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• 12 ways Matomo Analytics helps you to protect your visitor’s privacy

  5 mai 2020, par InnoCraft — Analytics Tips, Privacy, Security

  This post was originally published on January 11, 2017, and updated on May, 2020.

  At Matomo we think privacy matters. From the beginning, Matomo has had a strong focus on privacy and ensuring the privacy of your visitors and analytics data. 

  Here are some ways how you can ensure your users and visitors privacy by using Matomo (Piwik).

  1. Owning the data gives you power to protect user privacy

  Whether you host Matomo on-premises yourself, or whether you use Matomo’s cloud, YOU keep control of your data and nobody else. By knowing exactly where your data is stored and having full control over what happens to it, you have the power to protect your user’s privacy. No-one else can claim ownership. 

  2. GDPR compliance

  GDPR is one of the most important privacy laws to have come out in the last few years. As such, Matomo takes GDPR compliance very seriously. There’s even a 12-step checklist for you to follow to ensure your Matomo is GDPR compliant. Not only that Matomo is HIPAA, CCPA, LGPD, and PECR compliant.

  3. Data anonymization

  For better privacy by default, Matomo implements a range of data anonymization techniques. One of the main techniques is not recording the full IP address of your visitors. Some countries even require you to anonymize additional info considered Personally Identifiable Information (PII).

  To change the IP anonymization settings go to “Administration > Privacy”. 

  

  4. Configuring Matomo to not process personal data or personally identifiable information (PII)

  To further protect the privacy of your visitors, you can learn how to not process any personal information or PII. 

  5. Deleting old visitor logs

  The is important because visitor logs contain information all the collected raw data about every visitor and every action. You can configure Matomo to automatically delete logs from the database. When you delete old logs, only the real time and visitor log reports will no longer work for this old time period, all other aggregated reports will still work.

  For privacy reasons, we highly recommend that you keep the detailed Matomo logs for only 3 to 6 months and delete older log data. This has one other nice side effect : it will free significant database space, which will, in turn, slightly increase performance !

  

  6. Supporting the Do Not Track preference

  Do Not Track enables users to opt out of any tracking by websites they do not visit, including analytics services, advertising networks, and social platforms. By default, Matomo respects users preference and will not track visitors which have specified “I do not want to be tracked” in their web browsers. Get more information about DoNotTrack.

  To make sure Do Not Track is respected, go to “Administration => Privacy”.

  7. Including an Opt-Out Feature on your website or app

  By embedding the Opt-Out feature in your website, you give your visitors the possibility to opt-out of the tracking. When you go to “Administration > Privacy”, you will be able to copy and paste an HTML Iframe code to embed the opt-out feature for example into your privacy policy page or in your ‘Legal’ page. Your users can then click on a link to opt-out.

  On the Matomo Marketplace there are also some plugins available to customize the Opt-Out experience. For example AjaxOptOut and CustomOptOut.

  

  8. Disabling Live features

  The Real-Time, Visitor Log and Visitor Profile features give you insights into the tracked raw data by showing you details about every visitor and every action they performed. To protect the privacy of your visitors you may decide to prevent access to such features by disabling the “Live” plugin in “Administration => Plugins”. This way only aggregated reports will be shown in your Matomo.

  9. Disabling fingerprinting across websites

  By default, when one of your visitors visits several of your websites, Matomo will create a fingerprint for this user that will be different across the websites to increase the visitors’ privacy. You can make sure that this feature is disabled by going to “Administration => Config file” and verifying that the value of “enable_fingerprinting_across_websites” is set to zero.

  10. Disabling tracking cookies

  Matomo uses first-party cookies to store some information about visitors between visits. In some countries, the legislation requires websites to provide a way for users to opt-out of all tracking, in particular tracking cookies. You can disable cookies by adding one line in the Matomo Javascript code.

  11. Creating the tool of your dreams by developing your own plugins and getting access to the API

  Matomo is an open platform that lets you extend and customise the tracking ; reporting ; and user interface to your needs and to protect your visitors’ privacy the way you want or need it. Learn more in the Matomo Developer Zone. You may also have a look at our Matomo Marketplace where you can find several free and premium features to extend your Matomo.

  12. Transparency

  By default, all information and all collected data in your Matomo server are protected and nobody can access it. However, Matomo allows you to optionally make your collected data public and you can export any Matomo report including the whole dashboard to embed it into your website. This way you can show your users exactly which information you track. When you decide to make reports public, we do our best to protect privacy and automatically hide any Personally Identifiable Information such as the Visitor Profile and we make sure to not show any Visitor IP address and the Visitor ID.

