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• omxplayer freezes with videos generated with FFMPEG

  31 décembre 2020, par Chocksmith

  Omxplayer won't play any videos generated with FFmpeg on a Raspberry Pi

  


  I found this thread showing that it is necessary to include '-profile baseline -level 3.0' parameters : https://github.com/popcornmix/omxplayer/issues/577

  


  The full command is :

  


  ffmpeg -framerate 1/10 -pattern_type glob -i '*.jpg' -c:v libx264 -pix_fmt yuv420p -profile baseline -level 3.0 images.mp4


  


  I did that and now I am experiencing intermittent behavior.

  


  Sometimes it works and sometimes it does not work. I cannot explain why/when it plays or not.

  


  I also found a thread showing that it is necessary to upgrade the firmware and player. I did that and still having the same issue.

  


  Here is an example. First time it plays ok. Second time it freezes.

  


  First time : creating mp4

  


  (env) pi@raspberrypi:~/mkt $ ffmpeg -framerate 1/10 -pattern_type glob -i 'mensagens/*.jpeg' -c:v libx264 -pix_fmt yuv420p -profile baseline -level 3.0 images.mp4
ffmpeg version 4.1.6-1~deb10u1+rpt1 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 8 (Raspbian 8.3.0-6+rpi1)
  configuration: --prefix=/usr --extra-version='1~deb10u1+rpt1' --toolchain=hardened --incdir=/usr/include/arm-linux-gnueabihf --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-omx-rpi --enable-mmal --enable-neon --enable-rpi --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared --libdir=/usr/lib/arm-linux-gnueabihf --cpu=arm1176jzf-s --arch=arm
  libavutil      56. 22.100 / 56. 22.100
  libavcodec     58. 35.100 / 58. 35.100
  libavformat    58. 20.100 / 58. 20.100
  libavdevice    58.  5.100 / 58.  5.100
  libavfilter     7. 40.101 /  7. 40.101
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  3.100 /  5.  3.100
  libswresample   3.  3.100 /  3.  3.100
  libpostproc    55.  3.100 / 55.  3.100
Input #0, image2, from 'mensagens/*.jpeg':
  Duration: 00:01:10.00, start: 0.000000, bitrate: N/A
    Stream #0:0: Video: mjpeg, yuvj444p(pc, bt470bg/unknown/unknown), 1024x768 [SAR 72:72 DAR 4:3], 0.10 fps, 0.10 tbr, 0.10 tbn, 0.10 tbc
Please use -profile:a or -profile:v, -profile is ambiguous
Stream mapping:
  Stream #0:0 -> #0:0 (mjpeg (native) -> h264 (libx264))
Press [q] to stop, [?] for help
[swscaler @ 0x182ad70] deprecated pixel format used, make sure you did set range correctly
[libx264 @ 0x17b1170] using SAR=1/1
[libx264 @ 0x17b1170] frame MB size (64x48) > level limit (1620)
[libx264 @ 0x17b1170] using cpu capabilities: none!
[libx264 @ 0x17b1170] profile Constrained Baseline, level 3.0
[libx264 @ 0x17b1170] 264 - core 155 r2917 0a84d98 - H.264/MPEG-4 AVC codec - Copyleft 2003-2018 - http://www.videolan.org/x264.html - options: cabac=0 ref=2 deblock=1:0:0 analyse=0x1:0x111 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=1 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=0 weightp=0 keyint=250 keyint_min=1 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, mp4, to 'images.mp4':
  Metadata:
    encoder         : Lavf58.20.100
    Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuv420p, 1024x768 [SAR 1:1 DAR 4:3], q=-1--1, 0.10 fps, 16384 tbn, 0.10 tbc
    Metadata:
      encoder         : Lavc58.35.100 libx264
    Side data:
      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
frame=    7 fps=0.7 q=15.0 Lsize=      79kB time=00:01:00.00 bitrate=  10.8kbits/s speed=5.66x    
video:78kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 1.085207%
[libx264 @ 0x17b1170] frame I:3     Avg QP: 2.03  size: 14789
[libx264 @ 0x17b1170] frame P:4     Avg QP: 5.28  size:  8794
[libx264 @ 0x17b1170] mb I  I16..4: 91.0%  0.0%  9.0%
[libx264 @ 0x17b1170] mb P  I16..4: 26.1%  0.0%  3.8%  P16..4:  3.4%  1.3%  1.0%  0.0%  0.0%    skip:64.4%
[libx264 @ 0x17b1170] coded y,uvDC,uvAC intra: 6.5% 0.0% 0.0% inter: 2.8% 0.0% 0.0%
[libx264 @ 0x17b1170] i16 v,h,dc,p: 97%  1%  2%  0%
[libx264 @ 0x17b1170] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 41% 19% 20%  4%  3%  4%  3%  3%  3%
[libx264 @ 0x17b1170] i8c dc,h,v,p: 100%  0%  0%  0%
[libx264 @ 0x17b1170] ref P L0: 55.1% 44.9%
[libx264 @ 0x17b1170] kb/s:9.09


