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Research and Advances Jan 1 2010

Designing Data Governance

Organizations are becoming increasingly serious about the notion of "data as an asset" as they face increasing pressure for reporting a "single version of the truth." In a 2006 survey of 359 North American organizations that had deployed business intelligence and analytic systems, a program for the governance of data was reported to be one of the five success "practices" for deriving business value from data assets. In light of the opportunities to leverage data assets as well ensure legislative compliance to mandates such as the Sarbanes-Oxley (SOX) Act and Basel II, data governance has also recently been given significant prominence in practitioners' conferences, such as TDWI (The Data Warehousing Institute) World Conference and DAMA (Data Management Association) International Symposium. The objective of this article is to provide an overall framework for data governance that can be used by researchers to focus on important data governance issues, and by practitioners to develop an effective data governance approach, strategy and design. Designing data governance requires stepping back from day-to-day decision making and focusing on identifying the fundamental decisions that need to be made and who should be making them. Based on Weill and Ross, we also differentiate between governance and management as follows: • Governance refers to what decisions must be made to ensure effective management and use of IT (decision domains) and who makes the decisions (locus of accountability for decision-making). • Management involves making and implementing decisions. For example, governance includes establishing who in the organization holds decision rights for determining standards for data quality. Management involves determining the actual metrics employed for data quality. Here, we focus on the former. Corporate governance has been defined as a set of relationships between a company's management, its board, its shareholders and other stakeholders that provide a structure for determining organizational objectives and monitoring performance, thereby ensuring that corporate objectives are attained. Considering the synergy between macroeconomic and structural policies, corporate governance is a key element in not only improving economic efficiency and growth, but also enhancing corporate confidence. A framework for linking corporate and IT governance (see Figure 1) has been proposed by Weill and Ross. Unlike these authors, however, we differentiate between IT assets and information assets: IT assets refers to technologies (computers, communication and databases) that help support the automation of well-defined tasks, while information assets (or data) are defined as facts having value or potential value that are documented. Note that in the context of this article, we do not differentiate between data and information. Next, we use the Weill and Ross framework for IT governance as a starting point for our own framework for data governance. We then propose a set of five data decision domains, why they are important, and guidelines for what governance is needed for each decision domain. By operationalizing the locus of accountability of decision making (the "who") for each decision domain, we create a data governance matrix, which can be used by practitioners to design their data governance. The insights presented here have been informed by field research, and address an area that is of growing interest to the information systems (IS) research and practice community.
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Research and Advances Jan 1 2010

The Future of Digital Imaging

Traditionally, radiology is a support department that provides imaging services to other hospital departments. In this conventional framework, the primary concerns of a radiology department were how to enhance the productivity of imaging workflows. Most efforts have been made principally to remove unnecessary communications and thereby reduce report turnaround time. The introduction of information systems such as PACS (Picture Archiving and Communication System) and RIS (Radiology Information System) are typical examples of such efforts. Over the past decades, imaging technologies have advanced remarkably, and have led to the proliferation of digital imaging services. Many imaging solution providers are offering various off-the-shelf software programs at more affordable prices. Those programs are equipped with sophisticated imaging functions, and can easily manipulate the large amounts of image data generated from high-performance imaging modalities. As a result, the number of imaging centers providing diagnostic imaging services has grown considerably, and competition between them has intensified. In this evolving environment, enhanced productivity of imaging workflow is not sufficient to guarantee a competitive and successful imaging business. Rather, more diversified perspectives of customer satisfaction must be considered, and technological advancements must be leveraged for the quality and the competitiveness as well as the productivity of imaging services. In this article, we envision digital imaging services in radiology, with emphasis on the recent advancements in digital imaging technology and its future direction. Specifically, we focus on the four major issues prevailing in current imaging business practices: specialization, flexibility, reliability, and usability. We investigate the kinds of technologies pertaining to each issue, as well as the ways in which such technologies have enabled the invention of innovative services in diagnostic imaging practice.
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BLOG@CACM Oct 1 2009

