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@ -85,18 +85,18 @@ Digital stewardship is the active and long-term management of digital objects to
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\section{Introduction}
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Although digital preservation is a young field, there are now more scholarship, tools, and resources that address the long-term stewardship\footnote{For the purposes of this paper, "digital stewardship" is defined as the active and long-term management of digital objects towards their robust preservation for and unencumbered access by future generations, inclusive of all subfields of labor and expertise previously defined among professional surveys and studies as digital curation, data curation, data management, digital archiving, digital preservation, and digitization. Digital stewards include data librarians, digital asset managers, digital archivists, and all manner of administrators who seek to align disparate digitization and digital preservation efforts.} of digital material than ever before. In recent years there has been a notable expansion of educational and training resources in particular, including workshops, symposia, conferences, and professional development curricula. However, as the 2015 National Agenda for Digital Stewardship asserts, "[g]enuine interest and motivation to learn about a subject cannot be taught in a workshop or training session; similarly, knowledge about standards and practices in an evolving field is best gained through direct, practical experience."\cite{1} In short, being an effective steward of digital material requires more extensive and specialized training than can be acquired through traditional means.
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What, then, makes a digital steward? Despite the acknowledgment that stewards must possess a particular skillset, there has not yet been sufficient scholarship performed to identify a competency profile for digital stewards, as exist in other professional communities. A competency profile succinctly articulates the specific skills, responsibilities, and knowledge areas required to practice in one's profession, and is therefore instrumental to setting training and education goals. Perhaps it is due to the field's relative youth that so many analyses of it have focused principally on the surrounding literature--most commonly surveys of graduate school curricula or job advertisements--rather than on the backgrounds and training of practitioners themselves. But as the amount of digital material entering libraries, archives, and museums worldwide continues to grow, developing successful training goals for the next generation of stewards is an increasingly vital pursuit.
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What, then, makes a digital steward? Despite the acknowledgment that stewards must possess a particular skillset, there has not yet been sufficient scholarship performed to identify a competency profile for digital stewards, as exists in other professional communities. A competency profile succinctly articulates the specific skills, responsibilities, and knowledge areas required to practice in one's profession, and is therefore instrumental to setting training and education goals. Perhaps it is due to the field's relative youth that so many analyses of it have focused principally on the surrounding literature--most commonly surveys of graduate school curricula or job advertisements--rather than on the backgrounds and training of practitioners themselves. But as the amount of digital material entering libraries, archives, and museums worldwide continues to grow, developing successful training goals for the next generation of stewards is an increasingly vital pursuit.
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The lack of any cogent competency profile for this field is significant because competency profiles are used in the creation of job ads and curriculum development, which in turn affects how the field and its practitioners succeed in and improve their profession. In spite of this, the Agenda singles out the National Digital Stewardship Residency (NDSR hereafter) as an especially successful training model due to the fact that it allows recent graduates to gain practical, hands-on experience in the field managing digital stewardship projects. Although measuring the long-term impact of this program on the field at large would be premature\footnote{Although it is not a longitudinal analysis, the Council on Library and Information Resources (CLIR) is at the time of writing conducting a cross-cohort assessment of the entire NDSR program in order to evaluate the significance of the residency experience for the residents and their host institutions, and to identify common success factors across the various residencies.\cite{2}}, the project descriptions created by host institutions for both current and former residents yield valuable information. Both the wide variety of projects and activities covered as well as the fact that they explicitly outline goals and responsibilities for each individual resident and project makes them ideal for determining the skillset and expertise required to successfully perform the professional duties of a digital steward.
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The authors developed a competency profile for digital stewards by using a three-pronged approach: 1) reviewing literature on the topics of emerging digital stewardship roles, responsibilities, expected practices, and training needs; 2) qualitatively analysing current and completed NDSR project descriptions, which outline project tasks and deliverables; and 3) quantitatively analyzing the results from a survey conducted of former and current Residents that identified the range and types of competencies required to successfully complete each project. The result is a profile of the skills, responsibilities, and knowledge areas that define competency in digital stewardship, which will create a clearer understanding of the on-the-job skills required of digital stewardship professionals in the hopes of informing future professional and curricula development in the field.
