Updated README and tried to document all decisions I made so far
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---
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title: "Background information about MTT data"
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author: "Nora Wickelmaier"
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date: "`r Sys.Date()`"
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output:
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html_document:
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number_sections: true
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toc: true
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---
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# Log data from the Multi-Touch Table at the HAUM
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The Multi Touch Table at the Herzog-Anton-Ulrich-Museum (HAUM) in
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Braunschweig gives visitors of the Museum the opportunity to interact with
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67 artworks and 3 tiles containing information about the museum and its
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layout. The table was installed at the institute in October 2016 and since
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November 2016 log files from interactions of visitors of the museum have
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been collected. These log files are in an unstructured format and cannot be
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easily analyzed. The purpose of the following document is to describe how
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the data haven been transformed and which decisions have been made a long
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the way.
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# Data structure
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The log files contain lines that indicate the beginning and end of possible
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actions that can be performed when interacting with the artworks on the
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table. The layout of the table looks like 70 pictures have been tossed on a
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large table. Every artwork is visible at the start configuration. People
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can move the pictures on the table, they can be scaled and rotated.
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Additionally, the virtual picture cards can be flipped in order to find
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more information of the artwork on the "back" of the card. One has to press
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a little `i` for more information in one of the bottom corners of the card.
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On the back of the card two (?) to six information cards can be found with
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a teaser text about a certain topic. These topic cards can be opened and a
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hypertext with detailed information pops up. Within these hypertexts
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certain technical terms can be clicked for lay people to get more
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information. This also opens up a pop-up. The events encoded in the raw log
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files therefore have the following structure.
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```
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"Start Application" --> Start Application
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"Show Application"
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"Transform start" --> Move
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"Transform stop"
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"Show Info" --> Flip Card
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"Show Front"
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"Artwork/OpenCard" --> Open Topic
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"Artwork/CloseCard"
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"ShowPopup" --> Open Popup
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"HidePopup"
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```
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The right side shows what events can be extracted from these raw lines. The
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"Start Application" is not an event in the original sense since it only
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indicates if the table was started or maybe reset itself. This is not an
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interaction with the table and therefore not interesting in itself. All
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"Start Application" and "Show Application" are therefore excluded from the
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data when further processed and are only in the raw log files.
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# Parsing the raw log files
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The first step is to parse the raw log files that are stored by the
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application as text files in a rather unstructured format to a format that
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is better handled. The data are therefore transferred to a spread sheet
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format. The following section describes what problems were encountered
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while doing this.
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## Corrupt lines
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When reading the files containing the raw logs into R, a warning appears
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that says
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```
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Warning messages:
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incomplete final line found on '_2016/2016_11_18-11_31_0.log'
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incomplete final line found on '_2016/2016_11_18-11_38_30.log'
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incomplete final line found on '_2016/2016_11_18-11_40_36.log'
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...
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```
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When you open these files, it looks like the last line contains some binary
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content. It is unclear why and how this happens. So when reading the data,
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these lines were removed. A warning will be given that indicates how many
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files have been affected.
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## Units of the variables
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* Welche Einheit haben x und y? Pixel? --> yes
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* Welche Einheit hat scale? --> some kind if bit, does not matter, when
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calculating a ratio
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* rotation wirklich degree? --> yes
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* Nach welchem Zeitintervall resettet sich der Tisch wieder in die
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Ausgangskonfiguration? --> PM needs to look it up
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## How unclosed events are handled
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## How a case is defined
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* Herausfinden, ob mehr als eine Person am Tisch steht?
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- Sliding window, in der Anzahl von Artworks gezählt wird? Oder wie weit
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angefasste Artworks voneinander entfernt sind?
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- Man kann sowas schon "sehen" in den Logs - aber wie kann ich es
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automatisiert rausziehen? Was ist meine Definition von
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"Interaktionsboost"?
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- Egal wie wir es machen, geht es auf den "Event-Log-Daten"?
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## Additional meta data
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* Anreicherung der Log-Daten mit weiteren Metadaten? Was wäre interessant?
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- Metadata on artworks like, name, artist, type of artwork, epoch, etc.
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- School vacations and holidays
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- Special exhibits at the museum
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- Number of visitors per day (bei Sven noch mal nachhaken?)
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- Age structure of visitors per day?
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- ... ????
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# Problems and how I handled them
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```{r, include = FALSE}
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# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis")
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source("code/functions.R")
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```
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This lists some problems with the log data that required decisions. These
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decisions influence the outcome and maybe even the data quality. Hence, I
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tried to document how I handled these problems and explain the decisions I
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made.
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## Weird behavior of `timeMs` and neg. `duration` values
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I think the negative duration values happen, when an event starts in one
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log file and completes in another one. The variable `timeMs` seems to be
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continuous within one log file but not over several log files.
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```{r}
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# Read data
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dat0 <- read.table("data/rawdata_logfiles_small.csv", sep = ";",
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header = TRUE)
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dat0$date <- as.POSIXct(dat0$date)
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dat0$glossar <- ifelse(dat0$artwork == "glossar", 1, 0)
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# Remove irrelevant events
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dat <- subset(dat0, !(dat0$event %in% c("Start Application",
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"Show Application")))
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# Add trace variable
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dat1 <- add_trace(dat, glossar_dict = "data/glossar_dict.RData")
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# Close events
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dat2 <- rbind(close_events(dat1, "move"),
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close_events(dat1, "flipCard"),
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close_events(dat1, "openTopic"),
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close_events(dat1, "openPopup"))
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dat2 <- dat2[order(dat2$date.start, dat2$fileId.start), ]
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head(dat2[which(dat2$duration < 0),
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c("fileId.start", "fileId.stop", "event", "artwork", "duration")], 20)
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head(dat2[which(dat2$fileId.start != dat2$fileId.stop),
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c("fileId.start", "fileId.stop", "event", "artwork", "duration")], 20)
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plot(timeMs ~ as.factor(fileId), dat[1:5000,], xlab = "fileId")
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# Remove durations when event spans more than one log file, since they are
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# not interpretable
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#dat2[which(dat2$fileId.start != dat2$fileId.stop), "duration"] <- NA
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```
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The boxplot shows that we have a continuous range of values within one log
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file but that `timeMs` does not increase over log files. Since it seems not
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possible to fix this in a consistent way, I set all durations to `NA` where
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`fileId.start` and `fileId.stop` are not identical. I kept `timeMs.start`
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and `timeMs.stop` and also `fileId.start` and `fileId.stop` in the data
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frame, so it is clear why there are no durations. The other
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NOTE: Part of this problem was that time stamps that are part of the log
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file names are not zero-left-padded and therefore the files were not in the
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correct order when read into R. When zero left padding these file IDs and
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sorting by them and then by `date.start` within, some of the durations are
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exactly fixed. Unfortunately, only three `move` events were fixed, since it
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only fixed irregularities *within* one log file. See below for more
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details.
