Disappearing repositories – taking an infrastructure perspective on the long-
term availability of research data

  * Dorothea Strecker1 (corresponding author)
<EMAIL_ADDRESS>
0000-0002-9754-3807

  * Heinz Pampel1,2
0000-0003-3334-2771

  * Rouven Schabinger3
0000-0002-0249-7917

  * Nina Leonie Weisweiler2
0000-0001-6967-9443

1 Humboldt-Universität zu Berlin, Berlin School of Library and Information
Science

2Helmholtz Association, Helmholtz Open Science Office

3Swiss Library Service Platform (SLSP)

## Abstract

Currently, there is limited research investigating the phenomenon of research
data repositories being shut down, and the impact this has on the long-term
availability of data. This paper takes an infrastructure perspective on the
preservation of research data by using a registry to identify 191 research
data repositories that have been closed and presenting information on the
shutdown process.
The results show that 6.2 % of research data repositories indexed in the
registry were shut down. The risks resulting in repository shutdown are
varied. The median age of a repository when shutting down is 12 years.
Strategies to prevent data loss at the infrastructure level are pursued to
varying extent. 44 % of the repositories in the sample migrated data to
another repository, and 12 % maintain limited access to their data collection.
However, both strategies are not permanent solutions.
Finally, the general lack of information on repository shutdown events as well
as the effect on the findability of data and the permanence of the scholarly
record are discussed.

## Keywords

research data ; research data repository ; infrastructure maintenance ;
scholarly record

##  1 Introduction

With the number of published research data steadily increasing [80], the long-
term preservation of datasets is gaining importance, especially if research
data are to be regarded as self-contained components of the scholarly record
[116]. For this idea and data citation to succeed, continuous access to
datasets is required, since in order for datasets to become citable units,
they must be permanently available [84]. Concerns about perpetual access to
digital scholarly texts have resulted in the establishment of a distributed
network of preservation services that is maintained jointly by various
stakeholders [120]. However, the adoption of these preservation services is
slow compared to the growth in the number of academic journals, and some
journals have been shut down and disappeared [112]. Research data might be
even more vulnerable, as the burden of long-term preservation rests
predominantly on dedicated repositories – preservation systems comparable to
those for scholarly texts currently are not widely spread and can be difficult
to realize [107].
Long-term preservation of research data requires not only continuous care of
datasets, but also of the repositories that hold them [95]. The TRUST
Principles, a set of guiding principles for research data repositories
formulated by a multi-stakeholder group, ask repositories to “ensure
uninterrupted access to [their] valuable data holdings for current and future
user communities”[115, 3]. To meet these expectations, repository operators
need to find solutions for infrastructure maintenance, governance, securing of
funding, and continuity planning. The long-term operation of research data
repositories presents a challenge, and sometimes, for varying reasons and
despite best efforts, research data repositories are shut down.
Beyond case studies of individual repositories or selected disciplines, there
is currently little research investigating the phenomenon of research data
repositories being shut down and the impact this has on the long-term
availability of data [83]. To address this issue, this paper identifies
research data repositories of all types and from all disciplines that have
been closed and presents information on the shutdown process.
Based on metadata from a registry of research data repositories and
information collected from repository websites, this paper takes an
infrastructure perspective on the long-term preservation of research data. The
following questions are addressed:

  * •

How common is the phenomenon of research data repositories being shut down?

  * •

What are the risks that lead to repositories being shut down?

  * •

What measures are taken to prevent data loss when repositories are shut down?

The paper concludes with reflections on how repositories and registries can
contribute to better documentation of repository shutdown and data migration.

