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##  Appendix A Search Methodology

###  A.1 Identification and Information Sources

To find relevant papers for our survey, we conducted a systematic search in
six major scientific databases in computer science (Springer, Wiley Online
Library, ScienceDirect, ACM digital library, IEEE Xplore, EBSCO host between
November $23^{rd}$ and December $01^{st}$, 2019) using 23 search queries
capturing the different terms used to describe a wall-sized display (e.g.
“visualization wall”, “tiled display”, etc.). The methodology steps are
summarized in an adapted PRISMA [MLT∗09] study flowchart (Figure 17).

We used general search queries such as (“immersive analytics” AND “data
visualization”) and specific keywords like “wall-sized display” to ensure a
broad bibliographic search. The queries were executed on the full text with
filters on conferences and journals while ignoring any other types of
publication like book chapters (except for EBSCO-host). We have also entered
these queries in singular and plural forms when the search engine did not
support lemmatization natively (Wiley Online library, IEEE Xplore and EBSCO-
host).

Figure 17: Flowchart of our systematic search adapted from PRISMA [MLT∗09].
Figure 18: Papyrus software [MGN16] showing (a) a map of topics extracted from
the scientific corpus of 701 papers, (b) $14$ shoeboxes created with the
related number of papers, (c) a subset of papers assigned to the shoebox
related to textual data with the annotation mechanism.

We exported all query results to a spreadsheet with the metadata for each
record: title, year, DOI, conference or journal name, abstract, authors,
keywords, search query and database. We used the "export" functionality in
each database when available. We also developed a Web scraper to extract paper
abstracts from the ACM digital library and Springer library.

###  A.2 Screening and Selection Criteria

##### Removing duplicates and papers without abstracts

The initial spreadsheet included 13,613 records. Some data curation was
carried out to fix character encoding issues. After cleaning and merging
duplicate entries, the number of records was reduced to 8,632. Then, we
excluded papers having no abstracts considering they lacked scientific
contribution (e.g. calls for participation, proceedings front matter, and
keynotes). 521 records were excluded consequently and a total of 8,111 records
were retained.

##### Screening based on the relevance

Using a visual text mining tool, Papyrus [MGN16], to visually inspect this
corpus (see Figure 18-a), we identified topics that were irrelevant for our
literature review e.g. biological conferences where papers discuss the
properties of the “cell wall”, or the thermal properties of brick walls in
construction journals. This justified a second filtering step whereby
irrelevant journals and conferences, and their papers, were trimmed out of the
corpus.

To this end, another round of data curation was required to harmonize and
deduplicate conference/journal names. We first deleted year/volume information
using regular expressions (e.g. 10th international conference, 2016
international conference, TEI’16, etc.). We also calculated the normalized
Levenshtein distance for all pairs of names keeping pairs with similarity
greater than 0.8 in order to cope with variations in word order,
abbreviations, splitted words, (e.g. “Australian Conference on Computer Human
Interaction” and “Australian Computer Human Interaction Conference”,
“Universal Access in the Information Society” and “Univers. Access Inf.
Soc.”). We manually screened the resulting similarity pairs to remove false
positives. Hence, we were left with 2,665 distinct conference/journal names
containing the 8,111 records.

We then sorted these names based on the number of records they had, from the
most popular (373 papers in the CHI conference) to the less popular (only 1
paper in 1628 conferences/journals). For venues having more than three papers,
if at a first glance we found one relevant record title, all records for this
venue were retained, otherwise they were excluded. For venues having three or
fewer records, if their names sounded relevant to the VIS community and to
this survey, we kept their records. In the end, we eliminated 4,081 records
and kept 4,030 published in 534 distinct journals/conferences.