  


  First time playing mp4 (it plays OK) :

  


  (env) pi@raspberrypi:~/mkt $ omxplayer images.mp4 
Invalid framerate 0, using forced 25fps and just trust timestamps
Video codec omx-h264 width 1024 height 768 profile 578 fps 25.000000
Subtitle count: 0, state: off, index: 1, delay: 0
V:PortSettingsChanged: 1024x768@0.10 interlace:0 deinterlace:0 anaglyph:0 par:1.00 display:0 layer:0 alpha:255 aspectMode:0
have a nice day ;)


  


  Second time creating mp4 (nothing changes) :

  


  (env) pi@raspberrypi:~/mkt $ ffmpeg -framerate 1/10 -pattern_type glob -i 'mensagens/*.jpeg' -c:v libx264 -pix_fmt yuv420p -profile baseline -level 3.0 images.mp4
ffmpeg version 4.1.6-1~deb10u1+rpt1 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 8 (Raspbian 8.3.0-6+rpi1)
  configuration: --prefix=/usr --extra-version='1~deb10u1+rpt1' --toolchain=hardened --incdir=/usr/include/arm-linux-gnueabihf --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-omx-rpi --enable-mmal --enable-neon --enable-rpi --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared --libdir=/usr/lib/arm-linux-gnueabihf --cpu=arm1176jzf-s --arch=arm
  libavutil      56. 22.100 / 56. 22.100
  libavcodec     58. 35.100 / 58. 35.100
  libavformat    58. 20.100 / 58. 20.100
  libavdevice    58.  5.100 / 58.  5.100
  libavfilter     7. 40.101 /  7. 40.101
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  3.100 /  5.  3.100
  libswresample   3.  3.100 /  3.  3.100
  libpostproc    55.  3.100 / 55.  3.100
Input #0, image2, from 'mensagens/*.jpeg':
  Duration: 00:01:10.00, start: 0.000000, bitrate: N/A
    Stream #0:0: Video: mjpeg, yuvj444p(pc, bt470bg/unknown/unknown), 1024x768 [SAR 72:72 DAR 4:3], 0.10 fps, 0.10 tbr, 0.10 tbn, 0.10 tbc
Please use -profile:a or -profile:v, -profile is ambiguous
File 'images.mp4' already exists. Overwrite ? [y/N] y
Stream mapping:
  Stream #0:0 -> #0:0 (mjpeg (native) -> h264 (libx264))
Press [q] to stop, [?] for help
[swscaler @ 0x1c5fd70] deprecated pixel format used, make sure you did set range correctly
[libx264 @ 0x1be6170] using SAR=1/1
[libx264 @ 0x1be6170] frame MB size (64x48) > level limit (1620)
[libx264 @ 0x1be6170] using cpu capabilities: none!
[libx264 @ 0x1be6170] profile Constrained Baseline, level 3.0
[libx264 @ 0x1be6170] 264 - core 155 r2917 0a84d98 - H.264/MPEG-4 AVC codec - Copyleft 2003-2018 - http://www.videolan.org/x264.html - options: cabac=0 ref=2 deblock=1:0:0 analyse=0x1:0x111 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=1 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=0 weightp=0 keyint=250 keyint_min=1 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, mp4, to 'images.mp4':
  Metadata:
    encoder         : Lavf58.20.100
    Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuv420p, 1024x768 [SAR 1:1 DAR 4:3], q=-1--1, 0.10 fps, 16384 tbn, 0.10 tbc
    Metadata:
      encoder         : Lavc58.35.100 libx264
    Side data:
      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
frame=    7 fps=0.7 q=15.0 Lsize=      79kB time=00:01:00.00 bitrate=  10.8kbits/s speed=5.78x    
video:78kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 1.085207%
[libx264 @ 0x1be6170] frame I:3     Avg QP: 2.03  size: 14789
[libx264 @ 0x1be6170] frame P:4     Avg QP: 5.28  size:  8794
[libx264 @ 0x1be6170] mb I  I16..4: 91.0%  0.0%  9.0%
[libx264 @ 0x1be6170] mb P  I16..4: 26.1%  0.0%  3.8%  P16..4:  3.4%  1.3%  1.0%  0.0%  0.0%    skip:64.4%
[libx264 @ 0x1be6170] coded y,uvDC,uvAC intra: 6.5% 0.0% 0.0% inter: 2.8% 0.0% 0.0%
[libx264 @ 0x1be6170] i16 v,h,dc,p: 97%  1%  2%  0%
[libx264 @ 0x1be6170] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 41% 19% 20%  4%  3%  4%  3%  3%  3%
[libx264 @ 0x1be6170] i8c dc,h,v,p: 100%  0%  0%  0%
[libx264 @ 0x1be6170] ref P L0: 55.1% 44.9%
[libx264 @ 0x1be6170] kb/s:9.09