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The authors developed a competency profile for digital stewards by using a three-pronged approach: 1) reviewing literature on the topics of emerging digital stewardship roles, responsibilities, expected practices, and training needs; 2) qualitatively analyzing current and completed NDSR project descriptions, which outline project tasks and deliverables; and 3) quantitatively analyzing the results from a survey conducted of former and current residents that identified the range and types of competencies required to successfully complete each project. The result is a profile of the skills, responsibilities, and knowledge areas that define competency in digital stewardship, which will create a clearer understanding of the on-the-job skills required of digital stewardship professionals in the hopes of informing future professional and curricula development in the field.
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\section{About NDSR}
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NDSR was created by the Library of Congress, in partnership with the Institute of Museum and Library Services (IMLS), with the mission to "build a dedicated community of professionals who will advance our nation's capabilities in managing, preserving, and making accessible the digital record of human achievement."\cite{3} In its pilot year (2013-2014) NDSR matched ten recent graduates with mentors at ten cultural heritage institutions in order to develop, apply, and advance emerging digital stewardship practices and their own knowledge and skills in real-world settings. Since then, IMLS has granted funding to five additional NDSR programs among cultural heritage organizations throughout the country.
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The program involves competitive selection processes for both host institutions and residents. Host institutions are selected on the basis of criteria such as their ability to provide higher-level support and mentorship to residents, as well as the significance of their proposed projects. These projects can be as broad in scope as institutional assessments and policy writing, or as narrow as documenting the particular application of a software within a larger workflow. Applicants must be U.S. citizens or able to work in the U.S., as well as recent graduates of post-baccalaureate degrees.
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The program involves competitive selection processes for both host institutions and residents. Host institutions are selected on the basis of criteria such as their ability to provide higher-level support and mentorship to residents, as well as the significance of their proposed projects. These projects can be as broad in scope as institutional assessments and policy writing, or as narrow as documenting the particular application of software within a larger workflow. Applicants must be U.S. citizens or able to work in the U.S., as well as recent graduates of post-baccalaureate degrees.
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Although residents' salaries are paid through IMLS grant funds, they are regarded as regular employees by their host institutions and measures are taken to ensure that they are incorporated into the fabric of their institutions' workplaces. This is balanced by the fact that the residency is an apprenticeship program in which an important criterion for success is learning outcomes and job placement within the field after its completion. Each NDSR program supplements on-site support with workshops and trainings designed to foster professional growth. Residents are also strongly encouraged to publicize their projects through presentations and conference participation.
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Although residents' salaries are paid through IMLS grant funds, they are regarded as regular employees by their host institutions and measures are taken to ensure that they are incorporated into the fabric of their institutions' workplaces. This is balanced by the fact that the residency is an apprenticeship program in which important criteria are learning outcomes and job placement within the field after its completion. Each NDSR program supplements on-site support with workshops and trainings designed to foster professional growth. Residents are also strongly encouraged to publicize their projects through presentations and conference participation.
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\section{Literature Review}
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Competency profiles are a common way for information management professions to express educational and/or professional benchmarks. These include foundational professional concepts, information resources, research standards, lifelong learning expectations, and management principles and ethics, among other things. The American Library Association's "Core Competencies of Librarianship," for instance, establishes a baseline for those things that every "person graduating from an ALA-accredited master's program in library and information studies should know and, where appropriate, be able to employ."\cite{4} At least 16 affiliated or closely related professional organizations have adopted similar statements. \cite{5}
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@ -153,7 +153,7 @@ Personality requirements & 30 & Attention to detail \\
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The authors used a triangulated approach to create a profile of digital stewardship competencies. The literature review provided an initial sample of commonly used summary terminology for skills, knowledge areas, and responsibilities typically applied in practice. This informed the authors' distillation of 35 NDSR project descriptions through document analysis\footnote{Document analysis is a systematic procedure for analyzing and interpreting data generated from documents; in qualitative research, document analysis is often used to corroborate findings from other data sources such as surveys, interviews, etc.\cite{22}}, the results of which provided the authors the precise terminology with which to construct a survey instrument.
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Project descriptions for both New York residency cohorts\cite{23} and the second of the two cohorts in both Boston\cite{24} and Washington, D.C.\cite{25} were retrieved from each cohort's official website. Project descriptions for the initial Boston\cite{26} and Washington, D.C.\cite{27} residency cohorts were retrieved from the archived instances of those cohorts' official websites made available through the Internet Archive's Wayback Machine.
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Project descriptions for both New York residency cohorts\cite{23} and the second of the two cohorts in each Boston\cite{24} and Washington, D.C.\cite{25} were retrieved from each cohort's official website. Project descriptions for the initial Boston\cite{26} and Washington, D.C.\cite{27} residency cohorts were retrieved from the archived instances of those cohorts' official websites made available through the Internet Archive's Wayback Machine.
