This article reports the author's recent research in developing a holistic model for various levels of digital library (DL) evaluation in which perceived important criteria from heterogeneous stakeholder groups are organized and presented. To develop such a model, the author applied a three-stage research approach: exploration, confirmation, and verification. During the exploration stage, a literature review was conducted followed by an interview, along with a card sorting technique, to collect important criteria perceived by DL experts. Then the criteria identified were used for developing an online survey during the confirmation stage. Survey respondents (431 in total) from 22 countries rated the importance of the criteria. A holistic DL evaluation model was constructed using statistical techniques. Eventually, the verification stage was devised to test the reliability of the model in the context of searching and evaluating an operational DL. The proposed model fills two lacunae in the DL domain: (a) the lack of a comprehensive and flexible framework to guide and benchmark evaluations, and (b) the uncertainty about what divergence exists among heterogeneous DL stakeholders, including general users. The World Wide Web, along with advanced computation technologies, catalyses digital library (DL) research and practices. The past decade saw an exponential increase in the number of ongoing and completed DL projects. However, compared with the growing number of DL projects, the overall quality of DLs is insufficiently studied and reported (Chowdhury & Chowdhury, 2003; Goncalves, Moreira, Fox, & Watson, 2007; Isfandyari-Moghaddam & Bayat, 2008; Saracevic, 2000; Xie, 2006 Xie, , 2008 . "Evaluation is more conspicuous by its absence (or just minimal presence) in the vast majority of published work on digital libraries…So far, evaluation has not kept pace with efforts in digital libraries" (Saracevic 2000 p. 351). In addition to the quantity issue (i.e., not every DL project has been evaluated, and not every project with evaluation has its entire DL aspects covered), the quality of DL evaluation is problematic. Evaluation approaches and criteria vary among the existing studies. It is hardly possible to benchmark evaluation findings. Furthermore, the majority of the studies adopt traditional information retrieval (IR) and Received September 8, 2008; revised May 27, 2009; accepted July 27, 2009 © 2009 ASIS&T • Published online 13 October 2009 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/asi.21220 library evaluation approaches and criteria for examining common features (e.g., information accuracy, interface ease of use). Few metrics reflect unique DL characteristics, such as variety of digital format. And few address the effects of a DL at higher levels, including the extent to which a DL fits into or improves people's daily work/life (Bearman, 2007; Saracevic, 2000) . Having acknowledged the lacunae, a number of professionals and scholars have been seeking a valid DL evaluation framework, suggesting what should be evaluated, how a DL should be evaluated, and who should evaluate it. In 1998 (July/Aug), D-Lib Magazine published a report by the Computer Science & Telecommunication Board, National Research Council, within which the following conclusion is heuristic to DL evaluation: "Reaching a consensus on even a minimum common denominator set of new statistics and performance measures would be a big step forward …." Similarly, Borgman (2002) commented: "The digital library community needs benchmarks for comparison between systems and services…We also need a set of metrics for comparing digital libraries"(p.10). This article reports a three-stage research of developing a holistic model for DL evaluation. It starts with a summary of general background, literature review, and research objectives followed by a detailed methodology descriptions. The Finding section reports major results with a focus on illustrating the proposed model along with summarizing important criteria perceptions among heterogeneous stakeholder groups for different levels of DL evaluations. Finally, the Discussion section suggests implications of the research to DL innovation and directions for future studies. The review of previous studies is focused on what criteria and framework have been used in the DL evaluations. DL evaluation criteria and measures employed or proposed in existing literature can be essentially grouped at six levels, namely, content, technology, interface, service, user, and context, as suggested by Saracevic (2000) . Despite the significance of digital content evaluation (Xie, 2006) , this body of research seems to be a weaker area. Few studies report their DL evaluation at this level. Essentially, criteria are employed to assess four types of digital content: digital object, metadata, information, and collection. Among these four types, digital objects seem to be the unique type to DLs and, hence, be evaluated under DLspecific criteria, such as fidelity (Kenney, Sharpe, & Berger, 1998) and suitability to original artifact (Goodrum, 2001; Jones & Paynter, 2002) . The remaining three types have been evaluated with conventional criteria, including accuracy, clarity, cost, ease of understanding, informativeness, readability, timeliness, and usefulness. Additionally, scalability for user communities (Kengeri, Seals, Reddy, Harley, & Fox, 1999; Kenney et al., 1998; Larsen, 2000) tackles a crucial issue in DL innovation, which involves more diverse user communities with various backgrounds and changing needs. Digital technology evaluation has two foci: hardware and software. The latter uses primarily conventional relevancebased effectiveness measures, while several studies adapt them to fit into digital and hypermediated circumstances (Hee,Yoon, & Kim, 1999; Salampasis & Diamantaras, 2002 Digital service evaluations examine how well a DL can provide additional on-demand (especially human or humanlike) assistance to users. Lankes, Gross, & McClure, (2003) identified