  


  Second time playing mp4 (it freezes. I had to ctrl-c to interrupt) :

  


  (env) pi@raspberrypi:~/mkt $ omxplayer images.mp4 
Invalid framerate 0, using forced 25fps and just trust timestamps
Video codec omx-h264 width 1024 height 768 profile 578 fps 25.000000
Subtitle count: 0, state: off, index: 1, delay: 0
Stopped at: 00:00:00
have a nice day ;)


  


• Privacy in Business : What Is It and Why Is It Important ?

  13 juillet 2022, par Erin — Privacy

  Privacy concerns loom large among consumers. Yet, businesses remain reluctant to change the old ways of doing things until they become an operational nuisance. 

  More and more businesses are slowly starting to feel the pressure to incorporate privacy best practices. But what exactly does privacy mean in business ? And why is it important for businesses to protect users’ privacy ? 

  In this blog, we’ll answer all of these questions and more. 

  What is Privacy in Business ?

  In the corporate world, privacy stands for the business decision to use collected consumer data in a safe, secure and compliant way. 

  Companies with a privacy-centred culture : 

  • Get explicit user consent to tracking, opt-ins and data sharing 
  • Collect strictly necessary data in compliance with regulations 
  • Ask for permissions to collect, process and store sensitive data 
  • Provide transparent explanations about data operationalisation and usage 
  • Have mechanisms for data collection opt-outs and data removal requests 
  • Implement security controls for storing collected data and limit access permissions to it 

  In other words : They treat consumers’ data with utmost integrity and security – and provide reassurances of ethical data usage. 

  What Are the Ethical Business Issues Related to Privacy ?

  Consumer data analytics has been around for decades. But digital technologies – ubiquitous connectivity, social media networks, data science and machine learning – increased the magnitude and sophistication of customer profiling.

  Big Tech companies like Google and Facebook, among others, capture millions of data points about users. These include general demographics data like “age” or “gender”, as well as more granular insights such as “income”, “past browsing history” or “recently visited geo-locations”. 

  When combined, such personally identifiable information (PII) can be used to approximate the user’s exact address, frequently purchased goods, political beliefs or past medical conditions. Then such information is shared with third parties such as advertisers. 

  That’s when ethical issues arise. 

  The Cambridge Analytica data scandal is a prime example of consumer data that was unethically exploited. 

  Over the years, Google also faced a series of regulatory issues surrounding consumer privacy breaches :

  • In 2021, a Google Chrome browser update put some 2.6 billion users at risk of “surveillance, manipulation and abuse” by providing third parties with data on device usage. 
  • The same year, Google was taken to court for failing to provide full disclosures on tracking performed in Google Chrome incognito mode. A $5 billion lawsuit is still pending.
  • As of 2022, Google Analytics 4 is considered GDPR non-compliant and was branded “illegal” by several European countries. 

  If you are curious, learn more about Google Analytics privacy issues. 

  The bigger issue ? Big Tech companies make the businesses that use their technologies (unknowingly) complicit in consumer data violations.

  In 2022, the Belgian data regulator found the official IAB Europe framework for user consent gathering in breach of GDPR. The framework was used by all major AdTech platforms to issue pop-ups for user consent to tracking. Now ad platforms must delete all data gathered through these. Biggest advertisers such as Procter & Gamble, Unilever, IBM and Mastercard among others, also received a notice about data removal and a regulatory warning on further repercussions if they fail to comply. 

