Google says this technique, called "private set intersection," means you don't get to see Google's list of bad credentials, and Google doesn't get to learn your credentials, but the two can be compared for matches.

Download the billions of breached passwords and blacklist them all. Attackers have a copy; so should you.

These massive dumps of free passwords lower the cost of an attack dramatically. Password reuse or password guessing attacks are script kiddie stuff. Defending your organization against such threats is basic due diligence.

They are proof that our openness about our data formats means that you do not have to fear data lock-in.

It’s this third way that we avoid lock-in that is relevant to today’s topic. Our data format design is specified well enough so that people with no connection to AgileBits can write software to be able to handle it.

The second way we avoid locking you into 1Password is through the ability to export data to a more neutral format. Not all versions are yet where we want them to be with respect to export, and we’re working on that. But there is usually some path, if not always a simple click away, to export your 1Password data.

Data Erasure and Storage Time The personal data of the data subject will be erased or blocked as soon as the purpose of storage ceases to apply. The data may be stored beyond that if the European or national legislator has provided for this in EU regulations, laws or other provisions to which the controller is subject. The data will also be erased or blocked if a storage period prescribed by the aforementioned standards expires, unless there is a need for further storage of the data for the conclusion or performance of a contract.

The data is stored in log files to ensure the functionality of the website. In addition, the data serves us to optimize the website and to ensure the security of our information technology systems. An evaluation of the data for marketing purposes does not take place in this context. The legal basis for the temporary storage of the data and the log files is Art. 6 para. 1 lit. f GDPR. Our legitimate interests lie in the above-mentioned purposes.

The temporary storage of the IP address by the system is necessary to enable the website to be delivered to the user's computer. For this the IP address of the user must remain stored for the duration of the session.

In the case of storing the data in log files, this is the case after seven days at the latest. Further storage is possible; in this case, the IP addresses of the users are erased or anonymized, so that an association of the calling client is no longer possible.

The collection of the data for the provision of the website and the storage of the data in log files is absolutely necessary for the operation of the website. Consequently, there is no possibility of objection on the part of the user.

The legal basis for the processing of personal data using cookies is Art. 6 para. 1 lit. f GDPR. Our legitimate interests lie in the above-mentioned purposes.

Someone, somewhere has screwed up to the extent that data got hacked and is now in the hands of people it was never intended to be. No way, no how does this give me license to then treat that data with any less respect than if it had remained securely stored and I reject outright any assertion to the contrary. That's a fundamental value I operate under

A "breach" is an incident where data is inadvertently exposed in a vulnerable system, usually due to insufficient access controls or security weaknesses in the software.

One mistake that we made when creating the import/export experience for Blogger was relying on one HTTP transaction for an import or an export. HTTP connections become fragile when the size of the data that you're transferring becomes large. Any interruption in that connection voids the action and can lead to incomplete exports or missing data upon import. These are extremely frustrating scenarios for users and, unfortunately, much more prevalent for power users with lots of blog data.

data liberation is best provided through APIs, and data portability is best provided by building code using those APIs to perform cloud-to-cloud migration

The data liberation effort focuses specifically on data that could hinder users from switching to another service or competing product—that is, data that users create in or import into Google products

At Google, our attitude has always been that users should be able to control the data they store in any of our products, and that means that they should be able to get their data out of any product. Period. There should be no additional monetary cost to do so, and perhaps most importantly, the amount of effort required to get the data out should be constant, regardless of the amount of data. Individually downloading a dozen photos is no big inconvenience, but what if a user had to download 5,000 photos, one at a time, to get them out of an application? That could take weeks of their time.

Want to keep your users? Just make it easy for them to leave.

Users are starting to realize, however, that as they store more and more of their personal data in services that are not physically accessible, they run the risk of losing vast swaths of their online legacy if they don't have a means of removing their data.

In addition to strings, Redis supports lists, sets, sorted sets, hashes, bit arrays, and hyperloglogs. Applications can use these more advanced data structures to support a variety of use cases. For example, you can use Redis Sorted Sets to easily implement a game leaderboard that keeps a list of players sorted by their rank.

