بررسی عوامل به اشتراک گذاری داده ها علمی : درک انگیزش برای انتشار داده های پژوهش
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|5106||2013||13 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 12314 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
|شرح||تعرفه ترجمه||زمان تحویل||جمع هزینه|
|ترجمه تخصصی - سرعت عادی||هر کلمه 90 تومان||17 روز بعد از پرداخت||1,108,260 تومان|
|ترجمه تخصصی - سرعت فوری||هر کلمه 180 تومان||9 روز بعد از پرداخت||2,216,520 تومان|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Government Information Quarterly, Volume 30, Supplement 1, January 2013, Pages S19–S31
The research community is working to create new capabilities to share data and to deal with issues of data quality, standards, and protection, and ethical and responsible use of shared data. These issues have been found to influence the willingness of researchers to publish data created during the course of their research. We use the results of a survey conducted by the working groups of the DataONE project to present a new understanding of challenges to the development of global data collections and preservation by systematically examining the determinants of the researchers' likelihood to openly publish research data. This study found two key determinants affecting researchers' willingness to publish their data. First is data management in terms of data management skills and organization support. Second is the acknowledgement of the data set's originator in terms of appreciation and legal and policy requirements. This study also found that the impact of the significant determinants is contingent on the amount of data to be published. Finally, this study calls for further investigation to ascertain the relationship of data management and data quality, and systematic investigation on the roles and responsibility of government within these global data preservations.
Advances in computing, information and communication technologies produce dramatic and significant impacts on scientific research, making them increasingly data intensive and collaborative (Hey et al., 2009 and Tenopir et al., 2011). The rapid advances in computing capabilities also provide useful tools in manipulating and exploring massive data sets (Hey et al., 2009 and Savage and Vickers, 2009). Recognizing the magnitude and significance of digitalization and data-intensity in scientific research, in 2007, NSF solicited a proposal entitled Sustainable Digital Data Preservation and Access Network Partner (DataNet)2 to trigger development of the necessary systems of data preservation by engaging the research community and other interested stakeholders at the frontiers of computer and information science. Two projects were selected to create a set of exemplar national and global data research infrastructure organizations (called the DataNet Partners) that would provide unique opportunities to communities of researchers to advance science and engineering research and learning. DataONE and The Data Conservancy were established to build a robust national and global digital data framework. DataONE, short for “DataNet Observation Network for Earth”, is a virtual federated database to support universal access to earth and environmental data (www.dataone.org). The Data Conservancy (DC) is intended to collect, organize, validate, and preserve data for future reuse (www.dataconservancy.org). Open data initiatives for preservation of research data such as DataONE and Data Conservancy could encourage a wealth of scientific opportunities with less effort and fewer resources. Having access to such data, data in some cases collected over a lifetime, researchers could creatively innovate from archival data sets, promote new discoveries from old data sets, and connecting new meaning from existing research data sets (Nelson, 2009). Researchers could efficiently create more opportunities without the burden of data collection and repetition of efforts. As such, with an increase in the importance of the open data initiative, the role of data sharing becomes more important (Tenopir et al., 2011). Historically, access to and sharing of research data sets was part of collegiate tradition (Stanley & Stanley, 1988), operationalized through one-to-one personal means. The act of sharing data sets was regarded as a privilege among trusted colleagues based on mutual interest and respect (Kaye, Heeney, Hawkins, de Vries, & Boddington, 2009). A researcher seeking access to a data set would begin by locating the data and the owner, initiate a relationship, build trust, respect and mutual interest, and create a collaborative enterprise in the form of shared data sets. On the other hand, the proliferation of efforts to create global data preservation, to enable data sharing and reuse, challenges the generally accepted data sharing practice and raises new uncertainties and concerns for researchers regarding methods of sharing research data sets with the public. This paper uses the survey response conducted by the Usability and Assessment and Sociocultural Working Group of DataONE project.3 The objective of the survey is to understand and assess the current data sharing practices (Tenopir et al., 2011). The survey results provide an assessment of the perceptions of the barriers and enablers of data sharing that a