  Bonus tip – A privacy policy template for you

  When you use Matomo to track your visitors, we recommend you update your Privacy Policy to explain how Matomo is used and what data it gathers. Here’s a Privacy Policy template for you to copy on your site.

  Continuous privacy improvements

  We are always interested in improving the privacy. If you miss any feature or have an idea on how to improve the privacy, please let us know.

  More information about all the Matomo features

  If you want to learn more about all the features in Matomo, have a look at our User Guides and FAQ entries.

• ffmpeg conversion from Flac to Ogg produces corrupted files

  8 avril 2021, par experimental

  i transcoded flac files to ogg using this command

  


  ffmpeg -i input.flac -c:a libvorbis -b:a 500k  output.ogg


  


  yes i use 500k to keep the highest quality possible, some of the files are ok, but some of them can not be played - Unsupported format or corrupted file says the foobar - also my icecast streamer cant read it. So there is something wrong with the files.

  


  I believed it was due to the high bitrate so I tried

  


  ffmpeg -i input.flac -c:a libvorbis -b:a 320k  output.ogg


  


  the same happened, some files were ok, some were not playable.
so I tried again with default using this command

  


  ffmpeg -i input.flac -c:a libvorbis output.ogg


  


  same thing. some files were ok, some were corrupted and not playable.

  


  i have no clue why.

  


  both flac and ogg are in the same family, what happened during the transcoding that it became a corrupted file ?

  


  the spectral analysis does not show anything wrong - here it the ogg https://prnt.sc/115zdjl, here is the original flac https://prnt.sc/115zegw

  


  i am really interested what is going on and how to make it work ?

  


  can anyone explain ?

  


  here is complete log

  