##### Screening based on abstract

To further reduce the corpus to consider in the survey, we loaded the
resulting 4,030 records in Papyrus. Latent topics were automatically extracted
and visualized. Drilling down into a given topic, one could also access the
list of papers (see Figure 18-c) included in it and annotate every paper
according to whether it should be kept, discarded or a decision could not be
made based on the title and abstract only. One of the co-authors has screened
the 4030 abstracts to annotate them according to the following criteria.
Excluded were papers related to hardware, OS/Network protocols, distributed
rendering and distributed user interfaces on LHRDs, other devices and
technologies (e.g. mobile devices, wearable tangible displays, tabletops) when
they are not combined with LHRDs. We kept papers dealing with visualization
techniques on LHRDs. As a result, 3,329 records had to be discarded and 701
records were annotated as relevant or requiring to read their full text.

##### Full text assessing and tagging system

We used the 701 papers as an exhaustive scientific corpus for our survey. The
individual co-authors could use Papyrus software to further filter the
literature and to collect and classify relevant research in “shoeboxes”,
according to the different topics discussed in our survey. For instance,
concerning the visualization techniques on LHRDs, we built distinct shoeboxes
for specific types of data as shown in Figure 18-b. In addition to the
formally collected literature, the co-authors also contributed further
references based on their individual scientific background.

###  A.3 Software & Open Data

Throughout our process, we used several tools, Microsoft Excel to create a
spreadsheet with the papers. We developed macros in VBA to clean up the corpus
and the Fuzzy lookup add-in to deduplicate conference and journal names. This
corpus was loaded and processed afterwards in Papyrus, a visual text analytics
tool developed internally.

Our complete dataset and tagging system are accessible online at
https://viswallsurvey.list.lu. We also provide the final spreadsheet with the
701 papers underlying this survey in supplementary material and online at
https://dx.doi.org/10.21227/1aqm-xr17. We invite other researchers to
contribute to this corpus and join the discussion about wall-sized displays by
contacting us.