##  2 Background

###  2.1 Research data repositories

Infrastructures are “pervasive enabling resources in network form” [82, 98].
They permeate specific areas of life and support certain practices [111]. In
the area of knowledge work, information infrastructures form “robust networks
of people, artifacts, and institutions that generate, share, and maintain
specific knowledge about the human and natural worlds.” [94, 17] Research data
repositories are specialized information infrastructures that focus on the
curation, preservation, and dissemination of research data [83, 94, 102]. They
facilitate data journeys – the movements of data from the sites of production
to the sites of (re-)use – and are central components for realizing the vision
of habitual data publication, a fundamental Open Science practice [74, 79].
Although studies on researchers’ attitudes towards publishing their data in
repositories are still inconclusive [136], there is evidence that the use of
research data repositories to make data available has increased in recent
years [101, 106]. Research data repositories shape and are shaped by the
communities they serve. They can become sites of scientific collaboration by
enabling researchers to gather around datasets they jointly use [89, 113,
127], and might have to adapt services if the designated community it serves
shifts over time [92]. At a global level, the landscape of research data
repositories has continuously evolved. Driven by the ideal of promoting Open
Access to scholarly publications, the number of repositories increased
significantly between 2005 and 2012 [126], initially focusing on text
publications. Later, infrastructures specialized in the management of research
data gradually emerged, forming a global network of heterogeneous research
data repositories [109]. In 2023, the global registry re3data lists more than
3.000 research data repositories. Different types of research data
repositories have evolved to serve specific needs, for example institutional
repositories that support members of research and higher education
organizations [72], discipline-specific repositories that address researchers
from a particular research area [77], or generalist repositories, which allow
the storage of data irrespective of discipline [131].
Overall, the publication of research data appears to be characterized by
concentration tendencies. For example, a recent study of a data discovery
service found that only 20 repositories accounted for almost 80 % of the total
datasets indexed [80]. Most research data repositories are also operated by
institutions located in Europe and North America [109], and in the last few
years, European research data repositories have grown substantially in size
[90]. The number of repositories in Africa, Asia, and BRICS countries has
increased in recent years, but operators of these repositories sometimes find
it challenging to fully realize their visions, for example if funding or
institutional support are lacking [71, 86, 121, 123].

###  2.2 Long-term operation of research data repositories

####  2.2.1 Time scales of research data repositories

Time is a challenge for all types of infrastructures, because they operate at
two different time scales at once: They must both be usable now and remain
usable in the long term. As Karsati et al. put it, “an infrastructure occurs
when here-and-now practices are afforded by temporally extended technology”
[104, 400]. Both time scales can threaten the existence of a research data
repository – it might be shut down if it is unable to serve current needs and
practices, or if it can’t offer reliable services over a long period of time.
Repository operators are aware of these time scales, as many have expressed
concerns both about the long-term maintenance of their repository and the
ability to develop new functionalities [105].
A research data repository also has to bridge another time gap: The varying
life spans of its technical components and its data collection. Likely, the
life span of a data collection is longer compared to the technical components
required for its preservation: “data collections accrue slowly and steadily,
yet software and hardware can change relatively rapidly and are beyond the
control of collection staff responsible for data collection.” [137, 4]
Therefore, in order to preserve data collections, the research data
repositories storing them must also be maintained.

####  2.2.2 Risks to the long-term operation of research data repositories

Planning for the long-term preservation of research data is challenging,
because various factors can put both the data and the repository that holds
them at risk [140]. Research data are at risk of being lost if the research
data repository is threatened, for example if it is facing loss of funding
[118]. In interviews, developers and auditors of repository standards as well
as repository staff identified five potential sources of risk: finance, legal,
organizational governance, repository processes, and technical infrastructure
[98]. Barateiro et al. developed a comprehensive typology of risks to digital
long-term preservation systems, such as research data repositories [78, 8ff].
The typology lists vulnerabilities (“weaknesses […] in the environment”) and
threats (“events that affect normal behaviour”) that can adversely impact
components of these systems (see Table 1). Vulnerabilities can be introduced
to preservation systems either by software (process), by characteristics of
the information objects being preserved (data), or by the infrastructure
(infrastructure). Preservation systems can be threatened by non-deliberate
actions (disasters), deliberate actions (attacks), managerial decisions
(management), or changes in laws (legislation).

vulnerabilities |  process |  software faults
---|---|---
software obsolescence
data |  media faults
media obsolescence
infrastructure |  hardware faults
hardware obsolescence
communication faults
network service failures
threats |  disasters |  natural disasters
human operational errors
attacks |  internal attacks
external attacks
management |  economic failures
organizational failures
legislation |  legislative changes
legal requirements
Table 1: Typology of risks to long-term preservation systems, [78, 9]