  Big Tech firms have given brands unprecedented access to granular consumer data. Unrestricted access, however, also opened the door to data abuse and unethical use. 

  Examples of Unethical Data Usage by Businesses 

  • Data hoarding means excessively harvesting all available consumer data because a possibility to do so exists, often using murky consent mechanisms. Yet, 85% of collected Big Data is either dark or redundant, obsolete or trivial (ROT).
  • Invasive personalisation based on sensitive user information (or second-guesses), like a recent US marketing campaign, congratulating women on pregnancy (even if they weren’t expecting). Overall, 75% of consumers find most forms of personalisation somewhat creepy. 22% also said they’d leave for another brand due to creepy experiences.
  • Hyper-targeted advertising campaigns based on data consumers would prefer not to share. A recent investigation found that advertising platforms often assign sensitive labels to users (as part of their ad profiles), indicative of their religion, mental issues, history with abuse and so on. This allows advertisers to target such consumers with dubious ads. 

  Ultimately, excessive data collection, paired with poor data protection in business settings, results in major data breaches and costly damage control. Given that cyber attacks are on the rise, every business is vulnerable. 

  Why Should a Business Be Concerned About Protecting the Privacy of Its Customers ?

  Businesses must prioritise customer privacy because that’s what is expected of them. Globally, 89% of consumers say they care about their privacy. 

  As frequent stories about unethical data usage, excessive tracking and data breaches surface online, even more grow more concerned about protecting their data. Many publicly urge companies to take action. Others curtail their relationships with brands privately. 

  

  On average, 45% of consumers feel uncomfortable about sharing personal data. According to KPMG, 78% of American consumers have fears about the amount of data being collected. 40% of them also don’t trust companies to use their data ethically. Among Europeans, 41% are unwilling to share any personal data with businesses. 

  Because the demand for online privacy is rising, progressive companies now treat privacy as a competitive advantage. 

  For example, the encrypted messaging app Signal gained over 42 million active users in a year because it offers better data security and privacy protection. 

  ProtonMail, a privacy-centred email client, also amassed a 50 million user base in several years thanks to a “fundamentally stronger definition of privacy”.

  The growth of privacy-mindful businesses speaks volumes. And even more good things happen to privacy-mindful businesses : 

  • Higher consumer trust and loyalty 
  • Improved attractiveness to investors
  • Less complex compliance
  • Minimum cybersecurity exposure 
  • Better agility and innovation

  It’s time to start pursuing them ! Learn how to embed privacy and security into your operations.

• What Is Data Ethics & Why Is It Important in Business ?

  9 mai 2024, par Erin

  Data is powerful — every business on earth uses data. But some are leveraging it more than others.

  The problem ?

  Not all businesses are using data ethically.

  You need to collect, store, and analyse data to grow your business. But, if you aren’t careful, you could be crossing the line with your data usage into unethical territories.

  In a society where data is more valuable than ever, it’s crucial you perform ethical practices.

  In this article, we break down what data ethics is, why it’s important in business and how you can implement proper data ethics to ensure you stay compliant while growing your business.

  What is data ethics ?

  Data ethics are how a business collects, protects and uses data.

  It’s one field of ethics focused on organisations’ moral obligation to collect, track, analyse and interpret data correctly.

  

  Data ethics analyses multiple ways we use data :

  • Collecting data
  • Generating data
  • Tracking data
  • Analysing data
  • Interpreting data
  • Implementing activities based on data

  Data ethics is a field that asks, “Is this right or wrong ?”

  And it also asks, “Can we use data for good ?”

  If businesses use data unethically, they could get into serious hot water with their customers and even with the law.

  You need to use data to ensure you grow your business to the best of your ability. But, to maintain a clean slate in the eyes of your customers and authorities, you need to ensure you have strong data ethics.

  Why you need to follow data ethics principles

  In 2018, hackers broke into British Airways’ website by inserting harmful code, leading website visitors to a fraudulent site. 

  The result ? 

  British Airways customers gave their information to the hackers without realising it : credit cards, personal information, login information, addresses and more.

  While this was a malicious attack, the reality is that data is an integral part of everyday life. Businesses need to do everything they can to protect their customers’ data and use it ethically.

  Data ethics is crucial to understand as it sets the standard for what’s right and wrong for businesses. Without a clear grasp of data ethics, companies will willingly or neglectfully misuse data.