six criteria for evaluating digital reference, namely, courtesy, accuracy, satisfaction, repeat users, awareness, and cost. Some other criteria from traditional library face-to-face service evaluations (e.g., accessibility, courtesy, empathy, reliability, difference before and after service intervention, gaps between expectation and perception) can also be found in digital services. Additionally, a couple of criteria specifically fit digital reference transactions featuring time lag and invisibility in communication, such as responsiveness (Cullen, 2001; Lankes et al., 2003; White, 2001 ) and user's control (White, 2001 ). Evaluations at the user level indirectly measure DLs through examining attributes of their users, such as changes of their information behaviors, benefits as to users' tasks in hand, or later on research, work, and life. So far, most evaluations at this level focus on the use/usage and benefits of individual searching and learning. Frequently used user-level criteria include session time, accuracy of task completion, acceptance, use/intent to use, and satisfaction. In practice, DL evaluation at the context level is another weak area, regardless of its importance as pinpointed by several leading scholars (Bishop, 1999; Marchionini, 2000; Saracevic, 2000) . To date, only very few evaluations have examined to some extent the contextual effects of DLs, including copyright compliance (Jones, Gay, & Rieger, 1999) and preservation and spreading of culture (Places et al., 2007) . In addition, sustainability was proposed to measure the extent to which the augmentation of a DL could be secured without eventually losing its vitality (Blixrud, 2002; Lynch, 2003) . In sum, DL evaluations have been largely focused on interface and user levels. Content and context levels receive little attention. Moreover, most of the criteria used are merely borrowed from the domains of traditional library and information retrieval system. There lacks DL-specific evaluation measures for examining, for example, how well DL information and collections are integrated with each other, to what extent different DLs are compatible with each other, how well DLs support social/group interaction among heterogeneous users utilizing hypermedia information, and whether there are any changes in users' daily work and lives that are associated with DL applications. People have been working on developing frameworks/models for benchmarking evaluations. Among these studies, only a few provide criteria for multiple dimensions of DL evaluation: Kwak, Jun, & Gruenwald's (2002) Not only should attention be given to what evaluation frameworks are proposed, it is also vital to know how they are developed in order to see whether a given framework is valid and transferable to different settings. Among the handful of DL evaluation frameworks, the majority of them are constructed via consolidating experts' opinions, reviewing existing DL constructs, projects, and evaluation criteria, or relying on the researchers' own perspectives. The validity of these frameworks is weakened by either the This research aims to develop a holistic DL evaluation model with a set of criteria covering core DL aspects and embracing perspectives from heterogeneous stakeholders, including DL end users. Two theoretical frameworks shed light on the research. One is Saracevic's (1996 Saracevic's ( , 1997 Saracevic's ( , 2000 stratified information retrieval (IR) model; and the other is Marchionini's (2000 multifaceted approach for assessing DL impacts. The stratified model views an IR system, including a DL, as an entity containing components at different levels: content, technology, interface, user, service, and context. The system functions through interactions among the stratified levels. The model depicts essential components of a DL in a comprehensive but also flexible manner. In his conceptualization paper for DL evaluation, Saracevic (2000) describes the stratified layers as the "Contexts for Evaluation" (i.e., social, institutional, individual user, interface, system, and content). In other words, although the model was originally proposed for traditional IR systems, it should be still fitting to guide DL research. While the stratified model outlines what can be evaluated, Marchionini's multifaceted DL approach is a complementary framework, suggesting how quality data can be collected, analyzed, and reported. Having tackled the complexity of DL development with diverse people and activities, the multifaceted approach suggests DL evaluations to be conducted through taking different viewpoints, using different approaches and from different dimensions, then integrating data, and finally reaching a conclusion. Included are the stratified and multifaceted approaches that form enlightening guidelines for developing a holistic DL evaluation model in which diverse people's perspectives towards all kinds of levels. The main purpose of this research is to develop such a holistic DL evaluation model. The model should have the following two meanings in terms of being holistic: (a) cover all DL levels, including digital content, technology, interface, service, user, and context; and (b) bring in perspectives from as many diverse groups of stakeholders as possible. Three research objectives are as follows: • To identify what criteria can and should be used in DL evaluation and construct a preliminary set of criteria for different DL levels through examining existing studies and eliciting DL experts' opinions. • To examine, at a large scale, how important each criterion in the preliminary set is in the perspectives of more diverse stakeholder groups, and build a model in which criteria perceived to be "important" are presented in a meaningful manner. • To test the validity of the model when it is applied to extant DL use and evaluation. To develop the holistic DL evaluation model, I applied a hybrid research approach combining both qualitative and quantitative methods. Specifically, a three-stage research approach (see