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## Left padding of file IDs
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The file names of the raw log files are automatically generated and contain
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a time stamp. This time stamp is not well formed. First, it contains an
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incorrect month. The months go from 0 to 11 which means, that the file name
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`2016_11_15-12_12_57.log` was collected on December 15, 2016 at 12:12 pm.
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Another problem is that the file names are not zero left padded, e.g.,
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`2016_11_15-12_2_57.log`. This file was collected on December 15, 2016 at
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12:02 pm and therefore before the file above. But most sorting algorithms,
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will sort these files in the order shown below. In order to preprocess the
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data and close events that belong together, the data need to be sorted by
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events and artworks repeatedly. In order to get them back in the correct
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time order, it is necessary to order them based on three variables:
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`fileId.start`, `date.start` and `timeMs`. The file IDs therefore need to
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sort in the correct order (again see below for example). I zero left padded
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the log file names within the data frame using it as an identifier. These
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"file names" do not correspond exactly to the original raw log file names.
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This needs to be kept in mind when doing any kind of matching etc.
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```
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## what it looked like before left padding
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# 1422 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_2_57.log 2016-12-15 12:12:56 599671 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26874254
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# 1423 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 621 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26523465
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# 1424 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 677 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997736 13.26239605
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# 1425 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 774 Transform start 076 076.xml NA 2092.25 2008.00 0.2999345 13.26239605
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# 1426 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 850 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997107 13.26223362
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# 1427 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_2_57.log 2016-12-15 12:12:57 599916 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997771 13.26523465
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## what it looks like now
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# 1422 2016_11_15-12_02_57.log 2016-12-15 12:12:56 599671 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26874254
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# 1423 2016_11_15-12_02_57.log 2016-12-15 12:12:57 599916 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997771 13.26523465
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# 1424 2016_11_15-12_12_57.log 2016-12-15 12:12:57 621 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26523465
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# 1425 2016_11_15-12_12_57.log 2016-12-15 12:12:57 677 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997736 13.26239605
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# 1426 2016_11_15-12_12_57.log 2016-12-15 12:12:57 774 Transform start 076 076.xml NA 2092.25 2008.00 0.2999345 13.26239605
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# 1427 2016_11_15-12_12_57.log 2016-12-15 12:12:57 850 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997107 13.26223362
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```
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## Timestamps repeat
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The time stamps in the `date` variable record year, month, day, hour,
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minute and seconds. Since one second is not a very short time interval for
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a move on a touch display, this is not fine grained enough to bring events
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into the correct order, meaning there are events from the same log file
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having the same time stamp and even events from different log files having
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the same time stamp. The log files get written about every 10 minutes
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(which can easily be seen when looking at the file names of the raw log
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files). So in order to get events in the correct order, it is necessary to
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first order by file ID, within file ID then sort by time stamp `date` and
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then within these more coarse grained time stamps sort be `timeMs`. But as
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explained above, `timeMs` can only be sorted within one file ID, since they
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do not increase consistently over log files, but have a new setoff for each
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raw log file.
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## x,y-coordinates outside of display range
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The display of the Multi-Touch-Table is a 4K-display with 3840 x 2160
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pixels. When you plot the start and stop coordinates, the display is
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clearly to distinguish. However, a lot of points are outside of the display
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range. This can happen, when the art objects are scaled and then moved to
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the very edge of the table. Then it will record pixels outside of the
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table. These are actually valid data points and I will leave them as is.
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```{r}
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par(mfrow = c(1, 2))
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plot(y.start ~ x.start, dat2)
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abline(v = c(0, 3840), h = c(0, 2160), col = "blue", lwd = 2)
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plot(y.stop ~ x.stop, dat2)
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abline(v = c(0, 3840), h = c(0, 2160), col = "blue", lwd = 2)
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aggregate(cbind(x.start, x.stop, y.start, y.stop) ~ 1, dat2, mean)
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```
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## Pop-ups from glossar cannot be assigned to a specific artwork
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All the information, pictures and texts for the topics and pop-ups are
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stored in
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`/Logfiles/ContentEyevisit/eyevisit_cards_light/<artwork_number>`. Among
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other things, each folder contains XML-files with the information about any
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technical terms that can be opened from the hypertexts on the topic cards.
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Often these information are artwork dependent and then the corresponding
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XML-file is in the folder for this artwork. Sometimes, however, more
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general terms can be opened. In order to avoid multiple files containing
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the same informatione, these were stored in a folder called `glossar` and
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get accessed from there. The raw log files only contain the path to this
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glossar entry and did not record from which artwork it was accessed. I
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tried to assign these glossar entries to the correct artworks. The (very
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heuristic) approach was this:
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1. Create a lookup table with all XML-file names (possible pop-ups) from
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the glossar folder and what artworks possibly call them. This was stored
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as an `RData` object for easier handling but should maybe be stored in a
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more interoperable format.