Data visualization is both an art and a science

“Big Data reveals insights with a particular range of data points, while Thick Data reveals the social context of and connections between data points.”21

Adapting Tricia Wang’s notion of “thick data,”

User subjects and data objects are treated as programmable matter, which is to say extractable matter.

Covid-19 is an emergency on such a huge scale that, if anonymity is managed appropriately, internet giants and social media platforms could play a responsible part in helping to build collective crowd intelligence for social good, rather than profit

Google's move to release location data highlights concerns around privacy. According to Mark Skilton, director of the Artificial Intelligence Innovation Network at Warwick Business School in the UK, Google's decision to use public data "raises a key conflict between the need for mass surveillance to effectively combat the spread of coronavirus and the issues of confidentiality, privacy, and consent concerning any data obtained."

legitimate interest triggers when “processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject

of the six lawful, GDPR-compliant ways companies can get the green light to process individual personal data, consent is the “least preferable.” According to guidelines in Article 29 Working Party from the European Commission, "a controller must always take time to consider whether consent is the appropriate lawful ground for the envisaged processing or whether another ground should be chosen instead." 

“But, if you’re unsure or haven’t mapped out entirely your processing activities,” he said, “it’s impossible to accurately reflect what your users or clients are consenting to when they complete a consent request.”

“It is unfortunate that a lot of companies are blindly asking for consent when they don’t need it because they have either historically obtained the consent to contact a user,” said digital policy consultant Kristina Podnar. “Or better yet, the company has a lawful basis for contact. Lawful basis is always preferable to consent, so I am uncertain why companies are blindly dismissing that path in favor of consent.”

Data has become a “natural resource” for advertising technology. “And, just as with every other precious resource, we all bear responsibility for its consumption,”

They can form a new company that handles all operations within the EU but nowhere else. This subsidiary company can license and segregate European data from the parent company,

To join the Privacy Shield Framework, a U.S.-based organization is required to self-certify to the Department of Commerce and publicly commit to comply with the Framework’s requirements. While joining the Privacy Shield is voluntary, the GDPR goes far beyond it.

This protects you from government overreach, and protects your privacy, and makes identity theft a lot harder.

For example, personal information. Each governmental ministry might have any amount of information on a given voter. Finance knows about your tax, health knows about your medicare claims, justice knows about your criminal record, the RTA the status of your drivers licence. But they don’t know what the OTHER ministries know about you. The data is segregated. Just because one group of people knows about a given part of your life or existence, doesn’t mean that they can get access to everything else. You, by design, do not have one single file that has everything on you. The data is segregated.

GDPR is driving personal data breaches out into the open as companies face tough sanctions for non-disclosure.

None Of Your Business

Users have the right to obtain (in a machine readable format) their personal data for the purpose of transferring it from one controller to another, without being prevented from doing so by the data processor.

Users have the right to access their personal data and information about how their personal data is being processed. If the user requests it, data controllers must provide an overview of the categories of data being processed, a copy of the actual data and details about the processing. The details should include the purpose, how the data was acquired and with whom it was shared.

The Right to access is closely linked to the Right to data portability, but these two rights are not the same.

By choosing Matomo, you are joining an ever growing movement. You’re standing up for something that respects user-privacy, you’re fighting for a safer web and you believe your personal data should remain in your own hands, no one else’s.

Raw data access

Export and migrate your data between hosting options at any time

100% data ownership

With Matomo, the philosophy around data ownership is simple, you own your data, no one else.

People believe in us for that reason, and we will continue to champion the right for people to be in control of their data.

Data privacy now a global movementWe’re pleased to say we’re not the only ones who share this philosophy, web browsing companies like Brave have made it possible so you can browse the internet more privately; and you can use a search engine like DuckDuckGo to search with the freedom you deserve.

our values remain the same – advocating for 100% data ownership, respecting user-privacy, being reliable and encouraging people to stay secure. Complete analytics, that’s 100% yours.

