3

Chapter 1 gives background on the MIRACLE Project, defines institutional repositories (IRs), and describes the methods MIRACLE Project staff used to conduct a census of IRs in U.S. academic institutions.

1.1 The Impetus for the MIRACLE Project's Census of IRs in the United States

A considerable portion of the scholarly record is born digital, and some scholarship is produced in digital formats that have no physical, in-the-hand counterparts. The proliferation of digital scholarship raises serious and pressing issues about how to organize, access, and preserve it in perpetuity. The response of U.S. colleges and universities has been to build IRs to capture, preserve, and reuse the intellectual output of teaching, research, and service activities at their institutions. An IR is "a set of services that a university offers to the members of its community for the management and dissemination of digital materials created by the institution and its community members" (Lynch 2003) (see also Appendix F1).

The MIRACLE (Making Institutional Repositories a Collaborative Learning Environment) Project is investigating the implementation of IRs at academic institutions to identify models and best practices for the administration, technical infrastructure, and access to digital collections. The chief objective of the project is to identify specific factors contributing to the success of IRs and effective ways of accessing and using IRs. The census is the first of several activities aimed at achieving project objectives. Other activities will study IR users, contributors, and staff through the use of telephone interviews, case studies, personal interviews, observations, and experiments.

Originally, MIRACLE Project investigators proposed to survey operational IRs in North America; however, we were concerned that we would be duplicating the efforts of Charles Bailey and his University of Houston associates who were analyzing data from their Association of Research Libraries (ARL)-sponsored survey of member institutions at the same time we were making data-collection decisions for the MIRACLE survey (Bailey et al. 2006). Other surveys targeted specific user groups such as Coalition for Networked Information (CNI) members in the United States (Lynch and Lippincott 2005), CNI members abroad (van Westrienen and Lynch 2005), Canadian Association of Research Libraries (CARL)-member libraries (Shearer 2004), and early adopters of IR technology worldwide (Mark Ware Consulting 2004).

Examining these surveys' results, MIRACLE project investigators decided not to limit their efforts to a particular user group, membership, or affiliation, and not to restrict participation to institutions with an operational IR. Instead, we sought to cast our net broadly and fill a void. Conducting a census of academic institutions in the United States about their involvement with IRs, MIRACLE Project investigators decided not to exclude institutions that have not jumped on the IR bandwagon. Being more inclusive would increase our confidence that we would be able to identify the wide range of practices, policies, and operations in effect at institutions where decision makers are contemplating, planning, pilot testing, or implementing IRs. At the same time, it would enable us to learn why some institutions have ruled out IRs entirely.

1.2 Obtaining a Mailing List of Academic Library Directors

The first task of MIRACLE Project staff was to obtain an electronic mailing list bearing the names and e-mail addresses of academic library directors and senior library administrators at U.S. educational institutions. A number of companies provide this information for a fee (for example, see American Library Association 2006). After examining their products and services, MIRACLE Project staff narrowed options to the following four companies or products: (1) Thomson-Peterson's, (2) Market Data Retrieval, (3) American Library Directory Online, and (4) World Guide to Libraries Plus. After comparing these companies' products with respect to such variables as the number of records with e-mail addresses available, scope, and price, as well as other advantages and disadvantages, we decided to purchase mailing lists from two vendors: (1) American Library Directory (ALD) and (2) Thomson-Peterson's. Using ALD's online database, we downloaded a comprehensive list (2,207 records) of all college and university main libraries in the United States (including U.S. protectorates). Because ALD's online database did not provide e-mail addresses for specific individuals, we purchased a less comprehensive database from Thompson-Peterson's that we used to add e-mail addresses to ALD data. After deleting community colleges and duplicates, we ended up with 2,147 e-mail addresses for the nationwide census.

1.3 Conducting Comparative Analysis of Survey Software

To compare survey-software programs for administering our Web-based survey, MIRACLE Project staff signed up for free trials of 10 such software programs: SurveyMonkey, Zoomerang, Key Survey, SurveyConsole, EZQuestionnaire, iSalient, QuestionPro, Ridgecrest Surveys, SmartSurveys, and SuperSurvey. Staff also researched Flashlight Online, ScyWeb, and UM.Lessons. On the basis of pricing information, flexibility, and functionality, we narrowed the list to SurveyMonkey, Zoomerang, Key Survey, and UM.Lessons. Staff eliminated UM.Lessons and Key Survey from consideration because of the former's limited flexibility and functionality and the latter's cost.

MIRACLE Project staff's decision to use SurveyMonkey instead of Zoomerang was based on the former program's greater flexibility and functionality. Our purchase of a one-year professional subscription to SurveyMonkey would enable us to launch an unlimited number of surveys with an unlimited number of questions and to use its advanced features for the survey's many complicated questions.

1.4 Drafting and Pretesting Survey Instruments

To draft survey instruments, MIRACLE Project investigators reviewed published and open-access literature on IRs through 2005 (see the MIRACLE Project's bibliography for a list of relevant publications at http://miracle.si.umich.edu/bibliography.html), talked to colleagues, and asked advisory group members (see Appendix A) to review, comment on, and edit draft instruments. Because the investigators expected survey respondents to come from institutions that were at various stages of the IR effort, they could neither ask everyone the same questions nor ask questions in the same way. Advice from advisory group members resulted in these four categories of IR involvement: (1) no planning to date (NP), (2) planning only to date (PO), (3) planning and pilot testing one or more IR systems (PPT), and (4) public implementation of an IR system at the respondent's institution (IMP). MIRACLE Project investigators drafted four different questionnaires based on these four categories of IR involvement.

Asking the same or similar questions in two or more questionnaires would enable investigators to make comparisons among institutions on the basis of the extent of their involvement with IRs. For example, here is a question about anticipated benefits of IRs that is worded a little differently depending on an institution's involvement with IRs:

• For NP respondents: How important do you think these anticipated benefits of IR would be to your institution?

• For PPT and PO respondents: How important are these anticipated benefits of IR to your institution?

• For IMP respondents: At the beginning of IR planning at your institution, how important did you think these anticipated benefits of IR would be to your institution?

Appendixes B, C, D, and E contain the MIRACLE Project questionnaires for NPs, POs, PPTs, and IMPs, respectively.

1.5 Setting Up Survey Administration Procedures and Protocol

Having so many institutions (2,147) in the census sample required MIRACLE Project staff to work out a detailed distribution plan. After pretesting a few different approaches, we decided to send an e-mail message to each institution's academic library director or a senior administrator to tell them about the census and to ask them about the extent of their involvement with IRs. More specifically, we wrote, "Please tell me how you would characterize the current status of your institutional repository (IR)." We asked them to base their response on one of four categories: (1) no planning to date, (2) planning only to date, (3) both planning and pilot testing one or more IR systems, and (4) public implementation of an IR system at their institution.

On the basis of the person's response, we replied with an e-mail message bearing a link to the appropriate Web-administered questionnaire (see Appendixes B, C, D, and E for NP, PO, PPT, and IMP questionnaires, respectively). We used SurveyMonkey's list-management tool to send out initial survey links and to perform two subsequent follow-ups with individuals who had agreed to participate but who had failed to respond to our inquiries.

Recruiting people to participate in the MIRACLE census in this way is the electronic version of what those in the sales world term a "cold call." We sent prospective respondents e-mail messages with a substantive phrase in the "SUBJECT" line announcing our IR census and asked them to participate. It is likely that the people who responded to our e-mail message were interested in IRs and thus were more likely to open, read, and respond to such a message and eventually respond positively about IRs on their completed questionnaires. Thus, MIRACLE census respondents may be more favorably inclined toward IRs than other academic library directors and senior administrators generally because of how we recruited them.