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\section{Research Methods}
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\begin{figure*}[!t]
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@ -164,7 +164,7 @@ Project descriptions for both New York residency cohorts\cite{23} and the second
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The authors used a social science research methodology called grounded theory\cite{28} to analyze the qualitative data (project descriptions). Research using grounded theory begins with a collection of qualitative data that the researcher then reviews and re-reviews. During this process, the researcher tags specific quotes, words, or phrases as evidence, and assigns them "codes" that represent larger ideas.\cite{29} As data is iteratively reviewed, these codes can be grouped into concepts and ultimately categories, which become the basis for a new thesis or theory. This differs from traditional qualitative methodology because it creates its theoretical framework inductively, rather than relying upon an existing one.\cite{30}
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The authors used this method to code for attributes expected of each resident. The authors used NVivo\footnote{Produced by QSR International: http://www.qsrinternational.com/product}, a proprietary qualitative data analysis software designed for researchers working with data that requires deep levels of analysis, in order to perform document analysis. NVivo was chosen because of its real-time version control, which was useful because the research team was geographically distributed. Two of the authors performed an initial blind review of the materials, using a predetermined codebook\footnote{A codebook describes and defines the codes for which the authors searched.} based on an initial sampling of the dataset and the literature review.
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The authors used this method to code for attributes expected of each resident. In order to do this, the authors used NVivo\footnote{Produced by QSR International: http://www.qsrinternational.com/product}, a proprietary qualitative data analysis software designed for researchers working with data that requires deep levels of analysis. NVivo was chosen because of its real-time version control, which was useful because the research team was geographically distributed. Two of the authors performed an initial blind review of the materials, using a predetermined codebook\footnote{A codebook describes and defines the codes for which the authors searched.} based on an initial sampling of the dataset and the literature review.
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Although the document analysis could provide the authors with a baseline understanding of the attributes that the residents were intended to develop, the authors also sought to examine how the projects had been borne out in practice. To accomplish this, the authors designed and implemented an online survey of current and past residents. By comparing the findings of the document analysis and the survey, the authors could assign quantitative weight to any similarities, differences, or unanticipated but necessary competencies.
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The authors used Qualtrics\footnote{Produced by Qualtrics: https://www.qualtrics.com/}, a proprietary research software used to enable online data collection through building survey instruments, because it was readily available via an institutional license, randomized question order, and anonymized participants down to the IP address.
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Initially, four survey invitations were sent to the list of participants using the Qualtrics email function, or "mailer." The mailer allows for complete anonymity in the data collection: the authors could not see who had completed or not completed the survey. This also allowed the authors to send out individualized, anonymous links, to separate respondents in bulk. When the survey was scheduled to close, there were still nine participants of the original thirty-five who did not partake. To get as close to a full dataset as possible, each author sent a follow-up email to four-to-seven participants. The link to the survey included in these emails was still anonymous and did not record IP, but was no longer unique to each recipient.
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Initially, four survey invitations were sent to the list of participants using the Qualtrics email function, or "mailer." The mailer allows for complete anonymity in the data collection: the authors could not see who had completed or not completed the survey. This also allowed the authors to send out individualized, anonymous links, to separate respondents in bulk. Nine current or former residents did not participate by the date on which the survey was originally scheduled to end. To get as close to a full dataset as possible, each author sent a follow-up email to four-to-seven participants to remind them of the deadline. The link to the survey included in these emails was still anonymous and did not record IP addresses, but was no longer unique to each recipient.
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The authors acknowledge several methodological issues with the data collection for this study. The first is that the authors are included in the dataset as participants. The most significant issue is that the authors effectively studied themselves; they designed, tested, and discussed the survey before deployment. As a result, they did not take the survey blind. Not only did this differentiate them from the rest of the participants, which could potentially skew the data, but it also introduced the potential for nonresponse bias\cite{31}. However, the authors randomized the questions to mitigate the latter issue. Although the authors recognize that participating in their own research is unorthodox, they felt that it was essential to equally represent all of the different NDSR projects, locations, and cohorts in the survey results. Moreover, because the authors all belonged to the same 2014-15 NDSR in New York cohort, those projects would not have been represented in the survey results. The authors felt that the benefits of including their responses outweighed the potential costs of excluding their responses from the dataset.