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2. I went through all possible pop-ups in this lookup table and stored the
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artworks that are associated with it.
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3. I created a sub data frame without move events (since they can never be
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associated with a pop-up) and went through every line and looked up if
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an artwork and a topic card had been opened. If this was the case and a
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glossar entry came up before the artwork was closed again, I assigned
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this artwork to this glossar entry.
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This is heuristic since it is possible that several topic cards from
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different artworks are opened simultaneously and the glossar pop-up could
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be opened from either one (it could even be more than two, of course). In
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these cases the artwork that was opened closest to the glossar pop-up has
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been assigned, but this can never be completely error free.
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And this heuristic only assigns a little more than half of the glossar
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entries. Since my heuristic only looks for the last artwork that has been
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opened and if this artwork is a possible candidate it misses all glossar
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pop-ups where another artwork has been opened in between. This is still an
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open TODO to write a more elaborate algorithm.
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All glossar pop-ups that do not get matched with an artwork are removed
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from the data set with a warning.
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## Assign a `case` variable based on "time heuristic"
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One thing needed in order to work with the data set and use it for machine
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learning algorithms like process mining is a variable that tries to
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identify a case. A case variable will structure the data frame in a way
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that navigation behavior can actually be investigated. However, we do not
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know if several people are standing around the table interacting with it or
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just one very active person. The simplest way to define a case variable is
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to just use a time limit between events. This means that when the table has
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not been interacted with for, e.g., 20 seconds than it is assumed that a
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person moved on and a new person started interacting with the table. This
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is the easiest heuristic and implemented at the moment. Process mining
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shows that this simple approach works in a way that the correct process
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gets extracted by the algorithm.
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In order to investigate user behavior on a more fine grained level, it will
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be necessary to come up with a more elaborate approach. A better, still
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simple approach could be to use this kind of time limit and additionally
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look at the distance between artworks interacted with within one time
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window. When artworks are far apart is seems plausible that more than one
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person interacted with them. Very short time lapses between events on
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different artworks could also be an indicator that more than one person is
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interacting with the table.
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## Assign a `trace` variable
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The `trace` variable is supposed to show one interaction trace with one
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artwork. Meaning it starts when an artwork is touched or flipped and stops
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when it is closed again. It is easy to assign a trace from flipping a card
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over opening (maybe several) topics and pop-ups for this artwork card until
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closing this card again. But one would like to assign the same trace to
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move events surrounding this interaction. Again, this is not possible in an
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algorithmic way but only heuristically. I used the `case` variable in order
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to get meaningful units around the artworks.
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If within one case only a single trace for a single artwork was opened, I
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assigned this trace to the moves associated with this artwork. I (quite
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often) happens that within one case one artwork is opened and closed
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several times, each time starting a new trace. I then assigned all the
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following move events to the trace beforehand. This is, of course,
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arbitrary and could also be handled the other way around.
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Another possibility is, that an artwork gets moved within one trace without
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being flipped. I then assigned a new trace to this move.
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This overall worked very well even though it was based on the very
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heuristic approach assigning a case when the table has not been touched for
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20 seconds. It should be kept in mind that the trace assignments for the
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moves will change when case is defined in a different way.
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## A `move` event does not record any change
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Most of the events in the log files are move events. Additionally, many of
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these move events are recorded but they do not indicate any change meaning
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the only difference is the time stamp. All other variables indicating moves
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like `x.start` and `x.stop`, `rotation.start` and `rotation.stop` etc. do
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not show any change. They represent about 2/3 of all move events. These
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events are probably short touches of the table without an actual
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interaction. They were therefore removed from the data set.
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## Events that only close (`date.start` is NA)
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It looks like there is some kind of log error for the events that do not
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have a start stop. I was able to get rid of most by sorting for `popup` for
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the openPopup events, but there are still some left (50 for the small data
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set, which corresponds to 0.2 per mill). The following example shows that
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artwork "501" gets closed (line 31030) while the pop-up `sommerbau.xml`
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is still opened (line 31027). Then artwork "501" gets opened again
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(line 31035) and after that the pop-up `sommerbau.xml` is closed (line
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31040). This should not be possible and therefore (correctly) two events
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are assigned: One where the pop-up was opened and then not closed (which is
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common) and another one where the pop-up has no start.
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```{r}
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dat[31000:31019,]
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# Card gets flipped closed before pop-up closes --> log error!
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```
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I did not check all of these cases (for the complete data set this is
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simply not possible by hand) but just excluded all events that do not have
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a `date.start` since they are hard to interpret. Often they are log errors
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but in some cases they might be resolvable.
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||||
|
||||
```{r}
|
||||
# remove all events that do not have a `date.start`
|
||||
dim(dat2[is.na(dat2$date.start), ])
|
||||
dat2 <- dat2[!is.na(dat2$date.start), ]
|
||||
```
|
||||
|
||||
## Card indices go from 0 to 7 (instead of 0 to 5 as expected)
|
||||
|
||||
See `questions_number-of-cards.R` for more details.
|
||||
|
||||
I wrote a function that for each artwork extracts the file names of the
|
||||
possible topic cards and then looks up which topics have actually been
|
||||
displayed on the back of the card. I added an index giving the ordering in
|
||||
the index files.
|
||||
|
||||
The possible values in the variable `topicNumber` range from 0 to 7,
|
||||
however, not artwork has more than six different numbers. So I just renamed
|
||||
those numbers from 1 to the highest number, e.g., $0,1,2,4,5,6$ was changed
|
||||
to $0\to 1,1\to 2,2\to 3,4\to 4,5\to 5,6\to 6$. Next I used the index to
|
||||
assign topics and file names to the according pop-ups. This needs to be
|
||||
cross checked with the programming, but seems the most plausible approach
|
||||
with my current knowledge.