##  Appendix B Additional tables

Table B1: LHRD visualizations for different data types and how they utilize the increased display space. First author | Year |  Geographical |  Spatial |  Temporal |  Multidimensional |  Networks and trees |  Text and documents |  Single view |  Small multiples |  Multiple views |  Distributed views
---|---|---|---|---|---|---|---|---|---|---|---
Ball [BVS∗05] | 2005 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Prouzeau [PBC18] | 2018 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Ball [BNB07] | 2007 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Jakobsen [JHKH13] | 2013 | $\bullet$ |  |  | $\bullet$ |  |  | $\bullet$ |  | $\bullet$ |
Shoemaker [STKB10a] | 2010 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Ball [BN08] | 2008 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Nancel [NWP∗11] | 2011 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Onorati [OIB∗15] | 2015 | $\bullet$ |  |  |  |  | $\bullet$ | $\bullet$ |  | $\bullet$ |
Shoemaker [STKB10b] | 2010 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Ball [BN07] | 2007 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Ruddle [RTR∗15] | 2015 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Booker [BBSN07] | 2007 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Ronne [RJH11] | 2011 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Shupp [SBY∗06] | 2006 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Dostal [DHKQ14] | 2014 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Isenberg [IDW∗13] | 2013 | $\bullet$ |  | $\bullet$ |  | $\bullet$ |  | $\bullet$ | $\bullet$ |  |
Chung [CNF13] | 2013 | $\bullet$ |  |  |  |  |  | $\bullet$ |  |  |
Chokshi [CSMRM14] | 2014 | $\bullet$ |  |  |  |  | $\bullet$ |  | $\bullet$ | $\bullet$ | $\bullet$
Reda [RJPL15] | 2015 | $\bullet$ | $\bullet$ | $\bullet$ | $\bullet$ |  |  | $\bullet$ | $\bullet$ | $\bullet$ |
Horak [HBED18] | 2018 | $\bullet$ |  |  | $\bullet$ |  |  |  |  | $\bullet$ | $\bullet$
Prouzeau [PBC16b] | 2016 | $\bullet$ |  |  |  |  |  |  |  | $\bullet$ |
Ion [ICH∗13] | 2013 | $\bullet$ |  |  |  |  |  |  |  | $\bullet$ |
Kobayashi [KRGM∗18] | 2018 | $\bullet$ |  |  | $\bullet$ |  |  |  |  | $\bullet$ |
Langner [LKD18] | 2018 | $\bullet$ |  | $\bullet$ | $\bullet$ | $\bullet$ |  |  |  | $\bullet$ |
Su [SAP∗18] | 2018 | $\bullet$ |  |  |  |  | $\bullet$ |  | $\bullet$ | $\bullet$ |
von Zadow [VZBLD14] | 2014 | $\bullet$ |  |  |  |  |  |  |  |  | $\bullet$
Treanor [TJOH∗09] | 2009 |  | $\bullet$ |  |  |  |  | $\bullet$ |  |  |
Goodyer [GHW∗09] | 2009 |  | $\bullet$ |  |  |  |  | $\bullet$ |  |  |
Ruddle [RTR∗16] | 2016 |  | $\bullet$ |  |  |  |  | $\bullet$ |  |  |
Reda [RFK∗13] | 2013 |  | $\bullet$ |  |  |  |  | $\bullet$ | $\bullet$ |  |
Sollich [SvZP∗16] | 2016 |  | $\bullet$ |  |  |  |  | $\bullet$ |  |  | $\bullet$
Polys [PKB07] | 2007 |  | $\bullet$ |  |  |  |  | $\bullet$ |  |  |
Hanula [HPU∗15] | 2015 |  | $\bullet$ |  |  |  |  | $\bullet$ |  |  |
Liu [LCBL∗14] | 2014 |  | $\bullet$ |  |  |  | $\bullet$ |  | $\bullet$ |  |
Khan [KFA∗04] | 2004 |  | $\bullet$ |  |  |  |  |  | $\bullet$ |  |
Jagodic [JRJ∗11] | 2011 |  | $\bullet$ |  |  |  | $\bullet$ |  | $\bullet$ |  | $\bullet$
Pietriga [PDCI∗16] | 2016 |  | $\bullet$ |  |  |  |  |  |  | $\bullet$ |
Wigdor [WJF∗09] | 2009 |  | $\bullet$ |  |  |  |  |  |  | $\bullet$ |
Fernando [FADLc∗20] | 2020 |  |  | $\bullet$ |  |  | $\bullet$ | $\bullet$ |  |  |
Badam [BAEI16] | 2016 |  |  | $\bullet$ |  |  |  |  |  | $\bullet$ |
Thomas [TKAM17] | 2017 |  |  | $\bullet$ | $\bullet$ |  |  |  | $\bullet$ | $\bullet$ |
Jansen [JDF12] | 2012 |  |  |  | $\bullet$ |  |  | $\bullet$ |  |  |
Ruddle [RFT∗13] | 2013 |  |  |  | $\bullet$ |  |  | $\bullet$ |  |  |
Mateescu [MKB∗15] | 2015 |  |  |  | $\bullet$ |  |  | $\bullet$ |  |  |
Aurisano [ARJ∗15] | 2015 |  |  |  | $\bullet$ |  |  | $\bullet$ |  |  |
Reibert [RRF20] | 2020 |  |  |  | $\bullet$ |  |  | $\bullet$ |  |  |
Anslow [AMN∗10] | 2010 |  |  |  | $\bullet$ |  |  |  | $\bullet$ |  |
Bezerianos [BI12] | 2012 |  |  |  | $\bullet$ |  |  |  | $\bullet$ |  |
Yost [YHNN07] | 2007 |  |  |  | $\bullet$ |  |  |  | $\bullet$ |  |
Chegini [CLL∗17] | 2017 |  |  |  | $\bullet$ |  |  |  | $\bullet$ | $\bullet$ |
Tsandilas [TBJ15] | 2015 |  |  |  | $\bullet$ |  |  |  |  | $\bullet$ |
Riehmann [RMLR∗20] | 2020 |  |  |  | $\bullet$ |  |  |  |  | $\bullet$ |
Kister [KKTD17] | 2017 |  |  |  |  | $\bullet$ |  | $\bullet$ |  |  | $\bullet$
Lehmann [LSST11] | 2011 |  |  |  |  | $\bullet$ |  | $\bullet$ |  |  |
Kister [KRMD15] | 2015 |  |  |  |  | $\bullet$ |  | $\bullet$ |  |  |
Prouzeau [PBC16a] | 2016 |  |  |  |  | $\bullet$ |  | $\bullet$ |  |  |
von Zadow [vZD17] | 2017 |  |  |  |  | $\bullet$ |  | $\bullet$ |  |  |
Isenberg [ICB∗09] | 2009 |  |  |  |  | $\bullet$ |  | $\bullet$ |  |  |
Nolte [NBA∗16] | 2016 |  |  |  |  | $\bullet$ |  | $\bullet$ |  |  | $\bullet$
Chung [CNS∗14] | 2014 |  |  |  |  | $\bullet$ | $\bullet$ | $\bullet$ |  | $\bullet$ | $\bullet$
Bradel [BEK∗13] | 2013 |  |  |  |  | $\bullet$ | $\bullet$ |  | $\bullet$ |  | $\bullet$
Iyer [IPA17] | 2017 |  |  |  |  |  | $\bullet$ | $\bullet$ |  |  |
Nutsi [NK16] | 2016 |  |  |  |  |  | $\bullet$ | $\bullet$ |  |  |
Doshi [DTB∗17] | 2017 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Jansen [JSH19] | 2019 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Jakobsen [JH14] | 2014 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Birnholtz [BGMB07] | 2007 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Kirshenbaum [KKML19] | 2019 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Lischke [LMW∗15] | 2015 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Jakobsen [JH12] | 2012 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Andrews [AEN10] | 2010 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Endert [EFN12] | 2012 |  |  |  |  |  | $\bullet$ |  | $\bullet$ |  |
Geymayer [GWLS17] | 2017 |  |  |  |  |  | $\bullet$ |  |  | $\bullet$ |
Fiaux [FSB∗13] | 2013 |  |  |  |  |  | $\bullet$ |  |  | $\bullet$ |
Andrews [AN12] | 2012 |  |  |  |  |  | $\bullet$ |  |  | $\bullet$ |
Kukimoto [Kuk14] | 2014 |  |  |  |  |  | $\bullet$ |  |  | $\bullet$ | $\bullet$
Lischke [LHK∗17] | 2017 |  |  |  |  |  | $\bullet$ |  |  | $\bullet$ | $\bullet$