  With a firm foundation of data ethics, businesses worldwide can make a collective effort to function smoothly, protect their customers, and, of course, protect their own reputation. 

  3 benefits of leaning into data ethics

  We’re currently transitioning to a new world led by artificial intelligence.

  While AI presents endless opportunities for innovation in the business world, there are also countless risks at play, and it’s never been more important to develop trust with your customers and stakeholders.

  With an influx of data being created and tracked daily, you need to ensure your business is prioritising data ethics to ensure you maintain trust with your customers moving forward.

  

  Here are three benefits of data ethics that will help you develop trust, maintain a solid reputation and stay compliant to continue growing your business :

  1. Compliance with data privacy

  Privacy is everything. 

  In a world where our data is being collected nonstop, and we live more public lives than ever with social media, AI and an influx of recording and tracking in everyday life, you need to protect the privacy of your customers.

  One crucial way to protect that privacy is by complying with major data privacy regulations.

  Some of the most common regulations you need to remain compliant with include :

  • General Data Protection Regulation (GDPR)
  • California Consumer Privacy Act (CCPA)
  • Health Insurance Portability and Accountability Act (HIPAA)
  • General Personal Data Protection Law (LGPD)
  • Privacy and Electronic Communications (EC Directive) Regulations (PECR)

  While these regulations don’t directly address ethics, there’s a core overlap between privacy requirements like accountability, lawfulness and AI ethics.

  Matomo ensures you protect the privacy of your web and app users so you can track and improve your website performance with peace of mind.

  2. Maintain a good reputation

  While data ethics can help you maintain data privacy compliance, it can also help you maintain a good reputation online and offline.

  All it takes is one bad event like the British Airways breach for your company’s reputation to be ruined.

  If you want to keep a solid reputation and maintain trust with your stakeholders, customers and lawmakers, then you need to focus on developing strong data ethics.

  Businesses that invest time in establishing proper data ethics set the right foundation to protect their reputation, develop trust with stakeholders and create goodwill and loyalty.

  3. Increased trust means greater revenue

  What happens when you establish proper data ethics ?

  You’ll gain the trust of your customers, maintain a solid reputation and increase your brand image.

  Customers who trust you to protect their privacy and data want to keep doing business with you.

  So, what’s the end result for a business that values data ethics ?

  You’ll generate more revenue in the long run. Trust is one thing you should never put on the back burner if you have plans to keep growing your business. By leaning more into data ethics, you’ll be able to build that brand reputation that helps people feel comfortable buying your products and services on repeat.

  While spending time and money on data ethics may seem like an annoyance, the reality is that it’s a business investment that will pay dividends for years to come.

  5 core data ethics principles

  So, what exactly is involved in data ethics ?

  For most people, data ethics is a pretty broad and vague term. If you’re curious about the core pillars of data ethics, then keep reading.

  Here are five core data ethical principles you need to follow to ensure you’re protecting your customers’ data and maintaining trust :

  

  1. Data ownership

  The individual owns the data, not you. This is the first principle of data ethics. You don’t have control over someone else’s data. It’s theirs, and they have full ownership over it.

  Just as stealing a TV from an electronics store is a crime, stealing (or collecting) someone’s personal data without their consent is considered unlawful and unethical.

  Consent is the only way to ethically “own” someone’s data.

  How can you collect someone’s data ethically ?

  • Digital privacy policies
  • Signed, written agreements
  • Popups with checkboxes that allow you to track users’ behaviour

  Essentially, anytime you’re collecting data from your website or app users, you need to ensure you’re asking permission for that data.

  You should never assume a website visitor or customer is okay with you collecting your data automatically. Instead, ask permission to collect, track and use their data to avoid legal and ethical issues.

  2. Transparency

  The second core principle of data ethics within business is transparency. This means you need to be fully transparent on when, where and how you :

  • Collect data
  • Store data
  • Use data

  In other words, you need to allow your customers and website visitors to have a window inside your data activities.

  They need to be able to see exactly how you plan on using the data you’re collecting from them.

  For example, imagine you implemented a new initiative to personalise the website experience for each user based on individual behaviour. To do this, you’ll need to track cookies. In this case, you’d need to write up a new policy stating how this behavioural data is going to be collected, tracked and used.

  It’s within your website visitors’ rights to access this information so they can choose whether or not they want to accept or decline your website’s cookies.