Risks to the long-term operation of research data repositories have long been
discussed in the literature, in particular the risk of economic failure [87].
Concerns about funding cuts that threaten databases in the life sciences have
been raised for years [76, 119]. If funding for databases is discontinued,
entire research communities in the life sciences can be impacted, as the cases
of the Biological Magnetic Resonance Bank (BMRB) [122], EcoCyc [130], and
Online Mendelian Inheritance in Man (OMIM) [103] exemplify. In these cases,
researchers who used the repositories publicly called to save the databases,
as they were considered essential resources. These initiatives were
successful, since the databases were still operational at the time this paper
was written. Economic sustainability remains a major concern today [97],
although the funding of research data repositories has become more reliable in
part [85]. Revenue streams of research data repositories can change over time
[96], but still depend predominantly on publicly funded organizations [100].
Repositories also try to reduce technical risks (process and infrastructure
vulnerabilities) [95]. Generally, infrastructures such as research data
repositories can be adapted and reconfigured, but the “installed base”,
components they build on, might limit this flexibility and therefore pose a
risk [99]. These limits can contribute to tensions between building something
new and maintenance work [128].
Ensuring the sustainability of a research data repository is a continuous
process [95]. Despite this fact and the importance of infrastructure
maintenance for the long-term preservation of data, it is not explicitly
included in widely used models of digital curation, for example lifecycle
models or the OAIS reference model [138].

###  2.3 Research data repositories being shut down

One characteristic of infrastructures in general is that they are often taken
for granted and only noticed once they break down [132, 113]. This is also
true for information infrastructures such as research data repositories, but
the point when they “shut down” is not always clear cut; for example, the
information infrastructure can be closed entirely, scaled down, or
disassembled into components that are repurposed later [133].
Despite careful planning, a research data repository might be closed
eventually [91]. Currently, there is little evidence of how often this
phenomenon occurs. A study of biological databases found that after a period
of 18 years, 75 % were either closed entirely or the content was no longer
updated [73], but this high rate of shutdowns might not translate to other
repository types or disciplines. In another case, a consortial repository was
closed after former consortium members gradually reorganized research data
management and moved their data to institutional repositories [91]. A recent
study evaluated link rot in four registries of scholarly infrastructures but
only provided limited evidence of de facto repository availability [117].
Generally, shutting down an information infrastructure should not be
considered a failure, because it is “a highly reflective and introspective set
of practices” [133, 2205] that generates new insights, which can be very
useful for future undertakings.
If a repository is integral to the mission of the hosting institution, it is
more likely to receive long-term institutional and financial support [73]. An
institution’s mission might often outlast the lifetime of a repository, and,
therefore, the institution should make arrangements for the event that a
repository has to be closed [91]. If anticipated, the shutdown of a repository
can be planned and the stored datasets can be migrated to another repository,
while sudden closure might result in permanent data loss [83]. Therefore, to
ensure continuity of access to data, the repository certification organization
CoreTrustSeal asks applicants to consider succession planning, the
“preparations for handover of digital objects and services to another
repository” [88, 13].
Migration of data sources is a demanding task, as discrepancies between the
legacy and the new system must be overcome [124]. Although migration is likely
common among long-lived research data repositories [138], it is unclear how
prevalent the strategy is. The study of biological databases referred to above
found that after 18 years, 7 % of the databases had been migrated to new sites
[73], but it only covers infrastructures of one discipline. Migration is often
initiated in response to changing needs, both of repository operators and
users, with the intention to improve repository content, service and
management [140, 139].