Figure 1) -exploration, confirmation, and verification-was devised to identify as many and as various as possible of criteria that could and should be used in DL evaluation, and eventually to construct a valid model with the inclusion of important criteria perceived by various stakeholders. These three stages are conceptually and methodologically interrelated. During the exploration stage, a representative literature review and a semistructured interview were employed to examine what criteria could and should be used in DL evaluation. Then, the criteria identified from the exploration stage were embedded into an online questionnaire during the confirmation stage. More respondents from more heterogeneous DL stakeholder groups were asked to rate the importance of each criterion. The author constructed the holistic model by using descriptive and inference statistical techniques. Finally, in the verification stage, the validity of the model was tested through stakeholders' interaction with a real DL. The selection of the research methods is carefully planned with a consideration of being appropriate to corresponding research objectives as well as maximizing the strengths of each method. For example, a semistructured interview has strength in eliciting a person's tacit thoughts, particularly when he or she pertains rich knowledge on the topic (Lindlof, 1995) , and, thus, is appropriate for exploring as many as possible experts' perspectives on what criteria are important to DL evaluation, an area not so well explored. Meanwhile, an online survey is more suitable for statistically confirming the significance of these criteria through perspectives from a larger amount of and more diverse groups of DL stakeholders. Additionally, as a research method with both qualitative and quantitative nature, open-ended questions in the survey can be used to enrich the criteria set. I reviewed the literature using the following procedures: 1. Identified and selected related sources that are likely to cover DL evaluation literature. 2. Constructed search statements and composed search queries to retrieve DL evaluation literature. 3. Selected papers from retrieved sets that cover DL evaluation frameworks, methodologies, or criteria. 4. Summarized the frameworks, methodologies, and criteria from the papers selected. Considering the breadth of DL influences, Web of Science, a multidisciplinary database that indexes research articles from leading journals across disciplines, was also examined to expand the search scope to plausible DL application areas (e.g., education, health). Search query composition. The primary search statement was formed by a Boolean logic combination of (digital library or electronic library) and (evaluation or assessment or performance or outcome). However, specific search queries varied among databases depending on a given database's rules on search queries. Digital repository, as an emerging form for collecting, managing, and providing access to digital contents, was not used in the search query because it is too narrowly focused (Basefky, 2009) and has different boundaries than DL (Bearman, 2007) . Additionally, it has been much less addressed in literature (a search in Web of Science on June 3, 2009 brings up 2,301 records for digital library/libraries with 1990 as the earliest publication year while merely 61 records for digital repository/repositories with 2001 as the earliest publication year). Meanwhile, the combination of "performance" and "outcome" with "evaluation" and "assessment" using the Boolean OR operator is simply for expansion of literature search scope. Paper selection. The papers selected for the review were restricted to those studies with representative analyses or achievements on frameworks, methodologies, or criteria for DL evaluations. Eventually, 155 papers were selected as meeting the requirement. The justification for the selection is simply associated with the research objective, that is, to develop a holistic model for DL evaluation. Although the methodologies and frameworks primarily served as reference points with which this research was associated, the criteria identified from the literature were used in the later card sorting (CS) during the interviews, and for the discussion of new DL evaluation criteria identified from this research. of the literature review-criteria lists that were used to develop an interview protocol in the succeeding research step-can be found at this persistent URL: http:// hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17104. Interview participants. A purposive sampling method was employed to select nine DL experts who were likely to provide insightful thoughts about DL quality and performance indicators. Three groups of experts (i.e., administrators, developers, and researchers) with three in each group participated in the research. These expert stakeholders were recruited from the library school and the libraries at a university on the east coast of the United States. Interview participant eligibility required substantive knowledge of DLs and adequate experience developing, administering, or conducting research on DLs. Specifically, an eligible DL researcher should at least have published one paper or taught one course on DL. An eligible DL developer should have experience with designing or implementing at least one DL project. And an eligible DL administrator should be the one whose primary role is to oversee the implementation of at least one DL. Having acknowledged the limitation of selecting the participants from a single institution, I made considerable efforts to increase the multiplicity of viewpoints by soliciting participants with varied backgrounds. For example, while one DL researcher participant was an expert on interaction in DL library, the other two specialized in technological and cultural aspects, respectively. Additionally, I employed two strategies to help the participants elaborate more DL evaluation criteria: (a) employing background-specific questions at the