  With any new data collection or tracking, you need to be 100% clear about how you’re going to use the data. You can’t be deceptive, misleading, or withholding any information on how you will use the data, as this is unethical and, in many cases, unlawful.

  3. Privacy

  Another important branch of ethics is privacy. The ethical implications of this should be obvious.

  When your users, visitors, or customers enter your sphere of influence and you begin collecting data on them, you are responsible for keeping that data private.

  When someone accepts the terms of your data usage, they’re not agreeing to have their data released to the public. They’re agreeing to let you leverage that data as their trusted business provider to better serve them. They expect you to maintain privacy.

  You can’t spread private information to third parties. You can’t blast this data to the public. 

  This is especially important if someone allows you to collect and use their personally identifiable information (PII), such as :

  • First and last name
  • Email address
  • Date of birth
  • Home address
  • Phone number

  To protect your audience’s data, you should only store it in a secure database. 

  

  For example, Matomo’s web analytics solution guarantees the privacy of both your users and analytics data.

  With Matomo, you have complete ownership of your data. Unlike other web analytics solutions that exploit your data for advertising purposes, Matomo users can use analytics with confidence, knowing that their data won’t be sold to advertisers.

  Learn more about data privacy with Matomo here.

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  4. Intention

  When you collect and store data, you need to tell your users why you’re collecting their data. But there’s another principle of data ethics that goes beyond the reason you give your customers.

  Intention is the reason you give yourself for collecting and using the data.

  Before you start collecting and storing data, you should ask yourself the following :

  • Why you need it
  • What you’ll gain from it
  • What changes you’ll be able to make after you analyse the data

  If your intention is wrong in any way, it’s unethical to collect the data :

  • You’re collecting data to hurt others
  • You’re collecting data to profit from your users’ weaknesses
  • You’re collecting data for any other malicious reason

  When you collect data, you need to have the right intentions to maintain proper data ethics ; otherwise, you could harm your brand, break trust and ruin your reputation.

  5. Outcomes

  You may have the best intentions, but sometimes, there are negative outcomes from data use.

  For example, British Airways’ intention was not to allow hackers to gain access and harm their users. But the reality is that their customers’ data was stolen and used for malicious purposes. While this isn’t technically unlawful, the outcome of collecting data ended badly.

  To ensure proper data ethics, you must have good standing with your data. This means protecting your users at all costs, maintaining a good reputation and ensuring proper privacy measures are set up.

  How to implement data ethics as a business leader

  As a business leader, CTO or CEO, it’s your responsibility to implement data ethics within your organisation. Here are some tips to implement data ethics based on the size and stage of your organisation :

  Startups

  If you’re a startup, you need to be mindful of which technology and tools you use to collect, store and use data to help you grow your business.

  It can be a real challenge to juggle all the moving parts of a startup since things can change so quickly. However, it’s crucial to establish a leader and allow easy access to ethical analysis resources to maintain proper data ethics early on.

  Small and medium-sized businesses

  As you begin scaling, you’ll likely be using even more technology. With each new business technique you implement, there will be new ways you’ll be collecting user data. 

  One of the key processes involved in managing data as you grow is to hire engineers who build out different technologies. You must have protocols, best practices and management overseeing the new technologies being built to ensure proper data ethics.

  Global businesses

  Have you scaled internationally ?

  There will be even more rules, laws, regulations and organisations to answer to if you start managing data unethically.

  You should have established teams or departments to ensure you follow proper privacy and data protocols worldwide. When you have a large organisation, you have more money and vast amounts of data. This makes you a bigger target for leaks, ransomware and hackers.

  You should ensure you have cross-departmental groups working to establish ongoing protocols and training to keep your data management in good standing.

  Leverage data ethically with Matomo

  Data is powerful.

  It’s a crucial point of leverage that’s required to stay competitive.

  However, improper use and management of data can give you a bad reputation, break trust and even cause you legal trouble.

  That’s why you must maintain good data ethics within your organisation.

  One of the most important places to set up proper data ethics and privacy measures is with your website analytics.

  Matomo is the leading, privacy-friendly web analytics solution in the world. It automatically collects, stores, and tracks data across your website ethically.

  With over 1 million websites using Matomo, you get to take full control over your website performance with :

  • Accurate data (no data sampling)
  • Privacy-friendly and GDPR-compliant analytics
  • Open-source for transparency and to create a custom solution for you

  Try Matomo free for 21-days. No credit card required.

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