###  2.4 Closed repositories in registries

In a time frame similar to the emergence of repositories, specialized
registries collecting information about them have evolved. Presently, there
are several of these services that differ in the types of repositories they
cover, the metadata schemas they use to describe them, as well as the
stakeholders and use cases they serve. The records registries maintain can
facilitate repository use, but also monitoring activities. Because repository
registries collect information on information infrastructures, they can also
be valuable resources for research.
Depending on their mission, registries approach repository shutdowns
differently. For example, the registry OpenDOAR focuses on active Open Access
repositories. The inclusion criteria of the service state that a repository
“must be currently and reliably accessible to any web user around the world”
to be indexed.111OpenDOAR inclusion criteria:
https://v2.sherpa.ac.uk/opendoar/about.html If editors become aware of a
repository shut down, the record of that repository can be made invisible to
the public.
In contrast, the registry FAIRsharing, originally focused on databases in the
life sciences, does keep record of repositories that have been shut down,
since one objective of the service is to monitor the evolution of the objects
they describe [129]. The metadata schema therefore reflects the status of
repositories, which can be one of _ready_ , _in development_ , _uncertain_ or
_deprecated_. If a repository is deprecated, a date and a reason can be
specified.222FAIRsharing record schema:
https://fairsharing.github.io/JSONschema-
documenter/?schema_url=https://api.fairsharing.org/model/fairsharing_record_schema.json
The registry re3data also aims to describe the developments of the global
landscape of research data repositories, including the emergence and shutdown
of these infrastructures [125]. As a result, re3data documents the trajectory
of the global repository landscape over time by representing information on
the lifespan of a repository via the elements startDate and endDate in the
re3data Metadata Schema [134, 10]:

  * •

_startDate_ The date the research data repository was released

  * •

_endDate_ The date the research data repository ended its service of ingesting
new research data and/or providing it.

##  3 Methods

###  3.1 Extracting repository descriptions from re3data

Due to their overlapping missions, there are considerable intersections
between collections of repository registries [75]. Data collection for this
analysis is based on the registry of research data repositories
re3data333re3data: https://doi.org/10.17616/R3D, because it is currently the
most comprehensive source of information on repositories with a clear focus on
research data. Currently, it covers more than 3.000 repositories of all types
and from all disciplines. The service was launched in 2012 and therefore has
recorded information on the repository landscape for more than 10 years.
Repositories are indexed by an international editorial team based on a
comprehensive metadata schema. re3data metadata is available under an open
license (Creative Commons CC0 1.0 Universal444Creative Commons CC0 1.0
Universal: https://creativecommons.org/publicdomain/zero/1.0/) through an open
API.

###  3.2 Defining inclusion criteria

It can be difficult to determine whether a repository is permanently closed –
for example, a repository might reopen after being shut down for maintenance,
or the repository homepage might have been moved to a new URL [73]. In
addition, research data repositories have multiple temporal properties, such
as a life span and temporal coverage, and they can be difficult to
differentiate when attempting to determine what constitutes a closed
repository.
In this paper, a repository is considered shut down if data is no longer
accessible under the original or a new URL, or if the repository website
clearly states that the service has ceased operations (while sometimes
maintaining very limited access to the data). This definition refers to the
life span of a repository and does not relate to the temporal coverage of its
collection, unless the website explicitly states that the data are deprecated.
It is important to recognize the ambiguity of the term _closed_ in the context
of research data repositories. In this paper, _closed_ does not refer to
restrictions placed on access to data or repository services, but only to the
status and life span of repositories.

###  3.3 Collecting data

The analysis draws on re3data repository descriptions and supplements it with
information collected from repository websites.
To identify candidates for closed repositories, information on the end date of
the 3.069 repositories indexed in re3data was retrieved via the API on 2023,
January 2. As shown in Figure 1, this list was then restricted to repositories
with an end date; this produced a list of 223 candidate repositories. The list
of candidates was reviewed by the authors. After visiting the website of each
repository on the list, duplicate entries (7) were removed, as well as
repositories that did not meet the inclusion criteria for defining closed
repositories given above (25).

Figure 1: Process of identifying closed repositories

For the remaining 191 repositories, information on the start and end date
(year) was retrieved from re3data on 2023, January 2. Given that these
properties are optional in the re3data Metadata Schema, the values were
verified intellectually and completed where possible. Between 2023, January 2
and 30, repository websites, both the current version and versions archived by
the Internet Archive, as well as additional resources such as data papers
describing the repositories were searched for information on the shutdown
process. The content analysis of these materials focused specifically on the
reason for shutting down and information on the repository taking over custody
of the data. This information was collected for each repository in the sample,
and, in addition, the availability of data on the current repository websites
was checked. The statements providing reasons for shutting down the repository
were generalized and summarized into categories based on the typology of risks
to preservation systems developed by Barateiro et al. in Table 1 [78]. A
similar approach was used previously to study risks to research data in
laboratory settings [110].
On 2023, January 30, the type and subject of the closed repositories was
retrieved via the re3data API to contextualize the findings [134, 10–11]:

  * •

_type_ The type of the research data repository. (for example: disciplinary,
institutional)

  * •

_subject_ The disciplinary focus of the research data repository. (based on
subject areas defined by the German Research Organization DFG555Subject areas
defined by the DFG:
https://www.dfg.de/en/dfg_profile/statutory_bodies/review_boards/subject_areas/)

The final dataset is openly available [135].