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The authors acknowledge several methodological issues with the data collection for this study. The first is that the authors are included in the dataset as participants. The most significant issue is that the authors effectively studied themselves; they designed, tested, and discussed the survey before deployment. As a result, they did not take the survey blind. Not only did this differentiate them from the rest of the participants, which could potentially skew the data, but it also introduced the potential for nonresponse bias\cite{31}. However, the authors randomized the questions to mitigate the latter issue. Although the authors recognize that participating in their own research is unorthodox, they felt that it was essential to equally represent all of the different NDSR projects, locations, and cohorts in the survey results were they to recuse themselves. Moreover, because the authors all belonged to the same 2014-15 NDSR in New York cohort, those projects would not have been represented in the survey results. The authors felt that the benefits of including their responses outweighed the potential costs of excluding their responses from the dataset.
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Another potential problem was the fact that fifteen of the participants took the survey before they completed their residencies. This introduced a possibility for survey bias \cite{33}. They might not have been able to answer the optional questions regarding 1) post-NDSR job functions, and 2) additional skills necessary to complete their residencies. However, since the current residents could answer all the required questions (they were more than halfway through their residencies during data collection), they were still included in the participant population.
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The authors' final concern was with sending individual emails to participants. This demystified some of the initial anonymity afforded by using the Qualtrics mailer. Some participants replied to these individualized emails, indicating they had already taken the survey (some even providing the date), or that they had not taken part but would do so shortly. The authors promptly deleted these emails permanently, and no records remain. Given the already small sample size, the authors felt that having as close to a complete dataset as possible was so impactful to the results that the follow-ups were necessary.
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The authors' final concern was with sending individual emails to participants. This demystified some of the initial anonymity afforded by using the Qualtrics mailer. Some participants replied to these individualized emails, indicating they had already taken the survey (some even providing the date), or that they had not taken part but would do so shortly. The authors promptly deleted these emails permanently, and no records of them remain. Given the already small sample size, the authors felt that having as close to a complete dataset as possible was so impactful to the results that the follow-ups were necessary.
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\section{Results}
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This study had two main outputs: the results of the document analysis (qualitative), and the results of the survey (quantitative). Through examining both, the authors could create a matrix of the competency areas vital to the National Digital Stewardship Residencies.
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\label{Figure 4.}
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\caption{Breakdown of technical skills code category}
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\end{figure*}
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Perhaps the most striking aspect of the data was the \textit{Technical skills} category. \textit{Technical skills} had the most mixed results of any category in the survey, which could be due in part to the fact that it had the highest number of granular competency areas (sub-codes). The result was a clear disparity in the distribution of responses per importance level. The outlier in \textit{Technical skills} with the lowest importance rating was \textit{Web archiving}, which drove down the overall importance found in Figure 3. \textit{Workflow enhancement} was also an outlier; it was rated as the most essential technical skill by a margin of seven responses.
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Perhaps the most striking aspect of the data was the \textit{Technical skills} category. \textit{Technical skills} had the most mixed results of any category in the survey, which could be due in part to the fact that it had the highest number of granular competency areas (sub-codes). The result was a clear disparity in the distribution of responses per importance level. The outlier in \textit{Technical skills} with the lowest importance rating was \textit{Web archiving}, which lowered the overall importance found in Figure 3. \textit{Workflow enhancement} was also an outlier; it was rated as the most essential technical skill by a margin of seven responses.
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\subsection{Optional Questions}
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After answering the required questions above, survey respondents were invited to answer three optional questions.
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\subsubsection{Quantitative}
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An optional question in the survey asked the participants whether or not their experience in NDSR was relevant to their current employment. Every participant answered this question, with 90\% (30 participants) saying yes, while 10\% (3 participants) answered no.
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An optional question in the survey asked the participants whether or not their experience in NDSR was relevant to their current employment. Every participant answered this question, with 90\% (30 participants) say yes, while 10\% (3 participants) answering no.
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\subsubsection{Qualitative}
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The last two questions in the survey were open-ended questions that asked participants for feedback in longer-form writing. The first question asked participants to identify any competencies not addressed in the survey. 11 of 33 (33\%) of respondents answered this question. The authors could not ascribe any particular pattern to these responses, however several of them further described a competency or competencies from the survey as applied to their specific project. The second question asked for any additional feedback or comments. 6 of 33 (18\%) answered the second question. These answers were not analyzed using the qualitative methods above due to the low frequency and disparate topics covered, some of which again answered the previous optional question.