federated data repository such as DataONE needs to consider in building the system. Through the understanding of the barriers and concerns inhibiting the willingness of researchers to publish their data, DataONE could design their project to provide secure but flexible infrastructure, policies and best practices that would help to build researchers' confidence in data sharing (DataONE, (n.d.) and Tenopir et al., 2011). In the natural sciences, a number of researchers have found that the existence of basic setups for scientific data sharing, such as technical, organizational and legal conditions, are necessary but do not automatically convince researchers to engage in data sharing practices. Extant literature asserts that data sharing practices at present are minimal, with researchers more likely to withhold their data than to share it publicly (Rodriguez, 2009 and Tenopir et al., 2011). Building from this assertion, this research focuses its analysis on the supply part of the data sharing process, attempting to understand the determinants of individual researchers' motivation, factors that may convince individual researchers to publish their research data, particularly in earth and environmental science. In this regard, this paper does not consider the challenges facing the users in accessing, using, and extracting data from particular open data initiatives. Existing literature has discussed at length the challenges of data publication in open data initiatives, for example, Reichman, Jones, and Schildhauer (2011), Tenopir et al. (2011), Zimmerman, 2007 and Zimmerman, 2008, Nelson (2009), Piwowar and Chapman (2010), and others. Furthermore, a limited number of studies have focused on the role of the researchers' motivation and intentions for data publication using bibliometric measure (Piwowar & Chapman, 2010). On the other hand, the matter of how challenges affect the researchers' motivation to publish their data has received little systematic attention. This research was designed to contribute greater understanding of the behavior in publishing research data by correlating the challenges to the propensity of researchers to openly share their data. Using the survey response from DataONE, this paper will address two main research questions: 1) what are the critical challenges facing individual researchers in publishing their research data openly to the public and 2) to what extent do these challenges influence the propensity of researchers to openly share their data sets? In accordance with the research objectives and questions, the rest of the paper is organized as follows. Section 2 will outline the theoretical background, focusing on the challenges for researchers to publish research data sets, and subsequently propose the model of the determinants in sharing research data. Section 3 briefly explains the research design and methodology used in this study. In accordance to the objective, we equate data owner as the researchers/initiator who initiate and conduct the research the first time. Limitation of such assumption is discussed in the implication section. Section 4 presents the findings and Section 5 provides discussion highlighting the findings' implications on policy for open data initiatives and, finally, Section 6 provides concluding remarks.
نتیجه گیری انگلیسی
NSF's vision of global scientific discovery through global data preservation and access entails major challenges. These challenges rest on human aspects as well as the new methods, management structures, and technologies. Achieving the above vision rests in large part on the researchers' willingness to contribute to this vision by sharing their data. This research study provides a preliminary analysis of the determinants of the likelihood of researchers to publish their research data sets online. Survey results were analyzed using descriptive and inferential statistics. The analysis identified two key determinants for sharing research data sets. Each of the determinants is supported by two challenges, namely: 1) data management in terms of skill and organizational involvement, and 2) acknowledgement in terms of legal and policy requirements and acknowledgement to the data set's owner. The importance of data management to ensure open publication of data manifests not only in the significance of data management skills, but also in terms of organizational involvement to provide support for data management. Data management skills and support for data management are necessary elements for ensuring data quality. The second key determinant found is the significance of proper attribution to data set owners. The importance of attribution in this study manifests in various forms of articulated acknowledgement of the data owners, such as opportunities for collaboration, co-authorships, formal recognition, and proper citation. Equally important are legal regulations and policies to support data re-use and attribution. This finding highlights the significance of creating new capabilities to share data and to deal with the issues of sharing data. The capability of researchers to manage their data sets and deal with the issues of data quality, standards, and protection, in addition to ethical and responsible use of shared data will significantly influence their propensity to share their data.