Table B2: Interaction techniques  On-surface interaction | Touch and multi-touch | [JH14, JH16, HZRB11, LKD18, JJBH15, PBC16a, RRF20, RMLR∗20]
---|---|---
Pen input, pen and touch | [GSW01, WLJ∗12, ICH∗13, LSR∗15]
Tangible input | [vZBD∗16, CAC21]
Distant interaction | Mouse | [JHWS02, AEN10, BGMB07, JH16]
Remote controller | [BSW06, DC02, KBSR07, JPJ09, JNJ∗10, JDF12, NCP∗13, Zha17, LKD18, HBED18]
Mid-air gestures | [MRB05, VB05, NWP∗11, YPKT15, HNV15, LNV15, JJBH15, WJ16, MV18]
Gaze | [HCT∗08, CBBF10, SD13, LGK∗15a]
Utilizing space | Physical navigation | [BNB07, BN07, BB09, LMW∗15, EALN11, IDW∗13, NHC12, LCBL∗14, JH15, RJBR13, JSH19]
Proxemic interaction | [JHKH13, LSST11, DHKQ14, KRMD15, STKB10b, STKB10a, PBC18]
Spatial interaction | [RJBR13, LVZH∗16, KKTD17]
Multiple displays | Mobile devices | [VZBLD14, VZ15, CBF14, TBJ15, KKTD17, HBED18]
Head-mounted displays | [NYW∗16, SYFM19, AJN19, RFD20]
Multiple devices | [CSMRM14, PBC18, RTNS15, AJN19]