beginning as probes for getting them to think more about DL qualities later and (b) using the criteria identified from the literature in the CS as samples for eliciting more participants' own criteria. Data collection. During June to October 2005, semistructured interviews were conducted to collect the nine DL stakeholders' perspectives on DL criteria. I interviewed each participant once for about an hour. At the beginning of each interview, he or she was asked to read and sign an interview consent form giving permission to be interviewed and to be audio-taped. The nine interview questions were asked in the same order to minimize instrument bias (the instrument is available at http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD. 17104). After a couple of background-related questions were specific questions for eliciting participants' perspectives on the criteria that could, or should, be used in DL evaluation. Each of the DL criteria question targeted a given DL level, ranging from content, technology, interface, service, user to context. For each DL level, in addition to the question-answering (QA) during which the interviewees spoke freely about DL evaluation criteria, a card-sorting (CS) technique was employed for them to rank several criteria that were preselected from the literature review results, based upon their occurrence frequency. The number of CS criteria for each level was restricted to 8-11 for manageable and meaningful results as inferred by an earlier pilot study. All participants sorted these cards based upon their perceived importance of each criterion to evaluation at the DL level. When sorting the cards, they were encouraged to refer to the back of a card for the definition of the criterion. Data analysis. Qualitative data analysis software, Atlas.ti, was used to develop a coding scheme and to assign appropriate codes to meaningful narratives. The initial coding scheme was developed by incorporating results from the literature review and a pilot interview, and then it was applied in axial coding the nine interview transcripts. The scheme was organized into seven categories: one for DL constructs and six for the DL levels, as suggested by Saracevic in 2000. An open-ended coding technique was applied to identify new categories that were not included in the initial scheme. After the first coding run was finished, clean-ups were performed to remove less frequently mentioned criteria or to merge them to the closest ones if needed, in light of Auerbach and Silverstein's (2003) methodological suggestion. To ensure coding consistency across transcripts, a set of rules was developed to guide the coding process. Additionally, the coder (i.e., myself) executed iterative codingrecoding reliability checking until two consecutive coding runs for each category reached a 70% or higher consistency rate. The coder repeated the coding runs independently (i.e., without referring to earlier coding results but with the same original coding scheme and with two consecutive coding runs apart from each other for at least 1 month). Additionally, the recoding processes were carried out only for those categories with less than 70% consistency rate against the previous run. Eventually, four coding runs were executed before all reached the reliability threshold. Then, I examined frequency distribution patterns of all codes (criteria) within and among the six DL evaluation levels as well as among the three stakeholder groups. Meanwhile, a comparison between the code frequencies and the corresponding CS results was made to examine internal reliability within individual interviewees. I also sent the data analysis results back to the interviewees for "member checking" and received no requests for major changes. The criteria in the final list would be selectively included in the succeeding survey questionnaire for further confirmation by more respondents from more heterogeneous DL stakeholder groups. the other four stakeholder groups were recruited from various academic and professional listservs. Table 1 provides a brief description about the listservs. The academic listservs tended to have more DL researcher members, and the professional ones might have more DL administrator, developer, and librarian participants. Meanwhile, the rationale for the sampling frame for general users was that faculty and students from those institutions tend to have more opportunity of using and becoming familiar with DLs and, thus, have more insightful perspectives on the importance of evaluation criteria. These sampling frames were merely used to identify and recruit various stakeholders. The final stakeholder affiliation in the data analysis was determined by the participants' self-reporting in the survey. Data collection. During April to May 2006, an online survey recorded participants' perceptions on important DL evaluation criteria. A draw for digital devices and thank-you gifts were employed as incentives to increase response rate. A large percentage of survey respondents (87%) entered their names, as well as mail and e-mail addresses for receiving the gifts and result of the draw. The personal information suggests a low possibility of duplicate responses (i.e., very few people filled in the survey more than once). The questionnaire was divided into seven sections, with one for demographics, and the other six for the importance ratings on the criteria identified from the exploration stage with either high or least importance perceptions by the interviewees. Each importance-rating section corresponded to a DL level, as described by Saracevic (2000) . Figure 2 demonstrates a sample survey section that shows the header and the first several questions. The header provided the explanation on the given level DL evaluation and the instruction on how to take the survey, including using a mouse-over action for the definition of a criterion (see the small box on the left of Figure at the end of the section. The 7-point Likert scale ranged from 1 (insignificant at all) to 7 (extremely