      C:\Users\lukas.kotatko>ffmpeg -i "\\192.168.0.128\lukas\online radio resources\Atma FM playlists\channel 1\flac lossless\Tuu\One Thousand Years\02 One Thousand Years.flac" -c:a libvorbis -b:a 500k "\\192.168.0.128\lukas\online radio resources\Atma FM playlists\channel 1\flac lossless\Tuu\One Thousand Years\02 One Thousand Years [500k test].ogg"
ffmpeg version 4.3.1 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 10.2.1 (GCC) 20200726
  configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libdav1d --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libsrt --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-libxvid --enable-libaom --enable-libgsm --disable-w32threads --enable-libmfx --enable-ffnvcodec --enable-cuda-llvm --enable-cuvid --enable-d3d11va --enable-nvenc --enable-nvdec --enable-dxva2 --enable-avisynth --enable-libopenmpt --enable-amf
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
  libpostproc    55.  7.100 / 55.  7.100
Input #0, flac, from '\\192.168.0.128\lukas\online radio resources\Atma FM playlists\channel 1\flac lossless\Tuu\One Thousand Years\02 One Thousand Years.flac':
  Metadata:
    GENRE           : Tribal / Ambient
    ORGANIZATION    : Waveform Records
    ISRC            : 01101-2
    COMMENT         : US reissue featuring the six original tracks plus two taken from the Invocation album.
    MUSICBRAINZ_RELEASEGROUPID: 737d0518-3dc2-36b3-9419-282c0ade0e50
    ORIGINALDATE    : 1993
    ORIGINALYEAR    : 1993
    RELEASETYPE     : album
    MUSICBRAINZ_ALBUMID: f6339129-f662-43a1-93df-2f20540f73cc
    ALBUM           : One Thousand Years
    BARCODE         : 789060110125
    MUSICBRAINZ_ALBUMARTISTID: e05a42e7-60a3-4d2d-983c-51dc4eb67cad
    album_artist    : Tuu
    ALBUMARTISTSORT : Tuu
    ASIN            : B00005B9TT
    SCRIPT          : Latn
    RELEASESTATUS   : official
    LABEL           : Waveform Records
    CATALOGNUMBER   : 01101-2
    RELEASECOUNTRY  : US
    DATE            : 2001-05-08
    TOTALDISCS      : 1
    disc            : 1
    TOTALTRACKS     : 8
    MEDIA           : CD
    MUSICBRAINZ_TRACKID: aef9824d-e4a6-4ae6-aebe-50a83dd14f71
    TITLE           : One Thousand Years
    MUSICBRAINZ_ARTISTID: e05a42e7-60a3-4d2d-983c-51dc4eb67cad
    ARTIST          : Tuu
    ARTISTSORT      : Tuu
    ARTISTS         : Tuu
    MUSICBRAINZ_RELEASETRACKID: 621c9da6-a85d-3f8b-b485-5e6f74a60cd0
    track           : 2
    TRACKTOTAL      : 8
    DISCTOTAL       : 1
  Duration: 00:08:03.67, start: 0.000000, bitrate: 792 kb/s
    Stream #0:0: Audio: flac, 44100 Hz, stereo, s16
    Stream #0:1: Video: mjpeg (Baseline), yuvj420p(pc, bt470bg/unknown/unknown), 600x600 [SAR 1:1 DAR 1:1], 90k tbr, 90k tbn, 90k tbc (attached pic)
    Metadata:
      comment         : Cover (front)
Stream mapping:
  Stream #0:1 -> #0:0 (mjpeg (native) -> theora (libtheora))
  Stream #0:0 -> #0:1 (flac (native) -> vorbis (libvorbis))
Press [q] to stop, [?] for help
[swscaler @ 0000015307581a00] deprecated pixel format used, make sure you did set range correctly
[ogg @ 00000153073f1680] Frame rate very high for a muxer not efficiently supporting it.
Please consider specifying a lower framerate, a different muxer or -vsync 2
Output #0, ogg, to '\\192.168.0.128\lukas\online radio resources\Atma FM playlists\channel 1\flac lossless\Tuu\One Thousand Years\02 One Thousand Years [500k test].ogg':
  Metadata:
    GENRE           : Tribal / Ambient
    ORGANIZATION    : Waveform Records
    ISRC            : 01101-2
    COMMENT         : US reissue featuring the six original tracks plus two taken from the Invocation album.
    MUSICBRAINZ_RELEASEGROUPID: 737d0518-3dc2-36b3-9419-282c0ade0e50
    ORIGINALDATE    : 1993
    ORIGINALYEAR    : 1993
    RELEASETYPE     : album
    MUSICBRAINZ_ALBUMID: f6339129-f662-43a1-93df-2f20540f73cc
    ALBUM           : One Thousand Years
    BARCODE         : 789060110125
    MUSICBRAINZ_ALBUMARTISTID: e05a42e7-60a3-4d2d-983c-51dc4eb67cad
    album_artist    : Tuu
    ALBUMARTISTSORT : Tuu