##  4 Results

###  4.1 Prevalence of the repository shut down and time series analysis

An analysis of the end dates in the sample indicates that re3data has recorded
191 repositories that were closed, with the years of shutdown spanning a
period of 25 years. At the time of data collection, this constitutes 6.2 % of
all repositories indexed in re3data (3.069).
The first repository in the sample was shut down in 1999, the next closure
occurred after a pause of several years in 2005 (see Figure 2). This is
probably linked to the history of re3data – the service officially took up
operations in 2012, and coverage of repositories being shut down before that
date is likely sparse. The growth in the number of closed repositories has
been fairly consistent from 2012 onward. As of the end of the data collection
phase, one repository was closed in 2023.

Figure 2: Number of closed repositories indexed in re3data (cumulative)

Both a start and end date could be identified for 158 closed research data
repositories. Those repositories had been operational between 1 and 57 years
before being shut down. The median age of a repository when shut down was 12
years.

###  4.2 Characteristics of closed repositories

As Figure 3 shows, most repositories that were shut down are disciplinary and
specialize in data from the life sciences and natural sciences. Compared to
all repositories indexed in re3data at the time of data collection,
repositories with these characteristics are also overrepresented in the
sample. It is important to note that both properties (_type_ and _subject_)
can be repeated in re3data, so a repository might be assigned more than one
type or subject; these combinations are reflected in the Venn diagrams.

Figure 3: Types (A) and subjects (B) of closed repositories in re3data

A comparison of the 25th and 75th percentile of the age distribution of closed
repositories shows that compared to long-lived closed repositories,
repositories with a shorter life span (25th percentile) were more likely
institutional and had a focus on humanities and social sciences (see Table 2).
In contrast, long-lived closed repositories (75th percentile) were more likely
disciplinary with a focus on life sciences.

type |  | 25th percentile | 75th percentile
---|---|---|---
disciplinary | 81.6 % | 95 %
institutional | 23.7 % | 7.5 %
other | 13.2 % | 12.5 %
subject |  | 25th percentile | 75th percentile
humanities and social sciences | 26.3 % | 5 %
life sciences | 47.4 % | 57.5 %
natural sciences | 47.4 % | 47.5 %
engineering sciences | 10.5 % | 7.5 %
Table 2: Proportion of type and subject of closed repositories in the 25th
(short-lived) and 75th (long-lived) percentile of the age distribution

###  4.3 Risks resulting in repository shutdown

The reasons given for the closure of the repository were matched to the
typology of risks to preservation systems by Barateiro et al. [78]. As Table 3
shows, for the majority of closed repositories in the sample (62.5 % ; 120), a
reason for the shutdown could not be determined.
For the remaining 71 repositories, 77 risks could be identified. Among them,
threats (66) were more likely than vulnerabilities (11) to result in shut
down, meaning that for these repositories, shutdown can be attributed to
specific events rather than weaknesses in the environment. The most common
risks that led to shutdown were managerial threats in nature (64), either due
to organizational failure (37) or economic failure (27). Examples for
organizational failure include repository shutdown as part of broader
reorganization initiatives within the operating organization, or because the
mission of the repository was considered fulfilled. Economic failures cover
all types of funding cuts, including the cessation of project-related funding.
Vulnerabilities of repository technology lead to 5 repositories closing;
because repository websites and related materials provided no additional
information, both hardware and software obsolescence were identified as risks
in these cases. Threats introduced by external attacks, for example hacking
incidents, resulted in repository shutdown in two cases. In one case,
vulnerabilities due to media obsolescence lead to repository shutdown – the
research data were considered obsolete and were no longer maintained. Reasons
rooted in both vulnerabilities of technology and threats of economic failure
were cited by one repository.