Due to that, you have 100% data ownership as Matomo is hosted on your own servers and we have absolutely no way of gaining access to your data.

when you choose Matomo Cloud, we acknowledge in our Terms that you own all rights, titles, and interest to your users’ data. We obtain no rights from you to your users data. This means we can’t on-sell it to third parties, we can’t claim ownership of it, you can export your data anytime

the privacy of your users is respected

The relationship is between the website owner (you) and the visitor, with no external sources looking in

Own Your Encryption KeysYou would never trust a company to keep a record of your password for use anytime they want. Why would you do that with your encryption keys? With Graphite, you don't have to. You own and manage your keys so only YOU can decrypt your content.

To become compliant, organisations will need to either stop collecting the offending cookies or find a lawful ground to collect and process that data

Legitimate interest. When there is a genuine reason for processing personal data without consent. Interpretations of this legal ground may vary, but a good example would be risk assessment or checking children’s age, such as in an online liquor store.

Asking for consent when processing users’ personal data is one of the most important duties imposed on website owners by the GDPR.

The process of collecting and storing user consent from a technical perspective

it would appear impossible to require a publisher to provide information on and obtain consent for the installation of cookies on his own website also with regard to those installed by “third parties**”

Our solution goes a bit further than this by pointing to the browser options, third-party tools and by linking to the third party providers, who are ultimately responsible for managing the opt-out for their own tracking tools.

You are also not required to manage consent for third-party cookies directly on your site/app as this responsibility falls to the individual third-parties. You are, however, required to at least facilitate the process by linking to the relevant policies of these third-parties.

the publisher would be required to check, from time to time, that what is declared by the third parties corresponds to the purposes they are actually aiming at via their cookies. This is a daunting task because a publisher often has no direct contacts with all the third parties installing cookies via his website, nor does he/she know the logic underlying the respective processing.

When you think about data law and privacy legislations, cookies easily come to mind as they’re directly related to both. This often leads to the common misconception that the Cookie Law (ePrivacy directive) has been repealed by the General Data Protection Regulation (GDPR), which in fact, it has not. Instead, you can instead think of the ePrivacy Directive and GDPR as working together and complementing each other, where, in the case of cookies, the ePrivacy generally takes precedence.

Decision point #2 – Do you send any data to third parties, directly or inadvertently? <img class="alignnone size-full wp-image-10174" src="https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart.png" alt="GDPR cookie consent flowchart" width="1451" height="601" srcset="https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart.png 1451w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-300x124.png 300w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-981x406.png 981w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-761x315.png 761w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-611x253.png 611w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-386x160.png 386w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-283x117.png 283w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-600x249.png 600w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-1024x424.png 1024w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-50x21.png 50w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-250x104.png 250w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-241x100.png 241w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-400x166.png 400w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-350x145.png 350w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-840x348.png 840w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-860x356.png 860w, https://www.jeffalytics.com/wp-content/uploads/7deb832d95678dc21cc23208d76f4144_Flowchart-1030x427.png 1030w" sizes="(max-width: 1451px) 100vw, 1451px" /> Remember, inadvertently transmitting data to third parties can occur through the plugins you use on your website. You don't necessarily have to be doing this proactively. If the answer is “Yes,” then to comply with GDPR, you should use a cookie consent popup.

You must clearly identify each party that may collect, receive, or use end users’ personal data as a consequence of your use of a Google product. You must also provide end users with prominent and easily accessible information about that party’s use of end users’ personal data.

GDPR introduces a list of data subjects’ rights that should be obeyed by both data processors and data collectors. The list includes: Right of access by the data subject (Section 2, Article 15). Right to rectification (Section 3, Art 16). Right to object to processing (Section 4, Art 21). Right to erasure, also known as ‘right to be forgotten’ (Section 3, Art 17). Right to restrict processing (Section 3, Art 18). Right to data portability (Section 3, Art 20).

some examples of legitimate interest (although their main aim is to emphasize what rights, freedoms and so on override legitimate interest)

An example of reliance on legitimate interests includes a computer store, using only the contact information provided by a customer in the context of a sale, serving that customer with direct regular mail marketing of similar product offerings — accompanied by an easy-to-select choice of online opt-out.

