already feel the impact of the burgeoning development in the field of bibliographic data bases, and this effect will increase in the future. This article explores the growth, origins, technological development, and current activities of bibliographic data bases and examines the NCLIS National Program relative to these aspects. The relationships between data base function, funding, and use are set forth in a discussion of data base producers. Discussions of data formats, data elements and file structure provide the groundwork for a closer look at the methods and purposes underlying the retrospective and current awareness search capabilities of existent data bases. A review of related data base and data base center characteristics highlights the discussion of retrospective and current awareness search functions and intermediary search services. In all data base activity the prime objective of making available information easily accessible to all who need it emerges as no small task, especially in light of the realities of scattered resources and unsteady funding. Data base networking and resource sharing constitute one means to the achievement of this ideal. The greatest potential of the NCLIS National Program lies in this direction, in its ability to promote and provide a framework for the coordination of data base-related activities and research in response to national needs.     

晚近时期标准化发展趋势

20世纪80年代末到21世纪的前10年间,标准化呈现国际化发展趋势,标准属性从生产技术工具向贸易竞争工具深化,标准化功能从事后规范向事前引导发展,标准化身份从企业技术决策上升为国家战略,标准化出发点从技术保障转向社会公益,标准结构由单一框架向复合学科组合发展.标准化复归企业为主体带动国家发展可能成为标准化的又一次跳跃,在企业、国家、国际循环上升过程中,通过标准化发展和产业竞争发展实现企业、国家和世界的繁荣发展.     

Sorting of textual data bases: A variety generation approach to distribution sorting

A method of sorting large textual data-bases by computer using external storage is proposed. The range of sort-keys in a sample of data to be sorted is divided into a fixed set of partitions, which should also give an adequate representation of new data from a similar source. The partitions are composed of ordered key ranges. An incoming data stream is distributed into a series of bins according to the partition in which the key lies, and the bins are then seperately sorted, using an internal sort, to give an ordered file. It is shown how the number of disc accesses needed depends on the manner in which the bins become filled, and thus on statistics of the data. Experiments using an INSPEC data-base give information on which estimates of the efficiency of the method can be based.     

Investigating use continuance of data mining tools

While improving decisional quality is important to businesses, continued use of DMTs is a critical issue for managerial personnel. This problem mainly concerns the willingness of an individual to participate in the behavior. It can be further defined in a routine-based working behavior. This problem essentially involves three key issues, task fit, technology use, and habit. This study therefore integrates task-technology fit (TTF) model, expectation–confirmation mode (ECM), and habit, to examine the determinants of continued use of DMTs. Prior studies have focused on intention to use DMTs in the first time and only considered part of the three issues for identifying the determinants. 285 respondents from managerial personnel were collected to empirically evaluate this research model. The three issues are all important in influencing continuance use intention of DMTs. In particular, the task-technology fit indicates a direct effect on two factors of the technology use issue, user satisfaction and perceived usefulness, and an indirect effect on continuance use intention. User satisfaction and perceived usefulness, and habit are the key predictors of continuance use intention.     

优质保健青稞“藏青25”标准化生产中农药的科学使用技术

本文针对青稞品种“藏青25”的生产技术标准,根据GAP（中药材生产质量管理规范）要求提出了优质保健青稞“藏青25”标准化生产中农药的科学使用技术。     

Information quality life cycle in secondary use of EHR data

The paper argues that existing research on information quality (IQ) mainly focuses on the primary use of electronic health record (EHR) data, whereas IQ in secondary use of EHR data needs further deliberation. The current view of IQ in a healthcare context is static. It assumes that once the EHR system generates the information product, individual users may act on the information based on their subjective perception of its quality. However, this view ignores the complexities of secondary use of EHR data, in which users are actively involved in (re)generating and communicating the information product. Thus, IQ does not remain static but keeps on transforming through active engagement and interpersonal communication. To contribute to this debate, we conducted a qualitative case study in a Norwegian healthcare context by employing an IQ life cycle model. In conclusion, we enhanced the existing IQ model by (1) adding interpersonal communication, (2) showing the interrelations of the IQ dimensions, and (3) integrating the mechanisms of the transformation process for IQ in secondary use of EHR data. In doing so, we unfold the dynamics of IQ in the secondary use of EHR data.     

Data deluge or data trickle? Difficulties in acquiring public data for telecommunications policy analysis

Abstract

There is a paucity of granular, high-resolution broadband data in the United States, which limits the prospects of informed telecommunications policy debates. In the absence of regulation requiring telecommunication providers to accurately report service footprints, pricing, and service quality data, providers refuse to disclose this information, routinely citing competition as the primary reason for keeping network and pricing data obfuscated. In addition, many secondary datasets needed for broadband planning and policy research, such as parcel or address point data, are equally challenging to gather. These datasets are often controlled by county governments, with no overarching access policy, resulting in neighboring counties with widely divergent policies for the release of these important data. In this article we explore the challenges of open data and its impacts on telecommunication policy development. A recent project which explored the spatial provision of Google Fiber in the Kansas City metropolitan area helps to highlight these difficulties. Basic strategies for mitigating information asymmetries and the lack of data transparency for telecommunication policy analysis are discussed.     

Gender and sex bias in COVID-19 epidemiological data through the lens of causality

The COVID-19 pandemic has spurred a large amount of experimental and observational studies reporting clear correlation between the risk of developing severe COVID-19 (or dying from it) and whether the individual is male or female. This paper is an attempt to explain the supposed male vulnerability to COVID-19 using a causal approach. We proceed by identifying a set of confounding and mediating factors, based on the review of epidemiological literature and analysis of sex-dis-aggregated data. Those factors are then taken into consideration to produce explainable and fair prediction and decision models from observational data. The paper outlines how non-causal models can motivate discriminatory policies such as biased allocation of the limited resources in intensive care units (ICUs). The objective is to anticipate and avoid disparate impact and discrimination, by considering causal knowledge and causal-based techniques to compliment the collection and analysis of observational big-data. The hope is to contribute to more careful use of health related information access systems for developing fair and robust predictive models.     

Data quality management,data usage experience and acquisition intention of big data analytics

Big data analytics associated with database searching, mining, and analysis can be seen as an innovative IT capability that can improve firm performance. Even though some leading companies are actively adopting big data analytics to strengthen market competition and to open up new business opportunities, many firms are still in the early stage of the adoption curve due to lack of understanding of and experience with big data. Hence, it is interesting and timely to understand issues relevant to big data adoption. In this study, a research model is proposed to explain the acquisition intention of big data analytics mainly from the theoretical perspectives of data quality management and data usage experience. Our empirical investigation reveals that a firm's intention for big data analytics can be positively affected by its competence in maintaining the quality of corporate data. Moreover, a firm's favorable experience (i.e., benefit perceptions) in utilizing external source data could encourage future acquisition of big data analytics. Surprisingly, a firm's favorable experience (i.e., benefit perceptions) in utilizing internal source data could hamper its adoption intention for big data analytics.