risk |  description |  number of repositories
---|---|---
NA |  no information available |  120
threats - management - organizational failures |  repository was shut down as part of broader reorganization initiative within the operating organization, or because its mission is considered fulfilled |  37
threats - management - economic failures |  repository was closed because funding was cut |  27
vulnerabilities - infrastructure - hardware obsolescence |  repository was closed because of technological difficulties |  5
vulnerabilities - process - software obsolescence |  repository was closed because of technological difficulties |  5
threats - attacks - external attacks |  repository was closed because of acute hacking or security incidents |  2
vulnerabilities - data - media obsolescence |  repository was closed because the data is considered obsolete |  1
Table 3: Risks resulting in repository shutdown (more than one reason
possible)

###  4.4 Risk of data loss

The analysis revealed that for 88 % (168) of the repositories in the sample,
data was no longer available on the repository website. 23 (12 %) repositories
still maintained access to data in a limited capacity, for example via a
simple FTP interface. Maintenance of data and access services beyond that,
including search interfaces, had been ceased. 44 % (84) of the repositories
have listed a repository that has taken over custody of the data. Data loss
might have occurred at the closure of 90 (47.1 %) repositories; these
repositories did not maintain (limited) access to data or name a repository
that had taken over custody of the data.
One of these cases with a high risk of data loss concerns the repository
BIIACS666BIIACS: https://doi.org/10.17616/R3ZG6K. The repository had acquired
certification from Data Seal of Approval (DSA), a now discontinued predecessor
of the repository certification organization CoreTrustSeal. The repository was
launched in 2008, certified by DSA in 2013, and shut down in 2018. It is
unknown why the repository was shut down. In the self-assessment document
submitted to DSA, the repository expressed “a commitment to maintain the
perpetuity of the data with the highest standards, as part of [its]
mission”[114]. However, as of today, the data are no longer accessible from
the repository website and no repository taking over custody of the data was
named. The handles the repository issued to ensure persistent identification
of content no longer resolve today.777Example of a handle that no longer
resolves: http://hdl.handle.net/10089/17040

###  4.5 Data migration

For 84 (44 %) closed repositories, evidence of data migration was found. In
the sample, 75 repositories are listed that have taken over custody of data.
Most (60) of these substituting repositories were listed only once, but some
were mentioned two (10), three (3) and four (2) times. Three of the
repositories mentioned most frequently (PubChem888PubChem:
https://doi.org/10.17616/R3KG65 (4), Gene Expression Omnibus999Gene Expression
Omnibus: https://doi.org/10.17616/R33P44 (3), and
ArrayExpress101010ArrayExpress: https://doi.org/10.17616/R3302G (3)) are
large, disciplinary repositories that were established around 20 years ago and
are well-known by researchers within the discipline.
8 instances of data migrations reflected in the sample are part of a large-
scale reorganization of toxicology data providers within the US National
Library of Medicine (NLM) in 2019, where the content of toxicology resources
was integrated into other NLM sources [81]. Information on chemicals was
migrated to PubChem, which affected four repositories in the sample. Data
migrations were announced beforehand and are well documented [108]. A database
transition page is still maintained today.111111NLM toxicology database
transition page: https://www.nlm.nih.gov/toxnet/index.html
The analysis revealed that there are three cases in the sample where custody
of data was transferred to a repository that was later shut down (see Figure
4). In case 1, the chain of custody potentially ended with the new repository
closing, because no evidence was found that the data was migrated again. In
the other two cases, data was migrated again to repositories that are still
operational today, resulting in a chain of transfers of data custody that is
still intact. Figure 4 shows that in some cases, after a repository was shut
down and the data migrated to a new repository, that repository proceeded to
be closed in the same year.