significant). "No opinion" option was also provided. In addition, alert popup windows were used to ensure that the participants finish all the sections and to prevent missing values. Progress bars indicated the finished/unfinished portion of the survey. SPSS was used to analyze the data. Means and standard deviation were compared for a list of important criteria. Additionally, the one-way ANOVA test, a widely adopted statistical technique for examining differences in the mean values of a single variable associated with various groups, was conducted to examine inter-group divergence in perception of criteria importance (the single variable in this research context).ANOVA has strength in examining whether group means differ significantly and is weak in discovering which group means differ from one another. Therefore, wherever the inter-group divergence was identified, the posthoc technique was employed to further identify the groups contributing to the divergence. The large sample size in the survey increases the robustness of the test departing from normality. The employment of the parametric test should not seriously violate the assumptions, as Glass, Peckham, & Sanders's (1972) finding suggests. Digital library system. The validity of the model constructed was tested through actual DL use. The Rutgers University Library (RUL) Web site (http://www.libraries. rugers.edu/) was the operational DL system used for testing. The choice was made because of the following two reasons: (a) the ease of getting experiment participants representing various and diverse stakeholder groups and (b) the likelihood of experiment participants' familiarity with the system as a benefit of being able to furnish more experience-based and knowledge-based perspectives on important criteria for DL evaluation. As pointed out by several DL scholars (e.g., Borgman, 1999; Saracevic, 2000) , thus far, there is no agreed-upon DL definition. The chaotic situation is also related to a debate regarding whether a library Web site can be considered a DL. In my viewpoint, a university Web site could be one type of DL for the following two reasons. First, by comparing typical features on a representative library Web site (e.g., RUL) with the DL definition proposed by the Digital Library Federation (see Table 2 ), one may see that the former is essentially comparable with the latter. Specifically, the RUL site can be seen as the libraries' Web presence because the site contains a clear statement about the organizational mission, a well-defined user community, and a presentation of its organizational structures and resources. Meanwhile, it provides RU students, faculty, and other RUaffiliated community members with readily and economically available resources, including licensed databases and locally developed, rich digital collections (e.g., New Jersey Digital Highway) that are selected, organized and integrated, as well as maintained by specialized staff. From the site, faculty Digital libraries are organizations that provide the resources, including the specialized staff, to select, structure, offer intellectual access to, interpret, distribute, preserve the integrity of, and ensure the persistence over time of collections of digital works so that they are readily and economically available for use by a defined community or set of communities. and students can not only search for physical library collections but also access digital works. Meanwhile, they may readily seek online intellectual assistance from specialized librarians. Second, taking full advantage of network technologies, DLs gain their strengths by integrating distributed resources from different digital repositories. A DL does not necessarily require all its collections reside in a single local server. Furthermore, considering the enormous investments of a library on licensing commercial full-text e-resources and linking them to local systems, it is unfair to isolate all these resources from the Web site, which usually serves as the forefront of the library going digital. It is the integration of the Web site and the resources that makes a digital version of the library. During the summer of 2006, heterogeneous groups of stakeholders were recruited as experiment participants. The groups comprised general users, researchers, librarians, administrators, and developers. Whereas general users were recruited onsite in the two libraries (humanities and social science library and science and engineering library) in a university on the east coast of the United States, the latter four groups of participants were solicited through mailing lists of the university libraries and individual e-mail communications. As for the on-site recruitment, the author approached potential participants when they came to the library and started to use the library Web site. While the selection criteria for the groups of administrators, developers and researchers remained the same as the ones for the interview, the librarians were reference team members in the university libraries whose primary duty was to use the Web site to help and guide library users in finding information and library collections. These experiment participants were asked to prepare a search topic for locating relevant information via the library Web site. Data collection. These participants' perceptions about important criteria for the library Web site evaluation were collected through a post-search questionnaire after they finished searching the site. The questionnaire included all criteria from the holistic DL evaluation model, plus a few that were perceived to be least important by the survey participants. The inclusion of the least important criteria serves as an additional examination on whether these criteria are still considered to be the least important in the real DL-use setting. For each criterion, the participants were asked to read a statement about the criterion, and then check off the most appropriate answer in relation to their searching experience with the library