|
||||
|
||||
## Extracting topics from `index.xml` vs. `<artwork_number>.xml
|
||||
|
||||
When I extract the topics from `index.html` I get different topics, than
|
||||
when I get them from `<artwork>.html`. At first glance, it looks like using
|
||||
`index.html` actually gives the wrong results.
|
||||
|
||||
```{r}
|
||||
artworks <- unique(dat2$artwork)
|
||||
path <- "data/ContentEyevisit/eyevisit_cards_light/"
|
||||
topics <- extract_topics(artworks, "index.xml", path)
|
||||
topics2 <- extract_topics(artworks, paste0(artworks, ".xml"), path)
|
||||
|
||||
topics[!topics$file_name %in% topics2$file_name, ]
|
||||
topics2[!topics2$file_name %in% topics$file_name, ]
|
||||
```
|
||||
|
||||
For artwork "031", `index.html` only defines 5 cards (the 6th is commented
|
||||
out), but `topicNumber` for this artwork has 6 different entries. I will
|
||||
therefore extract the topics from `<artwork>.html`. (This seems also better
|
||||
compatible with other data sets like 8o8m.)
|
||||
|
||||
# Reading list
|
||||
|
||||
* @Arizmendi2022 [--]
|
||||
* @Bannert2014 [x]
|
||||
* @Bousbia2010 [--]
|
||||
* @Cerezo2020
|
||||
* @GerjetsSchwan2021 [x]
|
||||
* @Goldhammer2020
|
||||
* @Guenther2007
|
||||
* @HuberBannert2023 [x]
|
||||
* @Kroehne2018
|
||||
* @SchwanGerjets2021 [x]
|
||||
* @vanderAalst2016 [Chap. 2, x]
|
||||
* @vanderAalst2016 [Chap. 3]
|
||||
* @vanderAalst2016 [Chap. 5, x]
|
||||
* @Wang2019
|
||||
|
||||
# Open stuff
|
||||
|
||||
* Angle from which people approach table in Braunschweig? Consider in
|
||||
rotation variable?
|
||||
* Time limit for `case` variable different for different events? (openTopic
|
||||
should be opened the longest)
|
||||
|
||||
$\to$ I think this is not relevant since I am looking at time *between*
|
||||
events!
|
||||
|
||||
# Stuff AK found interesting
|
||||
|
||||
* Pre/post corona
|
||||
* Identify school classes
|
||||
* How many persons are present at the table?
|
||||
|
||||
# Other potential questions
|
||||
|
||||
* "Bursts"
|
||||
* 1st vs. 2nd half of the day
|
||||
* Can we identify "types of art"? With clustering or something?
|
||||
* Possible to estimate how many persons per day? Maybe average of certain
|
||||
weekdays? ... ?
|
||||
|
||||
321
README.md
321
README.md
|
|
@ -1,321 +0,0 @@
|
|||
# Offene Fragen
|
||||
|
||||
## Datenverständnis
|
||||
|
||||
* Welche Einheit haben x und y? Pixel? --> yes
|
||||
* Welche Einheit hat scale? --> some kind if bit, does not matter, when
|
||||
calculating a ratio
|
||||
* rotation wirklich degree? --> yes
|
||||
* Nach welchem Zeitintervall resettet sich der Tisch wieder in die
|
||||
Ausgangskonfiguration? --> PM needs to look it up
|
||||
|
||||
## Tisch-Software
|
||||
|
||||
* Gibt es Doku für die Bilder, die über die xml files hinausgeht? Sowas wie
|
||||
ein Manual oder ähnliches?
|
||||
* Gibt es evtl. irgendwo noch ein Tablet mit der Anwendung drauf?
|
||||
* Was bedeuten die Farben der Topic Cards? --> sieht man in den xml files
|
||||
|
||||
## Event Logs
|
||||
|
||||
* Wie gehen wir mit "nicht geschlossenen" Events um? Einfach rauslöschen?
|
||||
- für Transform tendiere ich zu ja, weil sonst total uninteressant
|
||||
- bei flipCard bin ich nicht so sicher... Aber man kann dann keine
|
||||
duration berechnen, wäre NA
|
||||
* Moves/scales/rotations ohne Veränderung würde ich auf jeden Fall
|
||||
rauslöschen
|
||||
* Es ist nicht möglich (bzw. ich weiß nicht wie) zusammengehörige Events
|
||||
eineindeutig zu identifizieren
|
||||
- nach Heuristik vorgehen? Doppelte Transformation start und stop einfach
|
||||
raus?
|
||||
- Daten sind nicht "fehlerfrei"; es gibt z.B. Transformation-Events wo
|
||||
das Ende nicht geloggt wurde
|
||||
* Wie identifiziere ich eine "Interaktionseinheit"?
|
||||
- Was ist ein "case"?
|
||||
- Eher grob über Zeitintervalle?
|
||||
- Noch irgendeine andere Idee?
|
||||
* Herausfinden, ob mehr als eine Person am Tisch steht?
|
||||
- Sliding window, in der Anzahl von Artworks gezählt wird? Oder wie weit
|
||||
angefasste Artworks voneinander entfernt sind?
|
||||
- Man kann sowas schon "sehen" in den Logs - aber wie kann ich es
|
||||
automatisiert rausziehen? Was ist meine Definition von
|
||||
"Interaktionsboost"?
|
||||
- Egal wie wir es machen, geht es auf den "Event-Log-Daten"?
|
||||
* Anreicherung der Log-Daten mit weiteren Metadaten? Was wäre interessant?
|
||||
- Metadata on artworks like, name, artist, type of artwork, epoch, etc.
|
||||
- School vacations and holidays
|
||||
- Special exhibits at the museum
|
||||
- Number of visitors per day
|
||||
- Age structure of visitors per day?
|
||||
- ... ????