1.6 Data Collection

MIRACLE Project staff conducted the nationwide IR census from April 19, 2006, through June 24, 2006. Data collection was not straightforward. When few respondents responded to our invitations and reminders, we discussed problems and brainstormed ways of solving them. For example, coprincipal investigator Elizabeth Yakel suggested replacing the original SUBJECT line in our e-mail messages, "IMLS Institutional Repositories Census," with the catchier phrase, "Be Counted! National Institutional Repository Census." This change did indeed result in a higher response rate.

Table 1.1 summarizes the six data collection rounds that were necessary to increase the survey's invitational response rate to an acceptable level.

Table 1.1 Data collection rounds

No. of invitations sent	Date	Cumulative invitation response rate*		Cumulative survey response rate†		Explanations and changes made to increase response rates
No. of invitations sent	Date	No.	%	No.	%	Explanations and changes made to increase response rates
2,147	4/19 to 4/26	172	9	89	5	Invitations sent through Rieh's e-mail account. Staff research 260 undeliverable messages.
1,698	5/2 to 5/14	320	15	169	8	Invitations sent through Markey's e-mail account. Staff continue to research undeliverable messages.
1,805	5/15 to 5/22	467	22	273	13	Invitations sent through Markey's e-mail account. Staff change SUBJECT line and invitation text.
1,619	5/23 to 5/30	566	27	370	18	Invitations sent through Markey's e-mail account.
1,511	5/31 to 6/7	627	30	420	20	Invitations sent through Yakel's e-mail account.
1,446	6/8 to 6/24	676	32	500	24	Yakel's account. Staff change SUBJECT line announcing end of census. Seven undeliverable messages.
*Total number of people who responded to our invitation stating that they were willing to participate in the MIRACLE Project census. †Total number of people who clicked on the SurveyMonkey link that MIRACLE Project staff sent to them in response to our invitation. Generally, these figures indicate how many people actually participated in the survey. Because some people who clicked on the link exited the survey without answering any questions, these percentages are inflated. After MIRACLE Project staff had removed empty and nearly empty response sets, deleted duplicates, etc., the census response rate was 20.8%.

Concurrent with sending e-mail invitations, MIRACLE Project staff e-mailed a link to the appropriate Web-administered questionnaire to respondents within three business days of their response to our invitation. When respondents failed to return the completed questionnaires, staff sent them up to two reminders. The text of these two e-mail responses (the first survey link e-mail and the reminder e-mail) remained fairly stable throughout the census. Staff took care to send e-mail correspondence from the same account (Rieh, Markey, or Yakel), matching the account to which each respondent had initially responded.

A large number of people who had agreed to participate in the census failed to follow through. To rectify this situation, MIRACLE Project staff drafted two e-mail messages—one for respondents who had not yet started filling out the questionnaire and a second for respondents who had answered some questions. The SUBJECT line of both e-mail messages was "Survey to Close 6/24 (Nationwide Census of Institutional Repositories)." In mid-June, staff sent these e-mails to selected respondents. Because these e-mail messages encouraged a number of respondents to complete questionnaires, staff sent a second message to those who had still not responded and changed the SUBJECT line to "5 Days Left: Last Chance to be Counted in Nationwide Census of Institutional Repositories." Quite a few people filled out questionnaires after receiving the second message. When MIRACLE Project staff closed questionnaire administration in SurveyMonkey at 8 a.m. on June 25, 2006, the invitation response rate was 32%.

1.7 Data Analysis

After closing the census in SurveyMonkey, MIRACLE Project staff exported census data from SurveyMonkey into four Microsoft Excel files (one for each version of the survey—NP, PO, PPT, and IMP). Staff cleaned up census data, deleting the responses of people who did not sign the informed consent form as well as those of people who responded only to the informed consent form or to the one question about the number of IRs at their institution. Staff deleted empty questionnaires. They deleted multiple answer sets, keeping only the most comprehensive response sets from respondents. Staff deleted one entry that was submitted from a two-year college. This college had been sent an invitation because of an error in one of the mailing lists that we had purchased. After data cleanup had been completed, the census response rate was 20.8%.

MIRACLE Project staff imported the cleaned-up census data into SPSS and calculated frequency tables for the responses to each question in each of the four survey versions. Using these SPSS calculations, staff created an Excel spreadsheet that depicted frequency tables side-by-side for each question across the four questionnaire versions. Staff also produced a Word document that shows respondents' answers to open-ended questions.

MIRACLE Project staff used related data files to probe research questions in greater depth. For example, they downloaded a file from the Carnegie Foundation's Web site that allowed them to determine whether census participants were representative of educational institutions in the United States (see Subchapter 2.2) (Carnegie Foundation 2006b).

1.8 Chapter 1 Summary

Institutional repositories are the response of U.S. colleges and universities to the problem of organizing, providing access to, and preserving scholarship that their learning communities produce in digital formats.

Originally, MIRACLE Project investigators proposed to survey operational IRs in North America; however, we were concerned that we would be duplicating previous surveys that targeted institutions with operational IRs. We decided to cast our net broadly and to conduct a census of American academic institutions about their involvement with IRs. Census results would fill a void—yielding data and analyses about educational institutions that are and are not involved with IRs.

MIRACLE Project staff purchased mailing lists from two vendors: (1) ALD, and (2) Thomson-Peterson's. After deleting community colleges and duplicates, we ended with a total of 2,147 e-mail addresses for the nationwide census.

Staff pilot-tested several Web-administered software programs and chose SurveyMonkey because of its flexibility and functionality for the complex questions in MIRACLE questionnaires.

Project investigators drafted questionnaires and received feedback from advisory group members regarding questions and response categories. On the basis of their input, staff developed four separate questionnaires based on respondents' extent of involvement with IRs: (1) no planning (NP), (2) planning only (PO), (3) planning and pilot testing (PPT), and (4) implementation (IMP). (See Appendixes B, C, D, and E for NP, PO, PPT, and IMP questionnaires, respectively.)

Data collection took place from April 19, 2006, through June 24, 2006. MIRACLE Project staff sent invitations to participate in the census via e-mail to each institution's academic library director or a senior administrator. The e-mail explained the census and asked them about the extent of their involvement with IRs. We replied via e-mail to those who responded to our request with a link to the appropriate Web-administered questionnaire.

Low response rates to our invitation resulted in changes in the text of our reminder messages, especially the wording of the message's SUBJECT line. After data collection ended on June 24, 2006, MIRACLE Project staff cleaned up census data, for example, deleting empty questionnaires or responses of people who did not sign the informed consent form. After data cleanup had been done, the census response rate was 20.8%. MIRACLE Project staff then proceeded with data analysis and reporting activities.

2 THE INSTITUTIONS AND THE PEOPLE INVOLVED WITH IRs

Chapter 2 examines the extent to which certain types of academic institutions are involved with institutional repositories (IRs) and the nature of people's involvement with IRs at these institutions.

2.1 Census Respondents

Of the 2,147 academic library directors and senior library administrators MIRACLE Project staff contacted, 446 participated in the census—a response rate of 20.8%. Characterizing the extent of their involvement with IRs, 236 (52.9%) respondents have done no IR planning (NP) to date, 92 (20.6%) respondents are only planning (PO) for IRs, 70 (15.7%) respondents are actively planning and pilot testing IRs (PPT), and 48 (10.8%) respondents have implemented (IMP) an operational IR. Figure 2.1 is a graphical representation of the extent of IR involvement by MIRACLE Project census respondents.