Web site. A sample statement was: "Digital interface should be designed in a way that its essential elements (e.g., color, layout, font, background, terminology use) are consistent across sections and pages." The participants could select any of the three options, that is, "not applicable to my case," "I don't know", and importance rating on a 6-point Likert scale from 1 (least important) to 6 (most important). In addition to the perceived importance rating on the preselected criteria, the participants were also encouraged to enter in open-ended sections for perceived significant features on the site that had helped (or hindered) them in the task implementation. They were encouraged to pay special attention, while searching, to information, interfaces, and various functions on the site rather than those provided by off-site commercial databases licensed by the libraries. Data analysis. Again, SPSS was used to analyze the distribution patterns of the participants' importance ratings and to identify group differences among the stakeholders. The participants'"I don't know" answers were treated as missing data because they had no meaning on the importance of a criterion. Their "not applicable to my case" answers were coded as zero, and they were included in the frequency analysis, but not in the descriptive and inference analyses (ANOVA), because the inclusion could bias the mean score and enlarge the standard deviation (SD). Besides, these answers had totally different meanings from the importance ratings. The results were compared with the ones from the confirmation stage for examining whether the important criteria from the confirmation stage were still perceived to be important when DL stakeholders interact with the operational DL and whether the inter-group differences still held. The Findings section reports demographic data of the interview, survey and experiments participants, the similarity and divergence of their perceived most and least important DL evaluation criteria, and the proposed holistic DL evaluation model in terms of the similarity and divergence. The interview participants-exploration stage. The author interviewed nine DL stakeholders, including three DL administrators (IA1, IA2, and IA3) and three DL developers (ID1, ID2, and ID3) from the libraries of a university on the east coast of the United States and three DL researchers (IR1, IR2, and IR3) from the Library and Information Science Program at the same institution. The survey participants-confirmation stage. In total, 434 survey participants finished the survey, of which the data of 431 were usable. Of these 431 participants, 159 (37%) self-reported their primary roles as librarians and 158 (37%) considered themselves general users. These two stakeholder groups constituted 74% of the total survey response. Meanwhile, the DL researchers, developers, and administrators numbered 53 (12%), 36 (8%), and 25 (6%), respectively. The difference in the group sample size is probably associated with population variance. Usually, the numbers of DL administrators, developers, and researchers are smaller than those of librarians and users. About half of the survey participants (220, 51%) were 30 to 49 years old, 93 (22%) were over 50, and 118 (27%) were 20 to 29 years old. The gender distribution was 167 (38.7 %) male and 264 (61.3%) female and was almost equally distributed among the four stakeholder groups except for the librarians. The librarian group had more females (114, 72%) than males (45, 28%). In terms of the highest education level achieved, the majority of participants held graduate (308, 71%) or doctoral degrees (100, 23%). Only 23 (5%) had baccalaureate or lower degrees. The skewed education level might be associated with the sampling frames of university settings for users and of the academic and professional listservs for the other four groups who are more likely to hold higher degrees. The subject backgrounds showed 209 (48%) for social sciences, 130 (30%) for sciences, 79 (18%) for humanities and arts, and 13 (3%) for others. Most survey participants (314, 73%) had been searching online for more than 3 years. The survey also attracted overseas participants. Among 367 (85%) participants who reported their nations, 310 (85%) were from the United States, and 57 (15%) were from 21 other countries, including China (16), United Kingdom (7), Germany (3), Greece (3), Spain (3), New Zealand (3), India (2), Egypt (1), Finland (1), Italy (1), Japan (1), Kenya (1), Korea (1), Mexico (1), Sweden (1). The experiment participants and their search tasksverification stage. Thirty-three DL stakeholders from a university on the east coast of the United States participated in the experiment. Of these, 11 (33%) self-reported as general users and 7 (21%), 6 (18%), 5 (15%), and 4 (12%) reported themselves as librarians, developers, researchers and administrators, respectively. In terms of age distribution, more than half of the participants (19, 58%) were over 40 years old, of which 11 (33%) participants were in their 50s. Additionally, 5 (15%) participants were in their 30s, 6 (18%) in their 20s, and 3 (9%) were under 20. The composition of subject fields for these participants was 11 (33%) for social sciences, 10 (30%) for sciences, and 7 (21%) for humanities and arts. More than half of the participants (19, 58%) had been using the university library Web for more than 3 years and over three-fourths (25, 76%) used the Web on a daily to weekly basis. Although the participants came up with their own search tasks of various topics, their search tasks were essentially to either find books/articles/images/other Web resources about a given topic (26 cases, 79%) or locate known items (7 cases, 21%). There was little inter-group difference among them in terms of the types of search tasks. The interview participants' perspectivess Table 3 lists Sustainability (4.0) Productivity (9; 6) Organizational Collaboration (30; 6) Integrity (4.2) accessibility (5.2) Sustainability (22; 6) Copyright compliance (5.1) QA = question answering; CS = card sorting. *The texts in bold are the important criteria that appeared in both the QA and the CS top-five rankings. criteria from the open-ended QA and the CS, which is based upon the frequency of a given criterion being mentioned (the first numbers in the parentheses), the number of interviewees who mentioned the criterion (the second numbers in the parentheses), or the average ranking order among the interviewees in CS. The data are grouped into the six DL levels. The criteria displayed on sorting cards for each DL level were preselected from the literature review findings. The number of CS criteria for each level was limited to 8-11. In contrast, there was no such preselection and restriction for QA criteria. What criteria and how frequently they were mentioned were open to the interviewees while they were answering questions, such as, "If you were asked to evaluate digital content, including digital object, information, metainformation and collection, what criteria would you use?" Furthermore, for a given DL level, CS always followed the open QA. Accordingly, criteria that were heavily mentioned by an interviewee might not be on the sorting cards. Similarly, during the open QA, an interviewee might not even mention a criterion highly ranked by him or her during CS. The transcripts revealed that some important criteria were excluded in the open QA due to oversight. For instance, after being presented with the sorting cards of the technologylevel evaluation criteria, IR3 said, "Reliability, I should have thought about that. Security, that's more important. I guess, I did forget the security matters…" In addition to the recall effect, the variation in total number of criteria between CS and QA and the emergence of new criteria in QA might also have caused the difference. Therefore, it would be more meaningful to look at shared criteria between QA and CS rather than to look for differences, although a potential reason for a couple of extremes (e.g., personalization for the interface, use/reuse for the user level and productivity of community members for the context) might be worth examining. Meanwhile, considering the primary research objective, which is to identify what criteria should be used for DL evaluation, the analyses focused more on the important criteria perceived rather than the unimportant ones. In general, over half of the important criteria (see the texts in bold in Table 3 The survey participants' perspectives. Table 4 summarizes the five most important criteria and the lowest regarded criterion of each of the six DL levels perceived by the survey participants. The rankings of the importance rating are based upon descriptive data, which include the mean (outside the parentheses) as the primary factor and SD (in the parentheses) as the secondary. Only when two criteria are identical in mean scores, the role of SD comes to play. The larger is the mean and the smaller the SD, the higher the ranking. Essentially, the important criteria perceived by the interviewees are also perceived to be significant by the survey participants, and so are the least significant criteria. For content level evaluation, usefulness to target users was consistently top ranked. It appeared in the top five lists of the survey, as well as the interview CS and QA. Unanimously, the interviewees and the survey participants regarded conciseness of information as the least important criterion. Digital technology evaluation criteria also were ranked consistently across the two studies. Reliability, effectiveness, and interoperability among systems unanimously appeared in the top lists of the survey as well as the interview CS and QA. Both ease of use and efficiency were highly rated in the survey and the interview QA section. Similarly, for interface level evaluation, all highly ranked criteria in both CS and QA-ease of use, effectiveness, and appropriateness to target users-were also ranked at the top in the survey. Attractiveness, the least important criterion in the interview, was still the second lowest ranked in the survey. The results for service level evaluation are also consistent. In particular, service accessibility and integrity to informationseeking path appeared in the top five lists of the interview CS and QA as well as of the survey. Similarly, courtesy was the lowest-ranked criterion in the three lists, presumably because it does not directly influence users' search outcome. In contrast to the high consistency in perceived important criteria at these four lower levels, DL evaluation criteria at user and context levels show a large variance between the interview and the survey results. For user level evaluations, while successfulness, efficiency of task completion, and productivity of users appeared in the top lists of both the survey and the interview, satisfaction rose to the top of the survey list despite its ranking in the interview as one of the least important criteria. Meanwhile, some criteria that were highly regarded in the interview (e.g., learning effect and information literacy) were not at the top of the survey list. Behavior changes dropped to the lowest-ranked criterion. This is presumably associated with the inclusion of user groups in the survey. Users tended to care more about the direct effects of using a DL, such as efficiency and successfulness of task completion, and less about the indirect outcomes. As for context evaluation, although the interviewees and the survey participants agreed on sustainability as the most important criterion for assessing a DL at its context level, they were unlikely to have parallel perception about the importance of DL's extended social impact. This criterion was highly regarded in the interview QA; but it became the least important criterion in the survey. Another highly ranked criterion (i.e., integrity to social practice) in the interview also dropped to the least second. In contrast, incoming and outgoing hyperlinks (i.e., network effect) in the survey