|
||||
|
||||
## HAUM
|
||||
|
||||
* Bei Sven noch mal nachhaken wegen Besucherzahlen?
|
||||
|
||||
|
||||
|
||||
|
||||
# Problems and how I handled them
|
||||
|
||||
This lists some problems with the log data that required decisions. These
|
||||
decisions influence the outcome and maybe even the data quality. Hence, I
|
||||
tried to document how I handled these problems and explain the decisions I
|
||||
made.
|
||||
|
||||
## Weird behavior of `time_ms` and neg. `duration`values
|
||||
|
||||
I think the negative duration values happen, when an event starts in one
|
||||
log file and completes in another one. The variable `time_ms` seems to be
|
||||
continuous within one log file but not over several log files.
|
||||
|
||||
```{r}
|
||||
dat_all[which(dat_all$duration < 0), ][1:5, 1:10]
|
||||
|
||||
# flipCard
|
||||
## trace 56
|
||||
dat3[dat3$trace == 56,]
|
||||
|
||||
dat[dat$fileid == "2016_11_15-11_12_57.log" & dat$date == "2016-12-15 11:17:26", ]
|
||||
dat[dat$fileid == "2016_11_15-11_42_57.log" & dat$date == "2016-12-15 11:46:19", ]
|
||||
|
||||
#dat[309:1405, ]
|
||||
|
||||
tmp <- dat[300:1405, ]
|
||||
tmp[tmp$artwork == "051", ]
|
||||
## -> was closed correctly, but does it belong together?
|
||||
|
||||
|
||||
## trace 61
|
||||
dat3[dat3$trace == 61,]
|
||||
|
||||
dat[dat$fileid == "2016_11_15-11_12_57.log" & dat$date == "2016-12-15 11:17:52", ]
|
||||
dat[dat$fileid == "2016_11_15-11_42_57.log" & dat$date == "2016-12-15 11:46:19", ]
|
||||
|
||||
tmp <- dat[350:1408, ]
|
||||
tmp[tmp$artwork == "057", ]
|
||||
## -> was closed correctly, but does it belong together?
|
||||
|
||||
|
||||
# openTopic
|
||||
dat_all[which(dat_all$duration < 0), ][100:105, 1:10]
|
||||
|
||||
# trace 2052
|
||||
dat4[dat4$trace == 2052,]
|
||||
|
||||
dat[dat$fileid == "2016_11_17-14_12_10.log" & dat$date == "2016-12-17 14:21:51", ]
|
||||
dat[dat$fileid == "2016_11_17-14_22_10.log" & dat$date == "2016-12-17 14:22:25", ]
|
||||
|
||||
tmp <- dat[23801:23950, ]
|
||||
tmp[tmp$artwork == "502", ]
|
||||
|
||||
plot(time_ms ~ as.factor(fileid), dat[1:5000,])
|
||||
```
|
||||
|
||||
The boxplot shows that we have a continuous range of values within one log
|
||||
file but that `time_ms` does not increase over log files.
|
||||
<!--
|
||||
TODO: I will probably update how events are closed and the names of these
|
||||
data frame, especially `dat3` and `dat4` will have to be adjusted.
|
||||
-->
|
||||
Since it seems not possible to fix this in a consistent way, I will set
|
||||
negative durations to `NA`. I will keep `time_ms.start` and `time_ms.stop`
|
||||
in the data frame, so it is clear why there are no durations. Maybe it
|
||||
would also be useful to keep `logfileid.start` and `logfileid.stop` in the
|
||||
data? Maybe just for proof checking this theory...
|
||||
|
||||
Part of it was that timestamps that are part of the log file names are not
|
||||
zero-left-padded. But this fixed only three `move` events, since it only
|
||||
fixed irregularities *within* one log file.
|
||||
|
||||
```{r}
|
||||
table(dat_all[dat_all$duration < 0, "event"])
|
||||
|
||||
# flipCard move openPopup openTopic
|
||||
# 562 100 34 284
|
||||
|
||||
|
||||
dat[dat$event %in% c("Transform start", "Transform stop"), ][1100:1300,]
|
||||
# --> got fixed by left padding... but only three all together!!
|
||||
|
||||
dat_all[735, ]
|
||||
|
||||
## what it looked like before left padding
|
||||
# 1422 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_2_57.log 2016-12-15 12:12:56 599671 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26874254
|
||||
# 1423 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 621 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26523465
|
||||
# 1424 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 677 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997736 13.26239605
|
||||
# 1425 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 774 Transform start 076 076.xml NA 2092.25 2008.00 0.2999345 13.26239605
|
||||
# 1426 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 850 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997107 13.26223362
|
||||
# 1427 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_2_57.log 2016-12-15 12:12:57 599916 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997771 13.26523465
|
||||
|
||||
## what it looks like now
|
||||
# 1422 2016_11_15-12_02_57.log 2016-12-15 12:12:56 599671 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26874254
|
||||
# 1423 2016_11_15-12_02_57.log 2016-12-15 12:12:57 599916 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997771 13.26523465
|
||||
# 1424 2016_11_15-12_12_57.log 2016-12-15 12:12:57 621 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26523465
|
||||
# 1425 2016_11_15-12_12_57.log 2016-12-15 12:12:57 677 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997736 13.26239605
|
||||
# 1426 2016_11_15-12_12_57.log 2016-12-15 12:12:57 774 Transform start 076 076.xml NA 2092.25 2008.00 0.2999345 13.26239605
|
||||
# 1427 2016_11_15-12_12_57.log 2016-12-15 12:12:57 850 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997107 13.26223362
|
||||
```
|
||||
|
||||
`time_ms` does not increase from log file to log file
|
||||
|
||||
```{r}
|
||||
tmp1 <- dat[!duplicated(dat$fileid), c("fileid", "time_ms", "event")]
|
||||
tmp2 <- dat[!duplicated(dat$fileid, fromLast=T), c("fileid", "time_ms", "event")]
|
||||
tmp <- rbind(tmp1, tmp2)
|
||||
tmp <- tmp[order(tmp$fileid), ]
|
||||
head(tmp, 50)
|
||||
|
||||
plot(time_ms ~ as.factor(fileid), dat[1:2000, ], xlab = "fileid")
|
||||
```
|
||||
|
||||
## x,y-coordinates outside of display range
|
||||
|
||||
The display is a 4K-display with 3840 x 2160 pixels. When you plot the
|
||||
start and stop coordinates, the display is clearly to distinguish. However,
|
||||
a lot of points are outside of the display range. This can happen, when the
|
||||
art objects are scaled and then moved to the very edge of the table. Then
|
||||
it will record pixels outside of the table. These are actually valid data
|
||||
points and I will leave them as is.