When MIRACLE Project staff contacted library directors and senior library administrators by e-mail, we asked them to pass our questionnaire to staff who were most familiar with their institution's involvement with IRs. The questionnaires concluded by asking respondents to identify their positions at their institution. Figure 2.2 shows the titles of those who completed questionnaires.

Almost three-quarters of respondents are library directors; the second- and third-largest percentages (10.2% and 7.9%, respectively) are library staff and assistant-associate librarians, respectively. Library directors prevail in terms of responding to the MIRACLE Project staff's request to participate in the census. We deliberately chose to make library directors or senior library administrators the initial contact at academic institutions because of the difficulty identifying the names of the key person(s) involved with IRs at academic institutions and finding address lists to simplify and streamline contacting tasks. For example, we could have contacted chief information officers (CIOs) instead of librarians but academic institutions do not necessarily apply the CIO moniker across the board nor do all institutions have such a position. The same thing probably applies to archivists. Even more complicated would have been contacting middle management in academic institutions—deans, directors, chairs, and heads of academic units, research centers, and institutes. Because every academic institution is likely to employ a librarian, we contacted librarians in top management positions to participate in our census.

Our decision to contact librarians may have caused us to miss academic, research, and service units that have implemented or are planning to implement an IR. To some extent, respondents' answers to a census question about how many IRs are available at their institutions may shed light on what we missed (see Chapter 5.1 for answers to this question). MIRACLE Project investigators readily admit that census results may be biased toward libraries because our initial contact was the college or university librarian.

Table 2.1 shows a breakdown of census respondents based on the extent of their institutions' involvement with IRs. At NP institutions, about 90% of respondents are library directors. Percentages in other named-position categories are very small. Of the four people classed in "Other," three are combined library directors-CIOs, and one is head of digital library programs.

Table 2.1. Respondents' positions based on the extent
of IR involvement at their institutions

Respondent position	NP		PO		PPT		IMP		Total
Respondent position	No.	%	No.	%	No.	%	No.	%	No.	%
Library director	194	90.6	57	71.3	29	48.3	8	21.6	288	73.7
Library staff	5	2.3	11	13.8	8	13.3	16	43.3	40	10.2
Assistant or associate library director	5	2.3	0	0.0	16	26.7	10	27.0	31	7.9
Archivist	4	1.9	3	3.7	2	3.3	0	0.0	9	2.3
CIO	1	0.5	5	6.2	1	1.7	1	2.7	8	2.0
VP or provost	1	0.5	0	0.0	0	0.0	0	0.0	1	0.3
Other	4	1.9	4	5.0	4	6.7	2	5.4	14	3.6
Total	214	100.0	80	100.0	80	100.0	37	100.0	391	100.0

At PO institutions, the percentage of respondents who are library directors (71.3%) is smaller than the percentage for NPs. Contacts at POs passed questionnaires to library staff (13.8%), CIOs (6.2%), and archivists (3.7%). Of the four people classed in "Other," two hold combined positions (i.e., library director-CIO and library director-archivist), one is assistant director of administrative services, and one is a faculty member affiliated with the library.

At PPT institutions, the percentage of respondents who are library directors (48.3%) is smaller than the percentages for POs and NPs. Contacts at PPTs mostly passed questionnaires to associate or assistant library directors (26.7%), library staff (13.3%), and archivists (3.3%). They rarely passed questionnaires to CIOs (1.7%). The four people classed in "Other" hold different positions: two are digital library directors, one is the associate dean for research, and one is the assistant director of library campus support systems.

At IMP institutions, the percentage of respondents who are library directors drops to 21.6%. Larger percentages of library staff generally (43.3%) and associate or assistant library directors (27.0%) are completing questionnaires. The two people classed in "Other" are a director of special collections and archives and a librarian working as a temporary consultant on the IR.

As shown in Table 2.1, library-director percentages decrease as IR activity increases. Most likely, directors passed on our request to complete questionnaires to staff who would be more knowledgeable about IR activity at their institution. Such activity increasingly involves library staff generally at PO institutions, and both library staff generally and assistant and associate directors at PPT and IMP institutions.

2.2 Using CCHE to Characterize Participating Institutions

Scrutinizing the types of institutions that participated in the MIRACLE census respondents made project investigators wonder whether certain types of institutions are more or less likely to be involved with IRs. To characterize the institutions that participated in the MIRACLE Project, investigators turned to the Carnegie Classification of Institutions of Higher Education (CCHE). CCHE was derived from empirical data on colleges and universities and has been updated five times since it was originally published for use by researchers in 1973. CCHE is "the leading framework for describing institutional diversity in U.S. higher education [and] … has been widely used in the study of higher education, both as a way to represent and control for institutional differences, and also in the design of research studies to ensure adequate representation of sampled institutions, students, or faculty" (Carnegie Foundation 2006a).

Table 2.2 lists classes of CCHE institutions that MIRACLE Project investigators invited to participate in the nationwide census. Because we limited the census to institutions awarding four-year baccalaureate degrees or higher, missing from Table 2.2 is the CCHE "Associate" class for institutions awarding two-year associate degrees.

Table 2.2. Classes of CCHE institutions invited to
participate in the MIRACLE census

Class	Definition	Subclasses
Doctorate-granting universities*	Institutions that award at least 20 doctoral degrees per year (excluding doctoral-level degrees such as the JD, MD, PharmD, DPT, which qualify recipients for entry into professional practice).	RU/VH: Research Univs. (very high research activity) RU/H: Research Univs. (high research activity) DRU: Doctoral/Research Univs.
Master's colleges and universities*	Institutions that award at least 50 master's degrees per year.	Master's/L: Master's Colleges and Univs. (larger programs) Master's/M: Master's Colleges and Univs. (medium programs) Master's/S: Master's Colleges and Univs. (smaller programs)
Baccalaureate colleges*	Institutions where baccalaureate degrees represent at least 10% of all undergraduate degrees and that award fewer than 50 master's degrees or fewer than 20 doctoral degrees per year.	Bac/A&S: Baccalaureate Colleges—Arts and Sciences Bac/Diverse: Baccalaureate Colleges—Diverse Fields Bac/Assoc: Baccalaureate/Associate's College
Special-focus institutions	Institutions awarding baccalaureate or higher-level degrees where a high concentration of degrees is in a single field or set of related fields.	Examples are theological seminaries, Bible colleges, medical schools, engineering schools, business schools, and law schools.
Tribal schools	Colleges and universities that are members of the American Indian Higher Education Consortium.	The majority are associate's colleges but there are a few baccalaureate colleges.
* Excludes special-focus institutions and tribal colleges.

To emphasize the research-intensive nature of census institutions, MIRACLE Project staff broke up the "Doctorate-granting Universities" CCHE class into two classes: (1) "Research universities," bearing institutions from the two Research Universities (RU/VH and RU/H) CCHE subclasses; and (2) "Doctoral universities," bearing institutions from the "Doctoral" (DRU) CCHE subclass. Figure 2.3 shows the percentages of institutions participating in the MIRACLE Project census by CCHE classes. It also distributes the population of U.S. academic institutions into these same CCHE classes.
High percentages of CCHE institutions come from the Special Focus (32.0%), Baccalaureate (29.3%), and Master's (27.3%) CCHE classes. Except for special-focus (11.7%) institutions, percentages of MIRACLE census respondents are comparable for master's (37.2%) and baccalaureate (27.6%) institutions. A large percentage (18.6%) of MIRACLE census respondents are research universities, but only 7.9% of CCHE institutions come from this class.

MIRACLE Project staff tallied the four types of MIRACLE census respondents according to their CCHE class. The results (see Table 2.3) reveal what types of CCHE institutions are more and less likely to implement IRs.