    ASIN            : B00005B9TT
    SCRIPT          : Latn
    RELEASESTATUS   : official
    LABEL           : Waveform Records
    CATALOGNUMBER   : 01101-2
    RELEASECOUNTRY  : US
    DATE            : 2001-05-08
    TOTALDISCS      : 1
    disc            : 1
    TOTALTRACKS     : 8
    MEDIA           : CD
    MUSICBRAINZ_TRACKID: aef9824d-e4a6-4ae6-aebe-50a83dd14f71
    TITLE           : One Thousand Years
    MUSICBRAINZ_ARTISTID: e05a42e7-60a3-4d2d-983c-51dc4eb67cad
    ARTIST          : Tuu
    ARTISTSORT      : Tuu
    ARTISTS         : Tuu
    MUSICBRAINZ_RELEASETRACKID: 621c9da6-a85d-3f8b-b485-5e6f74a60cd0
    track           : 2
    TRACKTOTAL      : 8
    DISCTOTAL       : 1
    encoder         : Lavf58.45.100
    Stream #0:0: Video: theora (libtheora), yuv420p(progressive), 600x600 [SAR 1:1 DAR 1:1], q=2-31, 200 kb/s, 90k fps, 90k tbn, 90k tbc (attached pic)
    Metadata:
      DESCRIPTION     : Cover (front)
      encoder         : Lavc58.91.100 libtheora
      GENRE           : Tribal / Ambient
      ORGANIZATION    : Waveform Records
      ISRC            : 01101-2
      MUSICBRAINZ_RELEASEGROUPID: 737d0518-3dc2-36b3-9419-282c0ade0e50
      ORIGINALDATE    : 1993
      ORIGINALYEAR    : 1993
      RELEASETYPE     : album
      MUSICBRAINZ_ALBUMID: f6339129-f662-43a1-93df-2f20540f73cc
      ALBUM           : One Thousand Years
      BARCODE         : 789060110125
      MUSICBRAINZ_ALBUMARTISTID: e05a42e7-60a3-4d2d-983c-51dc4eb67cad
      ALBUMARTIST     : Tuu
      ALBUMARTISTSORT : Tuu
      ASIN            : B00005B9TT
      SCRIPT          : Latn
      RELEASESTATUS   : official
      LABEL           : Waveform Records
      CATALOGNUMBER   : 01101-2
      RELEASECOUNTRY  : US
      DATE            : 2001-05-08
      TOTALDISCS      : 1
      DISCNUMBER      : 1
      TOTALTRACKS     : 8
      MEDIA           : CD
      MUSICBRAINZ_TRACKID: aef9824d-e4a6-4ae6-aebe-50a83dd14f71
      TITLE           : One Thousand Years
      MUSICBRAINZ_ARTISTID: e05a42e7-60a3-4d2d-983c-51dc4eb67cad
      ARTIST          : Tuu
      ARTISTSORT      : Tuu
      ARTISTS         : Tuu
      MUSICBRAINZ_RELEASETRACKID: 621c9da6-a85d-3f8b-b485-5e6f74a60cd0
      TRACKNUMBER     : 2
      TRACKTOTAL      : 8
      DISCTOTAL       : 1
    Stream #0:1: Audio: vorbis (libvorbis), 44100 Hz, stereo, fltp (16 bit), 500 kb/s
    Metadata:
      encoder         : Lavc58.91.100 libvorbis
      GENRE           : Tribal / Ambient
      ORGANIZATION    : Waveform Records
      ISRC            : 01101-2
      DESCRIPTION     : US reissue featuring the six original tracks plus two taken from the Invocation album.
      MUSICBRAINZ_RELEASEGROUPID: 737d0518-3dc2-36b3-9419-282c0ade0e50
      ORIGINALDATE    : 1993
      ORIGINALYEAR    : 1993
      RELEASETYPE     : album
      MUSICBRAINZ_ALBUMID: f6339129-f662-43a1-93df-2f20540f73cc
      ALBUM           : One Thousand Years
      BARCODE         : 789060110125
      MUSICBRAINZ_ALBUMARTISTID: e05a42e7-60a3-4d2d-983c-51dc4eb67cad
      ALBUMARTIST     : Tuu
      ALBUMARTISTSORT : Tuu
      ASIN            : B00005B9TT
      SCRIPT          : Latn
      RELEASESTATUS   : official
      LABEL           : Waveform Records
      CATALOGNUMBER   : 01101-2
      RELEASECOUNTRY  : US
      DATE            : 2001-05-08
      TOTALDISCS      : 1
      DISCNUMBER      : 1
      TOTALTRACKS     : 8
      MEDIA           : CD
      MUSICBRAINZ_TRACKID: aef9824d-e4a6-4ae6-aebe-50a83dd14f71
      TITLE           : One Thousand Years
      MUSICBRAINZ_ARTISTID: e05a42e7-60a3-4d2d-983c-51dc4eb67cad
      ARTIST          : Tuu
      ARTISTSORT      : Tuu
      ARTISTS         : Tuu
      MUSICBRAINZ_RELEASETRACKID: 621c9da6-a85d-3f8b-b485-5e6f74a60cd0
      TRACKNUMBER     : 2
      TRACKTOTAL      : 8
      DISCTOTAL       : 1
frame=    1 fps=0.1 q=-0.0 Lsize=   25860kB time=00:08:03.66 bitrate= 438.0kbits/s speed=44.6x
video:8kB audio:25721kB subtitle:0kB other streams:0kB global headers:7kB muxing overhead: 0.511663%