Figure 4: Cases where data was migrated to a new repository that was later
shut down; the chain of custody ends in case 1 and continues in cases 2 and 3

##  5 Discussion

###  5.1 Life span of research data repositories

Overall, the emerging landscape of research data repositories is dynamic, with
new repositories opening and others being shut down. The analysis showed that
research data repositories are shut down fairly frequently: 6.2 % of the
repositories indexed in re3data have been closed. Since re3data took up
operations in 2012, repository closures were recorded each year. Consequently,
a repository shutdown is not a rare event. As suggested in the literature,
shutdown should be considered an expected part of the repository life cycle
[91]. It is normal for conditions of data movements to change [79], and
repository shutdown does not have to be a negative outcome. It can be an
appropriate measure that might even result in new insights for the future
[133].
In the sample, the median age of a repository when closing is 12 years. This
limited life span could potentially put research data at risk and should be
considered when defining retention periods for the long-term preservation of
research data. Because repository shutdown is a real threat, infrastructure
maintenance should also be reflected in models of digital preservation, and
shutdown scenarios planned in advance.
Some closed repositories had particularly long or short life spans. A
comparison of top and bottom percentiles of the age distribution revealed
differences in type and subject specialization of these long- and short-lived
repositories. The sample of closed repositories indicates that disciplinary
repositories catering to the life sciences might be more successful at staying
operational long-term. However, there are also active long-lived repositories
in other disciplines; for example data archives in the social sciences that
have been established in the 1960s and are still operational today [93].
Therefore, more research is needed to fully understand this relationship,
particularly studies that also consider active repositories with long life
spans.
The risks that result in the shutdown of repositories are varied. Some might
be anticipated and planned for in advance, such as organizational changes
within broader reorganization initiatives, whereas others might not, such as
threats from acute security incidents.
As described above, infrastructures operate at different time scales at once
by serving current needs and practices while also providing reliable long-term
services. It is not clear from the analysis whether long- or short-term
requirements put repositories at risk of shutdown more frequently. For
example, managerial decisions to reorganize resources within an institution
might be motivated by efforts to provide more comprehensive services for
current users, or by an attempt to conserve resources in the long term.
Overall, more research is needed to determine factors that put research data
repositories at risk of being shut down, and how they can be addressed.
However, for most repositories in the sample, the risks resulting in shutdown
are unknown. The issue of missing information on repository shutdowns is
discussed in more detail below.

###  5.2 Identifying closed repositories

Reviewing repository websites during data collection has demonstrated that it
can be difficult to determine whether a repository is permanently shut down.
In part, this is due to the fact that a repository has multiple temporal
properties, such as a life span and temporal coverage of its collection. These
properties are distinct but can be difficult to separate in some cases. For
example, a repository might have stopped ingesting new data at a certain point
in time, but still maintain access to its collection. Depending on the
context, the data might then be considered deprecated, or it might have
retained its analytical potential, for example as historical data for time
series analysis. Future research could further investigate the interrelation
between temporal coverage and life span of research data repositories.
Another factor complicating the identification of closed repositories is the
lack of information on planned downtime. A repository might be temporarily
unavailable, for example due to maintenance activities. In case of prolonged
downtime periods where no information on the maintenance schedule is given on
the repository website, repository users might assume the repository is
permanently closed and report this to registries. In the sample, there was at
least one repository that had an end date in re3data, but came back online
after an unannounced downtime period.121212TreeBASE:
https://doi.org/10.17616/R3DK58 Repositories can avoid this by announcing
planned downtime on their websites.