Research universities vastly outnumber all other CCHE classes involved with IMP and PPT. A few institutions in the other CCHE classes are implementing IRs, but most are in the PO stage or are not involved with IRs at all. Most NP and PO respondents come from master's and baccalaureate institutions.

Table 2.3. CCHE classes reveal the extent of IR involvement
by census respondents

CCHE classes	NP		PO		PPT		IMP		Total
CCHE classes	No.	%	No.	%	No.	%	No.	%	No.	%
Research univs.	13	5.5	14	15.2	26	37.1	30	62.5	83	18.6
Doctoral univs.	7	3.0	7	7.6	3	4.3	1	2.1	18	4.0
Master's	103	43.6	32	34.8	22	31.5	9	18.8	166	37.2
Baccalaureate	79	33.5	29	31.5	10	14.3	5	10.4	123	27.6
Special focus	32	13.6	9	9.8	8	11.4	3	6.2	52	11.7
Tribal	1	0.4	0	0.0	0	0.0	0	0.0	1	0.2
Unclassified*	1	0.4	1	1.1	1	1.4	0	0.0	3	0.7
Total	236	100.0	92	100.0	70	100.0	48	100.0	446	100.0
* Three institutions are unclassified because they responded with two or more institutions in partnership-like arrangements.

2.3 Positions of the People Involved with IRs

Questionnaires asked census respondents about the people involved in their institutions' IR efforts. Specifically, respondents from PO, PPT, and IMP institutions were asked, "How active were people in the following positions in terms of leading the charge to get involved with IRs at your institution?" and respondents from NP institutions were asked, "How active do you think that the people in these positions would have to be to light the spark for IR planning at your institution?" Respondents chose from a list of 13 positions or could write in a response for "Other."

To simplify results, MIRACLE Project staff assigned weights to response categories as follows: (+2) very active; (+1) somewhat active; (0) no opinion, don't know, or not applicable; (-1) somewhat inactive; and (-2) very inactive. They totaled the weights. The results were then compiled to rank order all the positions. Table 2.4 uses IMP ranks to order top- (1 to 4), middle- (5 to 8), and bottom-ranked (9 to 13) positions.

Table 2.4. Positions of people involved in the IR effort

Top-ranked positions (1 to 4)	NP	PO	PPT	IMP
Library director	1	1	1	1
Assistant library director(s)	(11)†	2T*	2	2
Library staff member(s)	(5)	2T	3	3
A particular faculty member	(10)	(6)	4	4
Middle-ranked positions (5 to 8)	NP	PO	PPT	IMP
Institution's archivist	7	(4)	5	5
Institution's vice president or provost	(2)	8T	(9)	6
Staff at a library network, consortium, or other affiliated group	6	5	6	7
Faculty members generally	(3)	8T	8	8
Bottom-ranked positions (9 to 13)	NP	PO	PPT	IMP
Institution's chief information officer	(4)	(7)	(7)	9
Faculty governance	(8)	12	12	10
Graduate students	12	10	10	11
Institution's president or chancellor	9	13	13	12
Undergraduate students	13	11	11	13
† Parentheses indicate NP, PO, and PPT positions that deviated from IMP top, middle, or bottom ranks. * T indicates a ranked position that tied another position's weight.

Generally, PO, PPT, and IMP respondents agree about top-, middle-, and bottom-ranked positions. For PO, PPT, and IMP respondents, the three top-ranked active positions are (1) library director, (2) assistant or associate library director(s), and (3) library staff member(s). Students at all levels, faculty governance, presidents, and chancellors are not necessarily active in IR efforts.

NP respondents agree with those in the other three groups that the highest level of activity comes from the library director. To light the spark for the IR effort at NP institutions, support must come not only from top positions in the library but also from other leaders at the institution (e.g., the vice president or provost, or CIO) and from faculty members generally.

The questionnaires allowed respondents to give open-ended responses to this question. Most responses are unique but a few overlap. Respondents from PO, PPT, and IMP institutions say the following people are very active:

• director, staff, and/or advisory committee from the institution's instructional technology unit (three responses)

• faculty at the institution's Office of Undergraduate Research Initiatives

• global subject discipline research committees

• internal and external volunteers such as library school students and visiting librarians

• public relations staff

• strategist from the institution's Academic Computing

• curriculum technology staff

• technology-assisted learning staff

At NP institutions, people in positions that would have to be very active in an IR effort are again external to the library:

• director of the institution's instructional technology unit

• academic deans

• museum director

• Web developers

• systems staff

An examination of open-ended responses reveals in retrospect that we should have included a response category for "instructional technology staff" because it might have figured among the top-ranked response categories at PO, PPT, and IMP institutions. Other response categories on our list should have been "academic computing" and "academic deans."

2.4 Number of People Involved with IRs

Questionnaires asked PO, PPT, and IMP respondents how many people were involved in their institutions' IR efforts. The overall average is 7.2 people. At PO, PPT, and IMP institutions, averages are 6.0, 8.4, and 7.8 people, respectively.

These are merely counts of the number of people involved in the IR effort. MIRACLE Project investigators also wanted to ask census respondents about full-time equivalents (FTEs). However, respondents who pretested MIRACLE questionnaires expressed difficulty generating exact FTE numbers so we deleted questions about FTEs.

Figure 2.4 presents results in five-person ranges. Up to 10 people is typical for 89.8% institutions in the PO stage. On average, when institutions move to the PPT stage, the number of people involved increases. It then decreases in the IMP stage. At some institutions, more than 20 people are involved in the IR effort at the PPT stage. Although numbers from the ARL SPEC Kit are substantially higher (Bailey et al. 2006, 15), both SPEC Kit numbers and our numbers show a downward trend between the PPT and the IMP stages (see Appendix F4).

2.5 Positions of People Involved with IRs

The questionnaires asked who is leading IR planning, planning and pilot testing, and implementation at PO, PPT, and IMP institutions. Table 2.5 gives the results.

Table 2.5. Positions of people leading the IR effort

Position leading the IR effort	PO		PPT		IMP
Position leading the IR effort	No.	%	No.	%	No.	%
Library director	46	54.7	18	28.6	13	31.7
Library staff member	12	14.3	15	23.8	14	34.2
Assistant or associate library director	3	3.6	13.	20.6	11	26.8
CIO	4	4.8	1	1.6	1	2.4
Archivist	5	5.9	2	3.2	0	0.0
Faculty member in an academic unit	4	4.8	1	1.6	0	0.0
No committee or committee chair has been charged	6	7.1	1	1.6	0	0.0
Other	4*	4.8	12†	19.0	2‡	4.9
Total	84	100.0	63	100.0	41	100.0
* Team effort (2); consortium (1); duo effort: archivist and library director (1). † Director of instructional technology (3); duo effort (3), for example, library director and CIO; vice president or associate dean for research (2); team effort (2); consortium (1); digital asset management committee (1). ‡ Consortium (1); director of special collection and archives (1).

Generally, people in library positions lead in all stages of the IR effort. In the PO stage, the library director is in the lead. The library director relinquishes that role when the IR effort reaches PPT and IMP stages, in most cases, to one particular staff member or an assistant or associate library director. If archivists, CIOs, and faculty members from academic units are in the lead, the IR effort is in the planning stage. Write-in responses reveal that staff from two or more units may share the lead, especially during PPT stage. For example, the associate librarian leads planning and the CIO leads pilot testing.