  


• Adjusting The Timetable and SQL Shame

  16 août 2012, par Multimedia Mike — General, Python, sql

  My Game Music Appreciation website has a big problem that many visitors quickly notice and comment upon. The problem looks like this :

  
  
  

  The problem is that all of these songs are 2m30s in length. During the initial import process, unless a chiptune file already had curated length metadata attached, my metadata utility emitted a default play length of 150 seconds. This is not good if you want to listen to all the songs in a soundtrack without interacting with the player page, but have various short songs (think “game over” or other quick jingles) that are over in a few seconds. Such songs still pad out 150 seconds of silence.

  So I needed to correct this. Possible solutions :

  1. Manually : At first, I figured I could ask the database which songs needed fixing and listen to them to determine the proper lengths. Then I realized that there were well over 1400 games affected by this problem. This just screams “automated solution”.
  2. Automatically : Ask the database which songs need fixing and then somehow ask the computer to listen to the songs and decide their proper lengths. This sounds like a winner, provided that I can figure out how to programmatically determine if a song has “finished”.

  SQL Shame
  This play adjustment task has been on my plate for a long time. A key factor that has blocked me is that I couldn’t figure out a single SQL query to feed to the SQLite database underlying the site which would give me all the songs I needed. To be clear, it was very simple and obvious to me how to write a program that would query the database in phases to get all the information. However, I felt that it would be impure to proceed with the task unless I could figure out one giant query to get all the information.

  This always seems to come up whenever I start interacting with a database in any serious way. I call it SQL shame. This task got some traction when I got over this nagging doubt and told myself that there’s nothing wrong with the multi-step query program if it solves the problem at hand.

  Suddenly, I had a flash of inspiration about why the so-called NoSQL movement exists. Maybe there are a lot more people who don’t like trying to derive such long queries and are happy to allow other languages to pick up the slack.

  Estimating Lengths
  Anyway, my solution involved writing a Python script to iterate through all the games whose metadata was output by a certain engine (the one that makes the default play length 150 seconds). For each of those games, the script queries the song table and determines if each song is exactly 150 seconds. If it is, then go to work trying to estimate the true length.

  The forgoing paragraph describes what I figured was possible with only a single (possibly large) SQL query.

  For each song represented in the chiptune file, I ran it through a custom length estimator program. My brilliant (err, naïve) solution to the length estimation problem was to synthesize seconds of audio up to a maximum of 120 seconds (tightening up the default length just a bit) and counting how many of those seconds had all 0 samples. If the count reached 5 consecutive seconds of silence, then the estimator rewound the running length by 5 seconds and declared that to be the proper length. Update the database.

  There were about 1430 chiptune files whose songs needed updates. Some files had 1 single song. Some files had over 100. When I let the script run, it took nearly 65 minutes to process all the files. That was a single-threaded solution, of course. Even though I already had the data I needed, I wanted to try to hand at parallelizing the script. So I went to work with Python’s multiprocessing module and quickly refactored it to use all 4 CPU threads on the machine where the files live. Results :

  • Single-threaded solution : 64m42s to process corpus (22 games/minute)
  • Multi-threaded solution : 18m48s with 4 CPU threads (75 games/minute)

  More than a 3x speedup across 4 CPU threads, which is decent for a primarily CPU-bound operation.

  Epilogue
  I suspect that this task will require some refinement or manual intervention. Maybe there are songs which actually have more than 5 legitimate seconds of silence. Also, I entertained the possibility that some songs would generate very low amplitude noise rather than being perfectly silent. In that case, I could refine the script to stipulate that amplitudes below a certain threshold count as 0. Fortunately, I marked which games were modified by this method, so I can run a new script as necessary.

  SQL Schema
  Here is the schema of my SQlite3 database, for those who want to try their hand at a proper query. I am confident that it’s possible ; I just didn’t have the patience to work it out. The task is to retrieve all the rows from the games table where all of the corresponding songs in the songs table is 150000 milliseconds.
  

  sql

  < view plain text >

  1. CREATE TABLE games
  2.   (
  3.    id INTEGER PRIMARY KEY AUTOINCREMENT,
  4.    uncompressed_sha1 TEXT,
  5.    uncompressed_size INTEGER,
  6.    compressed_sha1 TEXT,
  7.    compressed_size INTEGER,
  8.    system TEXT,
  9.    game TEXT,
  10.    gme_system TEXT default NULL,
  11.    canonical_url TEXT default NULL,
  12.    extension TEXT default "gamemusicxz",
  13.    enabled INTEGER default 1,
  14.    redirect_to_id INT DEFAULT -1,
  15.    play_lengths_modified INT DEFAULT NULL) ;
  16. CREATE TABLE songs
  17.   (
  18.    game_id INTEGER,
  19.    song_number INTEGER NOT NULL,
  20.    song TEXT,
  21.    author TEXT,
  22.    copyright TEXT,
  23.    dumper TEXT,
  24.    length INTEGER,
  25.    intro_length INTEGER,
  26.    loop_length INTEGER,
  27.    play_length INTEGER,
  28.    play_order INTEGER default -1) ;
  29. CREATE TABLE tags
  30.   (
  31.    game_id INTEGER,
  32.    tag TEXT NOT NULL,
  33.    tag_type TEXT default "filename") ;
  34. CREATE INDEX gameid_index_songs ON songs(game_id) ;
  35. CREATE INDEX gameid_index_tag ON tags(game_id) ;
  36. CREATE UNIQUE INDEX sha1_index ON games(uncompressed_sha1) ;