The Netflix Prize, Computer Science Outreach, and Japanese Mobile Phones

The Communications Web site, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of Communications, we'll publish excerpts from selected posts. Greg Linden writes about machine learning and the Netflix Prize, Judy Robertson offers suggestions about getting teenagers interested in computer science, and Michael Conover discusses mobile phone usage and quick response codes in Japan.
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Research and Advances Oct 1 2009

Balancing Four Factors in System Development Projects

Introduction The success of system development is most often gauged by three primary indicators: the number of days of deviation from scheduled delivery date, the percentage of deviation from the proposed budget, and meeting the needs of the client users. Tools and techniques to help perform well along these dimensions abound in practice and research. However, the project view of systems development should be broader than any particular development tool or methodology. Any given development philosophy or approach can be inserted into a systems development project to best fit the conditions, product, talent, and goals of the markets and organization. In order to best satisfy the three criteria, system development project managers must focus on the process of task completion and look to apply controls that ensure success, promote learning within the team and organization, and end up with a software product that not only meets the requirements of the client but operates efficiently and is flexible enough to be modified to meet changing needs of the organization. In this fashion, the project view must examine both process and product. Often, tasks required for project completion seem contradictory to organizational goals. Within the process, managerial controls are applied in order to retain alignment of the product to the initial, and changing, requirements of the organization. However, freedom from tight controls promotes learning. The product also has contradictions among desired outcomes. Designers must consider tradeoffs between product efficiency and flexibility, with the trend in processing power leading us ever more toward the flexibility side. Still, we rage between conflicting criteria, with the advocates of a waterfall system development lifecycle (SDLC) usually pushing more for control aspects and efficient operations while agile proponents seek more of a learning process and flexible product. Regardless of the development methodology followed, project managers must strive to deliver the system on time, within budget, and to meet the requirements of the user. Thus, both product and process are crucial in the determination of success. To compound the difficulties, those in control of choosing an appropriate methodology view success criteria from a different perspective than other stakeholders. Understanding how different stakeholders perceive these factors impacting eventual project success can be valuable in adjusting appropriate methodologies. Our study looks at these relationships using well established instruments in a survey of IS development professionals to better clarify the importance of these variables in system project success and any perceived differences among different players in IS development (see the sidebar on "How the Study Was Conducted").
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Research and Advances Oct 1 2009

How Effective Is Google’s Translation Service in Search?

In multilingual countries (Canada, Hong Kong, India, among others) and large international organizations or companies (such as, WTO, European Parliament), and among Web users in general, accessing information written in other languages has become a real need (news, hotel or airline reservations, or government information, statistics). While some users are bilingual, others can read documents written in another language but cannot formulate a query to search it, or at least cannot provide reliable search terms in a form comparable to those found in the documents being searched. There are also many monolingual users who may want to retrieve documents in another language and then have them translated into their own language, either manually or automatically. Translation services may however be too expensive, not readily accessible or not available within a short timeframe. On the other hand, many documents contain non-textual information such as images, videos and statistics that do not need translation and can be understood regardless of the language involved. In response to these needs and in order to make the Web universally available regardless of any language barriers, in May 2007 Google launched a translation service that now provides two-way online translation services mainly between English and 41 other languages, for example, Arabic, simplified and traditional Chinese, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish (http://translate.google.com/). Over the last few years other free Internet translation services have been made available as for example by BabelFish (http://babel.altavista.com/) or Yahoo! (http://babelfish.yahoo.com/). These two systems are similar to that used by Google, given they are based on technology developed by Systran, one of the earliest companies to develop machine translation. Also worth mentioning here is the Promt system (also known as Reverso, http://translation2.paralink.com/), which was developed in Russia to provide mainly translation between Russian and other languages. The question we would like to address here is to what extent a translation service such as Google can produce adequate results in the language other than that being used to write the query. Although we will not evaluate translations per se we will test and analyze various systems in terms of their ability to retrieve items automatically based on a translated query. To be adequate, these tests must be done on a collection of documents written in one given language plus a series of topics (expressing user information needs) written in other languages, plus a series of relevance assessments (relevant documents for each topic).
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