|
||||
|
||||
```{r}
|
||||
par(mfrow = c(1, 2))
|
||||
plot(y.start ~ x.start, dat)
|
||||
abline(v = c(0, 3840), h = c(0, 2160), col = "blue", lwd = 2)
|
||||
plot(y.stop ~ x.stop, dat)
|
||||
abline(v = c(0, 3840), h = c(0, 2160), col = "blue", lwd = 2)
|
||||
|
||||
|
||||
aggregate(cbind(x.start, x.stop, y.start, y.stop) ~ 1, dat, mean)
|
||||
```
|
||||
|
||||
|
||||
## Timestamps repeat
|
||||
|
||||
|
||||
|
||||
## Popups from glossar cannot be assigned to a specific artwork
|
||||
|
||||
|
||||
## Assign a case variable based on "time heuristic"
|
||||
|
||||
## A `move`event does not record any change
|
||||
|
||||
## Add moves to `trace` variable
|
||||
|
||||
## openPopup does not close correctly
|
||||
|
||||
The sorting had to include `popup` otherwise nested events could not be
|
||||
closed correctly.
|
||||
|
||||
```{r}
|
||||
# TODO: Some correct entries are not closed:
|
||||
df[df$trace == 1843, ]
|
||||
# WHY???
|
||||
# --> Wrong eventid!
|
||||
dat5[dat5$trace == 1843, ]
|
||||
openPopup_wide[openPopup_wide$trace == 1843, ]
|
||||
```
|
||||
## Events that only close (`date.start` is NA)
|
||||
|
||||
It looks like there is some kind of log error for the events that do not
|
||||
have a start stop. I was able to get rid of most by sorting for `popup` for
|
||||
the openPopup events, but there are still some left (50 for the small data
|
||||
set, which corresponds to 0.2 per mill).
|
||||
|
||||
```{r}
|
||||
# remove all events that do not have a `date.start`
|
||||
dim(dat_all[is.na(dat_all$date.start), ])
|
||||
dat_all <- dat_all[!is.na(dat_all$date.start), ]
|
||||
# TODO: Find out how it can be that there is only a `date.stop`
|
||||
## --> happens, when event is not properly closed, see here:
|
||||
df[df$trace == 1843, ]
|
||||
dat_openPopup[dat_openPopup$trace == 1843, ]
|
||||
## --> still 50 (small data set) left, and some really do not seem to be
|
||||
## opened! Must be a log error
|
||||
# --> others should be closed!
|
||||
dat[31000:31019,] # this one e.g.
|
||||
# --> Actually NOT! card gets flipped before! Again - log error!
|
||||
```
|
||||
Will probably just get rid of them!
|
||||
|
||||
Think about if you want give warning messages about these deletions in the
|
||||
functions.
|
||||
|
||||
## Card indices go from 0 to 7 (instead of 0 to 5 as expected)
|
||||
|
||||
See `questions_number-of-cards.R` for details.
|
||||
|
||||
## Extracting topics
|
||||
|
||||
When I extract the topics from `index.html` I get different topics, than
|
||||
when I get them from `<artwork>.html`. At first glance, it looks like using
|
||||
`index.html` actually gives the wrong results.
|
||||
|
||||
```
|
||||
topics <- extract_topics(artworks, "index.xml", path)
|
||||
topics2 <- extract_topics(artworks, paste0(artworks, ".xml"), path)
|
||||
|
||||
topics[!topics$file_name %in% topics2$file_name, ]
|
||||
# artwork file_name topic index
|
||||
# 072 072_artist.xml artist 1
|
||||
# 073 073_artist.xml artist 1
|
||||
# 110 110_technik.xml technik 2
|
||||
topics2[!topics2$file_name %in% topics$file_name, ]
|
||||
# artwork file_name topic index
|
||||
# 031 031_vergleich.xml extra info 6
|
||||
# 033 033_technik.xml technik 2
|
||||
# 055 055_vergleich4.xml extra info 5
|
||||
# 063 063_thema3.xml thema 3
|
||||
# 063 063_extrainfo1.xml thema 4
|
||||
# 072 072_artist2.xml artist 1
|
||||
# 073 073_artist2.xml artist 1
|
||||
# 099 099_technik.xml technik 2
|
||||
# 110 110_technikneu.xml technik 2
|
||||
```
|
||||
|
||||
For artwork 031, `index.html` only defines 5 cards (the 6th is commented
|
||||
out), but `topicNumber` for this artwork has 6 different entries. I will
|
||||
therefore extract the topics from `<artwork>.html`. (This seems also better
|
||||
compatible with other data sets like 8o8m.
|
||||
|
||||
# Reading list
|
||||
|
||||
* @Arizmendi2022 [$-$]
|
||||
* @Bannert2014 [x]
|
||||
* @Bousbia2010 [$-$]
|
||||
* @Cerezo2020
|
||||
* @GerjetsSchwan2021 [x]
|
||||
* @Goldhammer2020
|
||||
* @Guenther2007
|
||||
* @HuberBannert2023 [x]
|
||||
* @Kroehne2018
|
||||
* @SchwanGerjets2021 [x]
|
||||
* @vanderAalst2016 [Chap. 2, x]
|
||||
* @vanderAalst2016 [Chap. 3]
|
||||
* @vanderAalst2016 [Chap. 5, x]
|
||||
* @Wang2019
|
||||
|
||||
# Open stuff
|
||||
|
||||
* Angle from which people approach table in Braunschweig? Consider in
|
||||
rotation variable?