Table B3: Overview of the seven evaluation scenarios by Lam et al. [LBI∗11] and corresponding examples of concrete evaluation questions. Scenario | Research questions | Citations
---|---|---
1 | UWP | What is the everyday use of LHRDs? How do users process their work on LHRDs? | [BN05a, BB09, BBB14]
|  | When and how could LHRDs facilitate and support the current workflow? | [RWM∗15]
|  | What are the use cases and benefits of LHRDs in a given situation? | [Cha18, BVS∗05, MKB∗15]
|  | How do users organize and manage information on an LHRD? | [BEK∗13, DTB∗17]
|  | What interaction and visualization would better fit with LHRDs? What are the challenges when combining an LHRD and other devices? | [KKTD17]
|  | How might LHRDs be a part of existing analysis tasks and practices? | [KJH12]
|  | What office work practices might benefit from LHRDs? | [KH19]
2 | VDAR | What are the user’s data analysis rationale, thought process and findings when using an LHRD? | [RFT∗13]
|  | What is the effect of display size of LHRDs on the quantity and breadth of insights acquired by users during visual exploration? | [RJPL15, LMW∗15, SADK∗09, RTR∗15, BN05a, RWM∗15]
|  | How do users adapt their sensemaking workflow to take advantage of an LHRD and its user interface? | [RJM∗12, ROJL14]
3 | CTV | How effective is the displayed app for the task using an LHRD? | [AMN∗10]
|  | How users perceive and interact with interfaces and visualizations displayed on LHRD? | [PKB07]
|  | How perceptually scalable are data visualizations for large displays? | [YN06]
4 | CDA | How pairs collaborate on multi-touch LHRD? | [LKD18, JH12, JH14]
|  | What are the different collaborative position patterns of pairs working with LHRD and multiple mobile devices? | [AJHE15]
|  | How group processes vary depending on the use of different modalities (e.g., direct interaction with touch or indirect distant interaction)? | [JH16, HKR∗05]
|  | How groups behave when they are closely collaborating in front of an LHRD? | [vZBD∗16, MLG∗18]
|  | How do the users collaborate and develop territories? | [BEK∗13]
|  | How users define interpersonal and onscreen workspaces? | [WIL16]
|  | How collaborative interaction affects efficiency? | [LCBLL16]
5 | UP | How display size and physical navigation affect task performance? | [LCBL∗14, JH13, RJH11, SADK∗09, BNB07, JH15, BN08, BN05b, CSR∗03]
|  | How does an LHRD compare to a regular display for achieving a task? | [RTR∗16, TJOH∗09]
|  | What types of interaction zones users expected when interacting with displays? | [PB18]
|  | How does visual encoding impact the effectiveness of large, high-resolution visualizations? | [EALN11]
|  | How does one interaction technique on LHRD compare to another by measuring the human performance? | [NWP∗11, JJBH15, NCP∗13, JNJ∗10, JPJ09]
6 | UE | Are the features useful for end-users? Are desired actions supported? | [TKAM17, CSMRM14, ICH∗13, AMN∗10, NBA∗16, KKTD17, ASS19]
|  | What are the pain points users encounter during their process using the software on LHRD, and what improvements should be made? | [DTB∗17, WJF∗09, PBC16b]
7 | AP | What is the performance of the algorithm loading an image on tiled LHRD? | [KVV∗04]
|  | Which algorithm perform better for rendering (e.g., graph) visualization? | [MGL06, HKD18, RLH17, HWU∗20, MFMSG20]
|  | Which algorithm perform better for seamless frame synchronisation on tiled LHRD? | [NDV∗10]