Questionnaires for PO, PPT, and IMP institutions asked respondents what positions IR committee members held. Figure 2.5 depicts the percentages of respondents choosing from 13 positions listed on their questionnaires. The figure uses lines to connect the three percentages, beginning with PO and ending IMP. It is not a timeline because different people completed PO, PPT, and IMP questionnaires. Presenting results in this way is helpful because it reveals the following dynamics of committee membership:

• Generally, IR committees are more inclusive during the PPT stage and less inclusive during the PO and IMP stages.

• The likelihood that staff from the vice president's or provost's office are on IR committees decreases from the PO stage to the PPT stage, while people in all other positions are more likely to be members of IR committees.

• The likelihood that library staff and assistant or associate library directors are on IR committees increases from stage to stage, while people in all other positions are less likely to be members of IR committees as IR work continues.

• Faculty members are more likely to be involved in the conceptual stages of planning the IR; their involvement decreases as the IR becomes operational.

Especially nonrepresentative at the IMP stage are CIO staff, faculty members, and staff from the office of the vice president or provost. Not included in Figure 2.5 are percentages for five positions—graduate students, undergraduate students, and staff from the office of the president or chancellor, from the CIO's office, and from the institution's legal counsel—because less than 10% of respondents observed their participation on IR committees.

Many respondents wrote in unique staff or management positions not included in the list.

At PO institutions the write-in positions are

• three for academic computing and three for instructional technology

• two for consortium

• one each for alumni relations, art-slide curator, center for teaching, communications, development, enrollment services, external affairs, dean of graduate studies, staff photographer, student affairs, and university press

At PPT institutions the write-in positions are

• four for instructional technology

• two for consortium

• one each for academic computing, art-collections curator, art-slide curator, and dean of graduate studies

At IMP institutions the write-in positions are

• three for instructional technology

• one each for academic computing, digital library program, health sciences center, media services, university press, and the college-level Web content editor

In retrospect, we should have included response categories for "instructional technology" and "academic computing" because several respondents volunteered them.

2.6 The Responsibility for the IR

Questionnaires for IMP and PPT respondents asked what percentage of the responsibility for an operational IR is given to various campus units, and the questionnaire for PO respondents asked what percentage should be given to various campus units. All three questionnaire versions listed the same units and respondents could write in units that were not listed. MIRACLE Project staff programmed SurveyMonkey to force respondents to enter percentages that added to 100%. Figure 2.6 gives the results.

During planning, respondents share responsibility for the IR, with the library taking about 40% of the responsibility; archives, central computing, and various academic units, sharing about 12% of the responsibility; and the CIO's office sharing 6% of the responsibility. During PPT, the responsibilities of the library and various academic units increase while others' responsibilities decrease. The increase for academic units during the PPT phase probably entails early adopters who are contributing to the IR in a pilot test. During IMP, the library shoulders almost all of the responsibility for the IR. Questionnaires should have included a response category for "consortium" because several write-ins named their consortium as the unit taking most of the responsibility for the IR.

2.7 Involvement with IRs

Questionnaires asked respondents at PO, PPT, and IMP institutions how long they have been involved with IRs. PO institutions average 12 months, PPT institutions average 21.3 months, and IMP institutions average 31.5 months.

Figure 2.7 shows responses in 12-month ranges. About 70% of PO institutions have been involved with IRs for 12 months or fewer. Comparable percentages of PPT (77.6%) and IMP (70.8%) institutions have been involved with IRs for 24 or fewer months and 36 or fewer months, respectively. About 15% of IMP institutions have been involved with IRs for more than four years.

2.8 Chapter 2 Summary

Of the 2,147 academic library directors or senior library administrators MIRACLE Project staff contacted, 446 participated in the census—a response rate of 20.8%. A little more than half of respondents have done no IR planning to date, about 20% are planning for IRs, about 15% are actively planning and pilot testing IRs, and a little more than 10% have implemented an operational IR (see Figure 2.1).

MIRACLE Project investigators used the CCHE to determine the types of institutions that are more or less likely to be involved with IRs. "Research universities" vastly outnumber all other CCHE classes involved with IMP and PPT (see Table 2.3). Most NP and PO respondents come from master's and baccalaureate institutions.

Census respondents in the PO, PPT, and IMP stages agree on the positions of people most involved with IRs at their institution. They are the library director, assistant or associate library director(s), and library staff member(s) (see Table 2.4). To light the spark for the IR effort at NP institutions, support must come not only from the library director but also from other leaders at the institution, including the vice president or provost and CIO. Faculty members generally should also be active.

The number of people involved in the IR effort averages 7.2 overall but varies a little during the IR implementation process. PO, PPT, and IMP institutions average 6.0, 8.4, and 7.8 people, respectively (see Subchapter 2.4). The PPT stage is most inclusive, involving 20 or more people at times (see Figure 2.4).

In terms of the person leading the IR effort, the library director takes the lead in the planning stage but relinquishes it, in most cases, to one particular staff member or an assistant-associate library director in the PPT and IMP stages (see Table 2.5). If archivists, CIOs, and faculty members from academic units are in the lead, the IR effort is probably in the planning stage.

IR committee membership waxes and wanes depending on the particular phase of the IR project (see Figure 2.5). IR committees are most inclusive during the PPT stage and less inclusive during the PO and IMP stages. The likelihood that library staff and assistant or associate library directors are on IR committees increases from stage to stage while people in all other positions are less likely to be members of IR committees as work proceeds.

During planning, respondents share responsibility for the IR with the library taking about 40% of the responsibility; archives, central computing, and various academic units, sharing about 12% of the responsibility; and the CIO's office sharing 6% of the responsibility (see Figure 2.6). When planning and pilot testing, the responsibilities of the library and various academic units increase while others' responsibilities decrease. The increase for academic units during the PPT phase probably entails early adopters who are contributing to the IR in a pilot test. At implementation, the library shoulders almost all of the responsibility for the IR.

Asked how long their institutions have been involved with IRs, PO institutions average 12 months, PPT institutions average 21.3 months, and IMP institutions average 31.5 months (see Figure 2.7). Of the total 48 IMP institutions in the MIRACLE census, seven (14.6%) have been involved with IRs for more than four years.

3 THE BUDGET FOR AN IR

Chapter 3 focuses on the budget for an institutional repository (IR), specifically on sources of funding and on line items in the IR budget.

3.1 Sources of Funding

Respondents from institutions planning (PO), planning and pilot testing (PPT), and implementing (IMP) IRs were asked how likely the funding for an IR was to come from a list of 17 sources.

To simplify results, MIRACLE Project staff assigned weights to response categories as follows: (+2) very likely; (+1) somewhat likely; (0) no opinion, don't know, or not applicable; (-1) somewhat unlikely; and (-2) very unlikely. Staff totaled the weights. These results were compiled to rank order all the funding sources. Table 3.1 uses IMP ranks to order the top- (1 to 6), middle- (7 to 12), and bottom-ranked (13 to 17) funding sources.

Table 3.1. Top- and bottom-ranked funding sources

Top-ranked funding sources (1 to 6)	PO	PPT	IMP
Special initiative supported by the library	1	2	1
Costs absorbed in routine library operating costs	2	1	2
Regular budget line item for your institution's library	4	3	3
Grant awarded by an external source	3	4	4
Special initiative supported by your institution's central administration	5	6	5
Special initiative supported by your institution's archives	(8)†	(9)	6
Middle-ranked funding sources (7 to 12)	PO	PPT	IMP
Grant awarded by an internal source	11	11	7
Special initiative supported by your institution's central computer services	(6)	(5)	8
Regular budget line item for your institution's archives	(15)	10	9
Costs absorbed in routine operating costs of your institution's archives	13	8	10
Regular budget line item for your institution's central computer services	9	11	11
Regular budget line item for your institution's central administration	(7)	(15)	12
Bottom-ranked funding sources (13 to 17)	PO	PPT	IMP
Costs absorbed in routine operating costs of your institution's central computer services	(10)	(7)	13
Costs absorbed in routine operation costs of central administration	(7)	15	14T*
Special initiative supported by academic colleges, departments, and schools	(11)	(13)	14T
Costs absorbed in routine operating costs of academic colleges, departments, and schools	16	16	16
Regular budget line item for academic colleges, departments, and schools	17	17	17
† Parentheses indicate PO and PPT funding sources that deviated from IMP top, middle, or bottom ranks. * T indicates a ranked funding source that tied another source's weight.