|
||||
* Time limit for `case` variable different for different events? (openTopic
|
||||
should be opened the longest)
|
||||
--> I think this is not relevant since I am looking at time *between*
|
||||
events!
|
||||
|
||||
# Stuff AK found interesting
|
||||
|
||||
* Pre/post corona
|
||||
* Identify school classes
|
||||
* How many persons are present at the table?
|
||||
|
||||
# Other potential questions
|
||||
|
||||
* "Bursts"
|
||||
* 1st vs. 2nd half of the day
|
||||
* Can we identify "types of art"? With clustering or something?
|
||||
* Possible to estimate how many persons per day? Maybe average of certain
|
||||
weekdays? ... ?
|
||||
|
||||
|
|
@ -1,46 +1,6 @@
|
|||
#' ---
|
||||
#' title: "Preprocessing raw log files"
|
||||
#' author: "Nora Wickelmaier"
|
||||
#' date: "`r Sys.Date()`"
|
||||
#' output:
|
||||
#' html_document:
|
||||
#' default
|
||||
#' pdf_document:
|
||||
#' toc: true
|
||||
#' number_sections: true
|
||||
#' geometry: margin = 2.5cm
|
||||
#' ---
|
||||
|
||||
# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/code")
|
||||
|
||||
#+ setup, include = FALSE
|
||||
knitr::opts_chunk$set(warning = FALSE, message = FALSE)
|
||||
|
||||
#' The following events can be extracted from the log files:
|
||||
#'
|
||||
#' ```
|
||||
#' LogEntry classes:
|
||||
#' TRANSFORM_START: "Transform start" --> "Transformation Start" in Tool
|
||||
#' TRANSFORM_STOP: "Transform stop"
|
||||
#' START_APPLICATION: "Start Application"
|
||||
#' SHOW_APPLICATION: "Show Application"
|
||||
#' SHOW_INFO: "Show Info" --> "Flip Card" in Tool
|
||||
#' SHOW_FRONT: "Show Front"
|
||||
#' SHOW_POPUP: "ShowPopup" --> "Show Popup" in Tool
|
||||
#' HIDE_POPUP: "HidePopup"
|
||||
#' ARTWORK: "Artwork" --> "Show Topic" in Tool
|
||||
#' ```
|
||||
|
||||
#' Choose which folders with raw log files should be included:
|
||||
|
||||
folders <- "all"
|
||||
#folders <- "_2016b"
|
||||
|
||||
dirpaths <- paste0("../data/haum_logs_2016-2023/", folders)
|
||||
|
||||
fnames <- dir(dirpaths, pattern = "*.log", full.names = TRUE)
|
||||
length(fnames)
|
||||
head(fnames)
|
||||
###### HELPER ######
|
||||
|
||||
# Need to left pad file names. If I do not do this, the sorting of the
|
||||
# timestamps will be off and I get negative durations later on since the
|
||||
|
|
@ -70,6 +30,18 @@ leftpad_fnames <- function(x) {
|
|||
res
|
||||
}
|
||||
|
||||
##### CONTENT ######
|
||||
|
||||
# Choose which folders with raw log files should be included
|
||||
|
||||
folders <- "all"
|
||||
#folders <- "_2016b"
|
||||
|
||||
dirpaths <- paste0("../data/haum_logs_2016-2023/", folders)
|
||||
|
||||
fnames <- dir(dirpaths, pattern = "*.log", full.names = TRUE)
|
||||
length(fnames)
|
||||
head(fnames)
|
||||
|
||||
logs <- lapply(fnames, readLines)
|
||||
nlog <- sapply(logs, length)
|
||||
|
|
@ -77,31 +49,19 @@ dat <- data.frame(fileId = rep(leftpad_fnames(fnames), nlog),
|
|||
logs = unlist(logs))
|
||||
head(dat$logs)
|
||||
|
||||
#' Remove corrupted lines
|
||||
# Remove corrupted lines
|
||||
|
||||
# Warning messages:
|
||||
# incomplete final line found on '_2016/2016_11_18-11_31_0.log'
|
||||
# incomplete final line found on '_2016/2016_11_18-11_38_30.log'
|
||||
# incomplete final line found on '_2016/2016_11_18-11_40_36.log'
|
||||
# ...
|
||||
|
||||
## --> files have a last line that looks like a binary entry??
|
||||
|
||||
# From LogEntry.as:
|
||||
# //pm: inserted this check to account for some broken logfiles
|
||||
# if (metaData[1] == null){
|
||||
# trace("corrupt line... still do not know how these came to happen.");
|
||||
|
||||
# corrupt lines are "" and need to be removed
|
||||
d1 <- dim(dat)[1]
|
||||
dat <- subset(dat, dat$logs != "")
|
||||
d2 <- dim(dat)[1]
|
||||
|
||||
#' The files contain `r d1-d2` corrupt lines that were remooved from the
|
||||
#' data.