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The last two questions in the survey were open-ended questions that asked participants for feedback in longer-form writing. The first question asked participants to identify any competencies not addressed in the survey. 33\% (11 of 33) of respondents answered this question. The authors could not ascribe any particular pattern to these responses, however several of them further described a competency or competencies from the survey as applied to their specific project. The second question asked for any additional feedback or comments. 18\% (6 of 33) answered the second question. These answers were not analyzed using the qualitative methods above due to the low frequency and disparate topics covered, some of which again answered the previous optional question.
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\section{Conclusions}
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Learning from the competency areas that were described in the NDSR projects and identified by residents as being especially important (i.e. achieving a surveyed modal average of 4 [Very important] or 5 [Essential]), a competency statement representing this profile could read as follows:
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\begin{quote}
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Effective digital stewards leverage their technical skills, knowledge of standards and best practices, research opportunities, communication skills, and project management abilities to ensure the long-term viability of the digital record.
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In order to accomplish this, they cultivate their skill developing and enhancing new and existing digital media workflows, managing digital assets, and creating and manipulating these assets' metadata. They commit to the successful implementation of these new workflows, standards, and best practices by reliably managing both project resources and people.
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In order to accomplish this, they cultivate their skill developing and enhancing new and existing digital media workflows, managing digital assets, and creating and manipulating these assets' metadata. They commit to the successful implementation of these new workflows by reliably managing both project resources and people.
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They maximize the impact of their professional practice by soliciting regular input from stakeholders both internal and external to their institutional setting. They articulate and document the standards and practices that address these needs by creating policies, professional recommendations, and reports, which requires that they maintain current and and expert knowledge of standards and best practices for metadata and data management in their respective sectors.
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To keep current and anticipate needs as they develop in these and other areas important to their field and their stakeholders, they conduct professional research in the forms of environmental scans, needs assessments and gap analyses, and surveys of emerging standards and best practices.
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They articulate and document the practices that address these needs by creating policies, professional recommendations, and reports, which requires that they maintain current and expert knowledge of metadata and data management standards in their respective sectors.
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Digital stewards are qualified to manage, preserve, and provide access to various new and/or challenging forms of media. They may also engage in, among other things: coding and scripting; digitization; hardware and software implementation; public outreach; and special media format management and migration.
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\end{quote}
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Finally, it is worth noting the fact that all residencies took place in the U.S.A., and consequently that this research is not international in scope. This presents an important area for future research, which might involve conducting a comparable study built on job descriptions culled from a variety of national contexts. Contrasting the results of such a study with the competency profile presented here would perhaps enable the construction of a stronger and more well-rounded profile overall.
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This research has implications for current and future digital stewards alike: The resulting profile can be used to guide graduate and professional development curricula, and training designed with this profile as its basis will focus on the skills most needed to be an effective digital steward. For instance, this study suggests that although specific technical skills are viewed as highly important in different settings, a much larger majority of projects required skills less bound to a particular technology or media, like documentation creation and workflow analysis. The high level of agreement regarding the importance of writing reports and communicating internally also bolster a need for digital stewards to not only possess a deep understanding of their field, but to effectively disseminate their work to others. This new profile illustrates the fundamental competencies that must be cultivated by digital stewards in order to succeed in the profession.
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This research has implications for current and future digital stewards alike: The resulting profile can be used to guide graduate and professional development curricula, and training designed with this profile as its basis will focus on the skills most needed to be an effective digital steward. For instance, this study suggests that although specific technical skills are viewed as highly important in different settings, a much larger majority of projects required skills less bound to a particular technology or media, like documentation creation and workflow analysis. The high level of agreement regarding the importance of writing reports and communicating internally also bolsters a need for digital stewards to not only possess a deep understanding of their field, but to effectively disseminate their work to others. This new profile illustrates the fundamental competencies that must be cultivated by digital stewards in order to succeed in the profession.
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\section{Supplementary Materials}
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The authors welcome and encourage others to extend and reproduce their study, and have made all research materials, including the survey instrument and data, freely available at the following: \url{https://osf.io/xfc26}
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The authors welcome and encourage others to extend and reproduce their study, and have made all research materials, including the survey instrument and data, freely available at the following URL: \url{https://osf.io/xfc26}
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\bibliographystyle{unsrt}
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\bibliography{2016-10-03_iPRES_NDSRLongPaperBiblio}
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Reference in New Issue