PO, PPT, and IMP respondents agree about the top-ranked funding source for IRs—funding comes or will come from the library. For example, a typical strategy is to absorb the costs into routine library operating expenses. Libraries at large research universities may find it easier to enlist such a strategy than libraries at small institutions because the IR effort may be hard to pinpoint in the former's multimillion-dollar budgets. Other strategies, such as a special library initiative or adding a regular budget line item, may require the library to obtain support from the central administration or to divert resources from ongoing activity to the IR.

Respondents agree that IR funding does not or will not come from academic units. Respondents from PO institutions especially do not envision funding coming from the archives. In write-in responses, two institutions indicate that they have received, or expect to receive, funds from the U.S. Department of Education's Title III grants, which aim to "assist eligible IHEs [institutions of higher education] to become self-sufficient and expand their capacity to serve low-income students by providing funds to improve and strengthen the academic quality, institutional management, and fiscal stability of eligible institutions" (U.S. Department of Education 2006). Two other write-in responses say their funding comes from a consortium.

3.2 IR Budget Line Items

Questionnaires for IMP and PPT institutions asked respondents what percentage of their IRs' annual budget is allocated to various line items. The two questionnaire versions listed the same line items, and respondents could write in items that were not listed. SurveyMonkey was programmed so that it required respondents to enter percentages that added to 100. Figure 3.1 gives the results.

Costs for staff and vendor fees represent about 75% of the IR budget, with staff costs exceeding vendor fees during PPT and vice versa during implementation. Hardware acquisition represents about 10% of the IR budget. Software costs represent 7% and 2.5% of PPT and IMP budgets, respectively. Costs for software maintenance, hardware maintenance, and system backup account for 12.5% of the IR budget.

Although many respondents volunteered open-ended comments pertaining to costs, only two comments cite line items that MIRACLE Project investigators failed to include in their original list:

• "Marketing and PR [public relations] activities."

• "Server farm charges, 1%, hosted by Central Computing; storage farm charges, 11%; indirect costs (15%)."

Despite having a fully functional and operational IR, several IMP respondents write about the informality of their IR's budget:

• "Our IR does not have a budget."

• "No specific budget for IR. It is absorbed in the library budget."

• "We do not really have a budget for this. The fee to the vendor is paid out of our library's operating costs. Three staff members each spend a few hours a week working on this project. It is impossible to estimate the staff cost."

• "We only budget for the subscription to our hosted product. We don't budget the staff time."

• "IR isn't budgeted separately anymore and was only partially budgeted separately from the library in year 1 and year 2."

• "[T]his question is difficult to answer. Staff responsible for the repository [are] doing repository work [and other unrelated tasks]. Vendor fees are shared between the library and central administration . . . I don't know the full operating budget of [either the library or central administration] nor am I interested to know."

Here is a comment from an IMP respondent who is exceptionally precise about her institution's IR budget:

• "This coming year will be an exception: $100,000 has been allocated for initial purchase and migration of commercial service provider. Our operating budget alone without the above would be staff, 49%; hardware acquisition, 27%; hardware maintenance, 3%; software acquisition, 16%; software maintenance and updates, 2%; vendor fees, 3%."

Several PPT respondents comment on the shared nature of the IR initiative:

• "We are not funding this project with dollars from our [library] budget; system administration is picking up all hardware and software costs. We [the library] are providing only human resources."

• "Our IR software and hardware were a special allocation from Instructional Technology Services (ITS) and the central administration. Maintenance and upgrade of server and software will be absorbed by ITS regular budget process. Implementation of the IR will be absorbed into regular library workflow."

• "The software license of ContentDM was purchased by central computing. The annual maintenance license agreement is paid by the library. All labor is carved from staff time in the Library and Institutional Technology Departments, with faculty involvement supervising work-study students. We are small scale, concentrating on unique content when faculty want something digitized."

• "Our IR is distributed among departments on campus—it has no separate budget."

Other PPT respondents could not break down IR costs into listed line items because they did not know or were unsure about the breakdown, or had not yet budgeted for the IR.

3.3 Chapter 3 Summary

PO, PPT, and IMP respondents agree about the top-ranked funding sources for IRs—funding comes or will come from the library (see Table 3.1). They also agree that funding is not coming from academic units.

Costs for staff and vendor fees represent about 75% of the IR budget, with staff costs exceeding vendor fees during PPT and vice versa during implementation (see Figure 3.1). Hardware acquisition represents about 10% of the IR budget. Software costs represent 7% of PPT and 2.5% of of IMP budgets. Costs for software maintenance, hardware maintenance, and system budget account for 12.5% of the IR budget. Underlying the write-in responses of several IMP respondents is a certain informality about the IR budget. We did not speculate on reasons for this informality.

4 IMPORTANT INVESTIGATIVE ACTIVITIES

Chapter 4 explores important investigative activities that institutions conduct to determine whether to implement an institutional repository (IR).

4.1 Important Investigative Activities

Planning only (PO), planning and pilot testing (PPT), and implementation (IMP) questionnaires asked respondents to rate the importance of various investigative activities in terms of influencing their decision to initiate planning, pilot testing, and implementation. To simplify results, MIRACLE Project staff assigned weights to response categories as follows: (+2) very important; (+1) somewhat important; (0) no opinion, don't know, or not applicable; (-1) somewhat unimportant; and (-2) very unimportant. They totaled the weights. These results were then compiled to rank order all the activities. Table 4.1 uses ranked activities in the "Total" column to order top-, middle-, and bottom-ranked activities.

Table 4.1. Important investigative activities

Top-ranked investigative activities (1 to 4)	PO	PPT	IMP
Learning about successful implementations at comparable institutions	1	2	1
Learning from reports of other institutions' PO, PPT, and IMP activities	2	1	2
Learning about successful implementations at a wide range of academic institutions	(5)*	3	3
An analysis of a thorough literature review of IRs	(9)	(5)	4
Middle-ranked investigative activities (5 to 8)	PO	PPT	IMP
Using other institutions' operational IRs	6	8	5
Results of your institution's needs assessment	7	7	6
Demonstrating operational IRs to my institution's decision makers	(3)	6	7
Learning about available expertise and assistance from a library consortium, network, group of libraries, etc.	(4)	(4)	8
Bottom-ranked investigative activities (9 to 12)	PO	PPT	IMP
Demonstrating IR metadata harvesters such as OAIster and Google Scholar to my institution's decision makers	10	10	9
Identifying better digital preservation techniques	(8)	9	10
Waiting for a critical mass of IR implementation at comparable institutions to happen	11	12	11
Waiting for a critical mass of IR implementation generally to happen	12	11	12
* Parentheses indicate PO and PPT investigative activities that deviated from IMP top, middle, or bottom ranks.