###  5.3 Strategies for preventing data loss

The analysis of information collected from repository websites focused on two
strategies for preventing data loss when a repository is shut down:
Maintaining limited access to data and migrating data to another repository.
The results show that these strategies are used by repositories to varying
degrees.
Most repositories do not uphold access to data when they are shut down, often
leaving no trace of the repositories or their contents on their websites. Only
few repositories opt to maintain limited access to data, for example via a
simple FTP interface. This strategy, however, is not a permanent solution,
since all curation and long-term preservation activities have been
discontinued. If no measures are taken to preserve individual datasets, it
becomes more likely as time passes that data will no longer be usable. In
addition, browser support for FTP is declining, which might limit human access
to data in the future.
In contrast, the strategy of migrating data to another repository is more
common, being used by almost half of the repositories in the sample. Overall,
this strategy is more likely to retain the usefulness of data, because the
repositories that have taken over custody of the data can apply appropriate
curation and preservation measures. However, this strategy should not be
considered definitive either, as the burden of infrastructure maintenance is
not eliminated but transferred to the succeeding repository. This is
demonstrated by three cases of chaining of data migration, meaning that
custody of data has been transferred several times. In two of these cases, the
chain of data custody remained intact, but in one case it ended because the
repository that had ingested the data was shut down without indicating a
successor.
Some repositories seem to have established themselves as reliable options for
taking over custody of data, given that they have ingested data from multiple
repositories that were shut down. These tend to be large repositories with a
disciplinary focus and a comparatively long life span. They seem to have
become central infrastructures for the research domain they focus on while
also serving as a safe haven for data collections from other repositories.
Future research should critically investigate the long-term consequences of
data migration. For example, data migration conducted within larger
reorganization efforts can affect a number of repositories and result in a
consolidation of the repository landscape, by combining collections into
large, central repositories. Central repositories might be able to use limited
resources more efficiently, but could also create single points of failure if
they come at risk of being shut down themselves.
Other measures also have the potential to reduce the risk of data loss, for
example repository certification. One repository in the sample acquired formal
certification from DSA, but was shut down despite the stated commitment to
ensuring long-term availability of data, demonstrating that obtaining
certification is no guarantee that a repository will stay operational long-
term. However, the certification process can require repositories to provide
evidence of sustainable operations and succession planning, encouraging them
to implement appropriate measures. The same case also highlights the
limitations of another measure to ensure sustained access to data: The use of
persistent identifiers. Persistent identifiers are very useful for reliably
referring to research data, but they have to be maintained to function as
intended.

###  5.4 Documenting repository shut downs and changes in data custody

The analysis demonstrates that most repositories completely disappear after
being shut down: They maintain neither limited access to data nor a web page
with information on the shutdown process or potential data migration. This
lack of information can have serious consequences for data citation and the
permanence of the scholarly record. If research data are reused and cited, but
later become unavailable due to the repository shutting down, references can
break, which erodes the scholarly record. This is especially the case if no
information about the repository shutdown or data migration is shared.
An example of how information on repository shutdown can be provisioned is the
comprehensive reorganization of toxicology information within the NLM. Even
years after the initiative was concluded, the NLM maintains a database
transition page, a website that provides information on the reorganization
process. The initiative was announced in advance, and data migrations are
documented in detail, enabling researchers to trace datasets to the sites they
are stored at now.
Registries can contribute to making information on repository shutdown and
changes in data custody accessible. As services that collect information on
research data repositories and their trajectories, they are uniquely
positioned to do so. For example, re3data currently indicates whether a
repository was closed, and when. The most recent version of the re3data
Metadata Schema, version 4.0, introduces the option to reflect transfers of
data custody [134], which will make data migration visible in the registry.
To realize this vision of more comprehensive information on repository
shutdown, repository operators should consider being more transparent about
the process. By providing information on the shut down process beforehand and
naming the succeeding repository if the data were migrated, they can increase
transparency, help researchers trace chains of data custody, and inform other
repository operators.

##  6 Conclusion

The analysis showed that research data repository shutdown is not a rare
phenomenon but should be considered an integral part of the life cycle of
repositories. Repository shutdown poses a real threat to the perpetual
availability of research data. Therefore, when planning preservation measures,
repository operators should also take into account the infrastructure
perspective on the long-term availability of data. Planning ahead increases
the chance of saving data in case the repository is forced to shut down.
Strategies like data migration can prevent immediate data loss but should not
be considered permanent solutions. To more fully reflect the landscape of
research data repositories and support the integrity of the scholarly record,
registries can document repositories shutting down as well as changes in data
custody. Overall, more research is needed to evaluate strategies for
preventing data loss and to understand how specific factors affect the risk of
repository shutdown, for example how deeply a repository is embedded in its
community, its revenue streams, and its ability to respond to both short- and
long-term shifts in user needs.

## Limitations

Since re3data took up operations in 2012, re3data records likely don’t
document all incidents of repositories being shut down before that time. The
analysis is based solely on information that is publicly available online.
Most closed repositories have provided only limited or no information about
the shutdown process, therefore, data migration events or reasons for shutting
down are likely underreported.

## Funding information

This work has been supported by the German Research Foundation (DFG) under the
project _re3data COREF_ (Grant ID 422587133).

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