|
||||
#'
|
||||
# TODO: Catch this in a function and give back a meaningful warning
|
||||
# The files contain `r d1-d2` corrupt lines that were removed from the
|
||||
# data.
|
||||
|
||||
#' ### Extract relevant infos
|
||||
# Extract relevant infos
|
||||
|
||||
date <- sapply(dat$logs, gsub,
|
||||
pattern = "^\\[(.*)\\], \\[.*$",
|
||||
|
|
@ -139,8 +99,6 @@ ts_elements <- strsplit(timestamp, ":")
|
|||
time_ms <- as.numeric(sapply(ts_elements, function(x) x[4])) +
|
||||
as.numeric(sapply(ts_elements, function(x) x[3])) * 1000 +
|
||||
as.numeric(sapply(ts_elements, function(x) x[2])) * 1000 * 60
|
||||
# TODO: Maybe change to simple gsub()...
|
||||
# --> This is theoretically sound but a lot of lines for just removing ":"
|
||||
|
||||
dat$date <- lubridate::parse_date_time(date, "bdyHMSOp")
|
||||
dat$timeMs <- time_ms
|
||||
|
|
@ -156,17 +114,11 @@ dat$rotation <- moves[,4]
|
|||
dat$logs <- NULL
|
||||
# remove original log files from data so file becomes smaller
|
||||
|
||||
str(dat)
|
||||
|
||||
head(dat, 20)
|
||||
|
||||
# sort by fileId, since reading in by file names does not make sense because of
|
||||
# missing left zero padding
|
||||
# sort by fileId, since reading in by file names does not make sense
|
||||
# because of missing left zero padding
|
||||
dat <- dat[order(dat$fileId, dat$date, dat$timeMs), ]
|
||||
|
||||
## TODO: Replace artwork and popup numbers with informative strings
|
||||
|
||||
#' ### Save data frame
|
||||
# Export data
|
||||
|
||||
write.table(dat, "../data/rawdata_logfiles.csv",
|
||||
sep = ";", quote = FALSE, row.names = FALSE)
|
||||
|
|
|
|||
|
|
@ -2,8 +2,7 @@
|
|||
|
||||
source("functions.R")
|
||||
|
||||
# Read data
|
||||
|
||||
# Read data ##############################################################
|
||||
dat0 <- read.table("../data/rawdata_logfiles_small.csv", sep = ";",
|
||||
header = TRUE)
|
||||
dat0$date <- as.POSIXct(dat0$date)
|
||||
|
|
@ -13,7 +12,7 @@ dat0$glossar <- ifelse(dat0$artwork == "glossar", 1, 0)
|
|||
dat <- subset(dat0, !(dat0$event %in% c("Start Application",
|
||||
"Show Application")))
|
||||
|
||||
# Add trace variable
|
||||
# Add trace variable #####################################################
|
||||
dat1 <- add_trace(dat)
|
||||
|
||||
# Close events
|
||||
|
|
@ -21,7 +20,9 @@ dat2 <- rbind(close_events(dat1, "move"),
|
|||
close_events(dat1, "flipCard"),
|
||||
close_events(dat1, "openTopic"),
|
||||
close_events(dat1, "openPopup"))
|
||||
|
||||
dat2 <- dat2[order(dat2$date.start, dat2$fileId.start), ]
|
||||
|
||||
# Remove durations when event spans more than one log file, since they are
|
||||
# not interpretable
|
||||
dat2[which(dat2$fileId.start != dat2$fileId.stop), "duration"] <- NA
|
||||
|
|
@ -29,13 +30,12 @@ dat2[which(dat2$fileId.start != dat2$fileId.stop), "duration"] <- NA
|
|||
# Remove all events that do not have a `date.start`
|
||||
dat2 <- dat2[!is.na(dat2$date.start), ]
|
||||
rownames(dat2) <- NULL
|
||||
# TODO: Throw warning about this
|
||||
|
||||
#summary(dat2)
|
||||
|
||||
# Add case variable
|
||||
# Add case variable ######################################################
|
||||
dat3 <- add_case(dat2)
|
||||
|
||||
# Add event ID
|
||||
# Add event ID ###########################################################
|
||||
dat3$eventId <- seq_len(nrow(dat3))
|
||||
dat3 <- dat3[, c("fileId.start", "fileId.stop", "eventId", "case",
|
||||
"trace", "glossar", "event", "artwork",
|
||||
|
|
@ -46,17 +46,19 @@ dat3 <- dat3[, c("fileId.start", "fileId.stop", "eventId", "case",
|
|||
"scaleSize", "rotation.start", "rotation.stop",
|
||||
"rotationDegree")]
|
||||
|
||||
# Add trace for move events
|
||||
# Add trace for move events ##############################################
|
||||
dat4 <- add_trace_moves(dat3)
|
||||
|
||||
# Add topics: file names and topics
|
||||
# Add topics: file names and topics ######################################
|
||||
artworks <- unique(dat4$artwork)
|
||||
topics <- extract_topics(artworks, pattern = paste0(artworks, ".xml"),
|
||||
path = "../data/ContentEyevisit/eyevisit_cards_light/")
|
||||
|
||||
dat5 <- add_topic(dat4, topics = topics)
|
||||
|
||||
# Export data
|
||||
# TODO: Replace artwork with informative strings
|
||||
|
||||
# Export data ############################################################
|
||||
write.table(dat5, "../data/event_logfiles.csv", sep = ";",
|
||||
row.names = FALSE)
|
||||
|
||||
|
|
|
|||
|
|
@ -40,14 +40,11 @@ add_trace <- function(data, glossar_dict = "../data/glossar_dict.RData") {
|
|||
load(glossar_dict)
|
||||
lut <- glossar_dict[glossar_dict$glossar_file %in% glossar_files, ]
|
||||
|
||||
head(subdata2[, c("artwork", "event", "popup", "trace")], 20)
|
||||
|
||||
inside <- glossar_files[glossar_files %in%
|
||||
lut[sapply(lut$artwork, length) == 1,
|
||||
"glossar_file"]]
|
||||
single_art <- unlist(lut[lut$glossar_file %in% inside, "artwork"])
|
||||
|
||||
|
||||
for (file in lut$glossar_file) {
|
||||
|
||||
artwork_list <- unlist(lut[lut$glossar_file == file, "artwork"])
|
||||
|
|
|
|||
Loading…
Reference in New Issue