At the top of the ranked list are investigative activities concerning learning about IRs from the experiences of others. For PPT and IMP respondents, this includes analyzing literature reviews. PO and PPT respondents rank "Learning from a library consortium …" higher than IMP respondents do, most likely because the latter charged ahead with IR implementation before consortia, networks, and comparable groups had begun their involvement with IRs. PO respondents rank "Demonstrating operational IRs to my institution's decision makers" much higher than PPTs and IMPs do. Such demonstrations probably make IRs more tangible to decision makers. They increase decision makers' understanding of system functionality, IR contributors, contents, users, and uses. They help decision makers understand how IRs are in keeping with the institution's mission and thereby make them more favorably inclined to the IR initiative in terms of both funding and rhetoric.

At the bottom of the list are two activities about "Waiting for a critical mass of IR implementation to happen." Because only 28% of both PO and PPT respondents rate it "very" or "somewhat" important, it is clear that these respondents want to get involved with IRs now rather than to follow the crowd.

A wait-and-see attitude is evident in this write-in comment:

• "Waiting for clear leaders to emerge in the vendor or open-source IR options. Waiting for options that better meet our needs. Many products have potential but [are] not ready for prime time."

Write-ins by several PO respondents reveal three investigative activities that, had they been listed on the questionnaire, would have received high ratings: (1) finding funding for IR hardware and software; (2) finding funding for IR staffing; and (3) finding expertise for IR staffing.

Two write-ins by PPT respondents describe how they are taking the initiative to study their institutions' digital output:

• "IRs were starting to be formed on an ad hoc basis across the campus; we wanted to provide a single gathering space and search engine for these documents."

• "Conducted study of [our] institution's Web presence, which demonstrated a stewardship need and identified an extensive amount of potential IR content. Worked with pilot departments to add content and gauge interest."

Two write-ins by IMP respondents capture of experience of early adopters of IR technology:

• "We agreed to become a member of the original DSpace Federation in order to test a repository system and position ourselves to engage in e-publishing activities."

• "We were very early in our implementation, so there were few fully implemented repositories to examine. It was our provost's desire to start a 'faculty e-archive' that was the primary deciding factor."

4.2 The Needs Assessment

MIRACLE Project investigators expected that a needs assessment would be an important investigative activity that institutions would undertake before deciding to get involved with IRs. For that reason, the questionnaires featured as many as three additional questions about the needs assessment.

To our surprise, respondents ranked the needs assessment in the middle of the pack (Table 4.1). Although most evidently felt that the needs assessment was relatively unimportant compared with other activities, their answers were revealing.

About one in sixteen PO, one in four PPT, and one in three IMP institutions, respectively, have conducted a needs assessment (Figure 4.1). The percentage of respondents who do not know whether their institution conducted a needs assessment ranges from 5% to 12%. Asked whether they would be likely to conduct a needs assessment prior to making a decision about implementing an IR, about 70% of PO respondents and 44% of PPT respondents say they are "very" or "somewhat" likely to do so.

Questionnaires asked IMP respondents how important the needs assessment was for accomplishing 11 IR-related tasks. Table 4.2 lists these tasks and the percentages of respondents who told us that the needs assessment is "very" or "somewhat" important for accomplishing them. More than 75% of respondents rate all but four tasks very high in importance. At the top of that list is "Formulating IR policies." Because "Making the decision to implement an IR" is close to the bottom of the list, we can presume that census institutions were not conducting the needs assessment to help them decide whether to implement an IR. Instead, they were conducting the assessment to discover the reception their IR would get from their institution's learning community. One write-in comment says as much:

• "This was not a traditional needs assessment. We knew were going to implement an IR and some of the needs assessment was carried out while planning the IR."

Table 4.2. Importance of the needs assessment

Rank	IR-related tasks	% Important
1	Formulating IR policies	90.0
2	Identifying first adopters of an IR	84.2
3	Recruiting digital content for the IR	83.3
4	Choosing an IR software package	82.4
5	Streamlining IR planning and implementation	82.4
6	Increasing faculty awareness of the IR	79.0
7	Identifying especially active contributors to the IR	77.8
8	Identifying new services to build onto the IR	72.2
9	Scheduling the rollout of various IR services	68.8
10	Making the decision to implement an IR	68.4
11	Identifying preservation techniques	62.5

A handful of respondents told us that faculty interest was key to proceeding with an IR and that they did not necessarily have to conduct a needs assessment to find signs of such interest. Here are their comments in this regard:

• "There was no needs assessment but the IR was very much faculty driven. Leadership was taken by the University Library Council (a senate-provostial advisory group) that pushed the agenda and prepared the report that led to provost funding and support."

• "Our assessment was more dynamic and ongoing … it involved response to innovative faculty requests and ongoing outreach from librarians regarding changes in scholarly communication practices, e.g., an e-publishing symposium hosted by the library author's rights issues."

• "Our former dean of faculty was particularly interested in DSpace and secured funding for the university libraries to implement and support its use here."

4.3 Pilot Testing IR Software Packages

The PPT and IMP questionnaires asked respondents to rate the importance of various benefits of pilot testing one or more IR-system software packages. To simplify results, MIRACLE Project staff assigned weights to response categories as follows: (+2) very important; (+1) somewhat important; (0) no opinion, don't know, or not applicable; (-1) somewhat unimportant; and (-2) very unimportant. They totaled the weights. These results were then compiled to rank order all the positions. Table 4.3 lists all 10 benefits in rank order. Except for the bottom-ranked benefit, the percentages of respondents rating benefits "very" or "somewhat" important are very high, ranging from 67% to 93%. Respondents are positive even about the bottom-ranked benefit, giving demonstrations to prospective partners, because almost 50% of them rate it "very" or "somewhat" important.

Table 4.3. Important benefits of pilot testing

Important benefits (1 to 5)	PPT	IMP
Identifying the strengths and shortcomings of available IR software	2	1
Developing the requisite technical expertise for IR implementation	1	2
Estimating costs for the technical implementation of an IR	3T*	3
Giving demonstrations to people involved in the IR implementation decision	5	4
Identifying first adopters of an IR at your institution	(6)	5
Less important benefits (6 to 10)	PPT	IMP
Preservation of your institution's intellectual output	(3T)	6
Gauging the interest of potential contributors to the IR	7	7
Control over your institution's intellectual output	9	8
Gauging the interest of potential IR-system users	8	9
Giving demonstrations to an institution(s) interested in partnering with us to encourage them in IR implementation	10	10
† Parentheses indicate PPT benefits that deviated from IMP top- and bottom-ranked benefits. * T indicates a ranked benefit that tied another benefit's weight.

The three top-ranked benefits—developing the requisite technical expertise, learning about IR software, and estimating costs—are very practical in terms of implementing an IR. Middle- to low-middle ranked benefits pertain to potential contributors and users of the IR. MIRACLE Project investigators thought benefits pertaining to contributors especially would be ranked higher in view of the difficulty in recruiting each (see Subchapter 6.5 and Appendix F8.4), but they were not. PPT and IMP respondents' lists of ranked benefits are almost the same. The only difference is that PPT respondents give greater importance to preserving their institution's intellectual output. Two write-ins comment on the importance of pilot testing for collection building:

• "Building an IR collection prior to production so that on [the] release [of our operational IR] it has apparent value."

• "Expanding student access to teaching materials in particular courses such as archaeology and botany."

Questionnaires asked PO respondents whether they were likely to pilot test one or more IR software packages prior to implementing an IR. Figure 4.2 graphs the results.

Almost two-thirds of PO respondents are likely to pilot test. Whether the one-quarter of PO institutions that are not pilot testing or the one-eighth of PO institutions that do not know whether pilot testing is in their future are skipping directly to implementation or terminating IR-related activities is revealed by their answers to a question about their next steps pertaining to the IR effort (see Subchapter 4.4).