participants' perspectives were important to a certain extent, whereas it was the lowest-ranked criterion in the interview QA and CS. For the lower level DL evaluation, several instances of inconsistency between the two studies have also been observed. For example, technological flexibility was highly ranked in the interview CS, but in the survey it was the lowestranked criterion, possibly because the criterion seems to be of greater interest to DL developers than to users, and the inclusion of users' opinions in the survey contributed to the ranking drop. Additionally, the two lowest-ranked criteria in the interview (i.e., display quality and security) were ranked more highly in the survey. For service level DL evaluation, there was only one inconsistent perception (i.e., gaps between expectation and perception).It was excluded from the top five list of the survey whereas appearing in both CS and QA interview top results. This might again relate to the participation of general users in the survey who care less about the gaps. importance have been identified among the three stakeholder groups from the interview. Table 5 lists the consensus and divergence criteria from the CS results. The reason for using CS instead of QA results was that the criteria were identical among interviewees in CS, and thus, ready for comparison. In contrast, there was too much variance in QA on the criteria being mentioned. The determination of consensus or divergence was based upon comparing the sum of the ranking value from each group for a given criterion. If there was any criterion with the sum value larger or smaller by a factor of 2 over any of the other two groups, then this criterion was considered as having a divergent inter-group ranking. Otherwise, it was considered consensus. For example, the sum of the ranking value for content usefulness to target users is 15, 5, and 13, respectively, for the administrator, developer and researcher groups. Therefore, the criterion is considered to be much more highly ranked by the developer group than the other two and, thus, is categorized as divergent. Likely, the criteria with higher importance rankings (e.g., usefulness of information, technological reliability, and interface effectiveness) had more divergence and less consensus than the lower ranked criteria (e.g., conciseness, security, and personalization). Also, the service level and the user level diverged less (one out of the top five), whereas the other four levels had two or more perceived important criteria with wide variance. Not all DL evaluation criteria included in the survey have statistically significant differences among the five DL stakeholder groups. ANOVA results show that only 11 out of the 51 criteria (22%) have statistically significant inter-group differences on the criteria importance ratings. Table 6 , a summary of the ANOVA results, demonstrates that service, interface, and user evaluation criteria received more consensus among the groups on the importance ratings, which is in line with the interview results. In contrast, the context evaluation criteria had the most group divergence. Scheffe's post-hoc test results showed that the differences existed only among some of the five stakeholder groups. Furthermore, the differences existed primarily between the general users and the other stakeholder groups, including the administrators (6 criteria), the librarians (8 criteria), and the researchers (2 criteria). What the administrators, librarians, or researchers highly perceived was sometimes the ones least regarded by the users. For instance, unlike the other stakeholder groups' perspectives, all appropriateness criteria for the aspects of digital content, technology, and interface were not favored by the general users. Whereas the administrators and the librarians regarded copyright compliance and other context level evaluation criteria, the general users held the opposite view. Comprehensiveness of collection was the only criterion that had higher rankings from the users. Interestingly, no significant effect was found between the developers and any of the other four groups. In addition to the statistically significant effects, group differences can also be found through comparing the topranking criteria among the stakeholder groups. Some criteria are on the top five lists from all stakeholder groups (see text in bold in Table 7 ), while the others are perceived as being important by some of the groups. For instance, content evaluation had three criteria (i.e., accessibility, accuracy, and usefulness) that received all five groups' importance perceptions. However, the administrators considered appropriateness and integrity of information more important than ease of understanding, which was on the top five lists of the other four stakeholder groups, but not on the administrators' list. Additionally, comprehensiveness and fidelity of information only showed up in the users' and developers' top five lists, respectively. The succeeding holistic DL evaluation model section has more elaboration on inter-group consensus and divergence. Clearly, the service evaluation had the largest inter-group consensus (100%), and the technology evaluation received the least agreement (29%) with respect to the five top ranked criteria. The agreement rates for the other four DL level evaluations were 37% for the content and the context and 50% for the interface and the user. Lower agreement for the technology evaluation was also found in the interviews. The underlying reason might be associated with the unfamiliarity
Recently, Zhang REF developed a "holistic digital library evaluation model" for various levels of digital library evaluation according to Saracevic's six levels, in which the most relevant DL evaluation criteria among five groups of stakeholders (administrators, developers, librarians, researchers, users) are identified and organized.
Developing a holistic model for digital library evaluation
J. Assoc. Inf. Sci. Technol.
J. Assoc. Inf. Sci. Technol.
Computer Science