4.4 Next Steps Pertaining to the IR Effort

The questionnaires asked PO respondents what steps they plan to take next as a direct result of their IR planning and asked PPT respondents what their next steps are as a direct result of their IR planning and pilot testing. Table 4.4 gives the results.

Table 4.4. Next steps pertaining to the IR effort

Next steps	PO	PPT
Your institution supports implementation of an IR software package	2	1
Your institution widens the scope of its investigation into IRs	1	2
Your institution seeks funding for the next step of investigation of IRs	3	3
Your institution seeks a partner institution(s) to share in an IR	4	4
Your institution waits for a consortium, network group, or similar to implement an IR	5	5
Your institution terminates its investigation of Irs	6	6

Ranked at or near the top for PO and PPT respondents are widening the scope of their IR investigations and implementing an IR software package, respectively. Both are logical next steps given their current stages in the IR effort.

Examining percentages of respondents' ratings conveys the strength of their convictions. Figure 4.3 graphs respondents' ratings for the top-two ranked answer categories—implementing IR software and widening the scope of planning investigations.

Two-thirds of PPT respondents at institutions said implementing IR software is "very likely" to be their next step. None says that IR software implementation is "very unlikely," and only a small percentage (2.6%) say such implementation is "somewhat unlikely." Clearly, almost all PPT respondents in the MIRACLE census will be going ahead with IR implementation.

About one-sixth of PO respondents say implementing IR software is "very likely" to be their next step. Almost 50% said it is "somewhat likely." Compared with PPT respondents, PO resondents are lukewarm about implementing IR software as their next step. Instead, widening the scope of their investigation into IRs is "very" (17.7%) or "somewhat" likely (54.4%) to be their next task.

Figure 4.4 graphs respondents' ratings for the two middle-ranked answer categories—seeking funding and seeking partners. Large percentages of PO (65.8%) and PPT (55.5%) institutions will be seeking funding as their next step. Although large percentages of PO (42.3%) and even larger percentages of PPT (51.8%) respondents say they are unlikely to seek partners for IR implementation, several write-in responses mention possible participation in state-funded IRs. Not knowing their next step is more characteristic of PO respondents, about 10% of whom are not sure whether seeking funding or partners will be their next step.

Results for the bottom-ranked next steps—waiting for consortial developments and terminating IR involvement—are shown in Figure 4.5. Almost equal percentages of PO institutions are likely and are not likely to wait for a consortium or other group to implement an IR. PPT institutions appear to be speeding ahead with IR implementation—hardly 16% are waiting for a consortium or other group to implement an IR while about 70% are not waiting.

Percentages of PO and PPT institutions likely to terminate their investigations of IRs are very low (10.3% and 11.2%, respectively). Some respondents misinterpreted a "very" or "somewhat" likely answer to this question to mean that they would be turning their IR investigation in a different direction, for example, toward IR pilot testing or actual IR implementation, instead of terminating all IR-related activities; consequently, the percentages of census respondents who are truly terminating may be even lower than the percentages represented in Figure 4.5. For the most part, PO and PPT respondents in the MIRACLE Project census will be continuing their institutions' IR efforts.

Figure 4.6 shows how long it will take PO and PPT respondents to make the decision to implement an IR. Overall, PO respondents will be taking longer than PPT institutions. For example, about three-quarters of PPT respondents will be making the decision within six months. The same proportion of PO respondents will be making this same decision within 12 months.

4.5 Chapter 4 Summary

Asked to rate a list of 12 investigative activities, PO, PPT, and IMP respondents put those associated with learning about IRs from the experiences of others at the top. For PPT and IMP respondents, this includes analyzing literature reviews (see Table 4.1). PO respondents rank "Demonstrating operational IRs to my institution's decision makers" much higher than PPTs and IMPs do. Such demonstrations probably make IRs more tangible to decision makers, and, possibly, more favorably inclined to support the IR effort in rhetoric and funding. In the middle of the pack is the needs assessment. Follow-up questions reveal one in sixteen PO, one in four PPT, and one in three IMP institutions, respectively, have conducted a needs assessment (see Figure 4.1). Between 5% and 12% of respondents do not know whether their institutions have conducted a needs assessment. Asked whether they are likely to conduct a needs assessment prior to making a decision about implementing an IR, about 70% of PO respondents and 44% of PPT respondents say they are "very" or "somewhat" likely to do so.

Questionnaires asked IMP respondents how important the needs assessment was for accomplishing 11 IR-related tasks (see Table 4.2). More than 75% of respondents rate all but four tasks very high in importance. At the top is "Formulating IR policies." Because "Making the decision to implement an IR" is close to the bottom of the list, it is likely that census institutions are not conducting the needs assessment to help them make the decision to implement an IR. Instead, they are conducting it to discover how their institution's learning community will react to the IR.

Rating the importance of various benefits of pilot testing one or more IR-system software packages, most PPT and IMP respondents choose benefits that are very practical in terms of implementing an IR—developing the requisite technical expertise, learning about IR software, and estimating costs. Middle- to low-middle ranked benefits pertain to potential contributors and users of the IR (see Table 4.3).

Census respondents in the PPT stages of the IR effort are downright positive about implementing an IR at their institutions (see Subchapter 4.4). Their next steps are widening the scope of planning activities or implementating an IR. Most will not be waiting for a consortium, partner, or group of libraries; instead, they prefer to do IR implementation on their own. Very few will be terminating all IR-related activities.

5 IR SYSTEMS AND FEATURES

Chapter 5 tells how many institutions with institutional repositories (IRs) are implementing the IR-system software packages they have chosen, describes system features that respondents believe are satisfactory and less than satisfactory, and explains why and when IMP respondents would migrate to a new IR.

5.1 Number of IRs at Institutions

On planning and pilot testing (PPT) and implementation (IMP) questionnaires, the first question asked respondents how many IRs were available or would be available to their institution's learning community in the near future. Table 5.1 lists the results.

Table 5.1. Number of IRs

Number of IRs	PPT		IMP
Number of IRs	No.	%	No.	%
1	50	72.5	37	77.1
2	12	17.4	8	16.6
3	4	5.8	3	6.3
4	1	1.4	0	0.0
5 or more	2	2.9	0	0.0
Total	69	100.0	48	100.0

Most PPT and IMP institutions have one IR, but almost a quarter have two or more IRs. PPTs probably have more than one IR because they are pilot testing IR-system software packages. Also, PPTs and IMPs may be counting the academic departments and research units that have launched IR-like software to preserve, exchange, and distribute research and teaching objects among themselves, to colleagues at other schools, and to Web searchers generally. This project's phone interviews and case studies should ask follow-up questions to determine whether institutions with multiple IRs will eventually centralize IR services and, if so, which IR they will choose for centralization.

After respondents answered the first question, questionnaires instructed them to answer the remaining questions with the one IR in mind that offered the widest array of services to the most people and greatest number of constituencies.

5.2 IR Software

Table 5.2 enumerates the IR-system software packages that PPT and IMP respondents have pilot tested and implemented.

Table 5.2. Pilot-tested and implemented IRs

System	PPT Pilot-tested IRs		IMP Pilot-tested IRs		IMP Implemented IRs
System	No.	%	No.	%	No.	%
Dspace	31	27.9	13	40.7	19	46.4
ContentDM	22	19.8	2	6.2	2	4.9
Fedora	15	13.5	3	9.4	0	0.0
Greenstone	6	5.4	3	9.4	0	0.0
Luna	6	5.4	0	0.0	0	0.0
Bepress	5	4.5	4	12.5	11	26.8
ProQuest	4	3.6	0	0.0	5	12.2
Innovative Interfaces	4	3.6	0	0.0	0	0.0