This is no different where legitimate interests applies – see the examples below from the DPN. It should also be made clear that individuals have the right to object to processing of personal data on these grounds.

Individuals can object to data processing for legitimate interests (Article 21 of the GDPR) with the controller getting the opportunity to defend themselves, whereas where the controller uses consent, individuals have the right to withdraw that consent and the ‘right to erasure’. The DPN observes that this may be a factor in whether companies rely on legitimate interests.

Legitimate Interest may be used for marketing purposes as long as it has a minimal impact on a data subject’s privacy and it is likely the data subject will not object to the processing or be surprised by it.

15. Data sharing: practices and needs of the transport research community In view of the growing importance of data sharing in transportresearch and based on recommendations of a dedicated expert group on the Transport Research Cloud a new study will establish:1. What are the needs and objections of transports researchers in relation to data sharing:2. What are the training requirementsneeded for the transport research community to facilitate data sharing and3. What potential user communities would expect from a Transport Research Cloud?Type of Action: Provision of technical/scientific services by the Joint Research CentreIndicative timetable: Second quarter of 2020Indicative budget: EUR 0.20 million from the 2020 budget

multiple scandals have highlighted some very shady practices being enabled by consent-less data-mining — making both the risks and the erosion of users’ rights clear

Earlier this year it began asking Europeans for consent to processing their selfies for facial recognition purposes — a highly controversial technology that regulatory intervention in the region had previously blocked. Yet now, as a consequence of Facebook’s confidence in crafting manipulative consent flows, it’s essentially figured out a way to circumvent EU citizens’ fundamental rights — by socially engineering Europeans to override their own best interests.

The deceitful obfuscation of commercial intention certainly runs all the way through the data brokering and ad tech industries that sit behind much of the ‘free’ consumer Internet. Here consumers have plainly been kept in the dark so they cannot see and object to how their personal information is being handed around, sliced and diced, and used to try to manipulate them.

design choices are being selected to be intentionally deceptive. To nudge the user to give up more than they realize. Or to agree to things they probably wouldn’t if they genuinely understood the decisions they were being pushed to make.

For mainly two reasons: I pay for things that bring value to my life, and when something's "free", you're usually really just giving away your privacy without being aware.

sleep Student's Sleep Data

Pulse Pulse Rates and Exercise

HSAUR agefat Total Body Composision Data

Google Recaptcha and personal dataBut we all know: there’s no such thing as a free lunch right? So what is the price we pay for this great feature? Right: it’s personal data.

Consent is one of six lawful grounds for processing data. It may be arguable that anti-spam measures such as reCaptcha can fall under "legitimate interests" (ie you don't need to ask for consent)

A 1% sample of AddThis Data (“Sample Dataset”) is retained for a maximum of 24 months for business continuity purposes.

Not only are public transport datasets useful for benchmarking route planning systems, they are also highly useful for benchmarking geospatial [13, 14] and temporal [15, 16] RDF systems due to the intrinsic geospatial and temporal properties of public transport datasets. While synthetic dataset generators already exist in the geospatial and temporal domain [17, 18], no systems exist yet that focus on realism, and specifically look into the generation of public transport datasets. As such, the main topic that we address in this work, is solving the need for realistic public transport datasets with geospatial and temporal characteristics, so that they can be used to benchmark RDF data management and route planning systems. More specifically, we introduce a mimicking algorithm for generating realistic public transport data, which is the main contribution of this work.

Generating random data

Right now, if you want to know what data Facebook has about you, you don’t have the right to ask them to give you all of the data they have on you, and the right to know what they’ve done with it. You should have that right. You should have the right to know and have access to your data.

Good data privacy practices by companies are good for the world. We wake up every day excited to change the world and keep the internet that we all know and love safe and transparent.

startup focused on creating transparency in data. All that stuff you keep reading about the shenanigans with companies mishandling people's data? That's what we are working on fixing.

 Get a convenient overview of your test results

1947 to 2004

Data Model

Research ethics concerns issues, such as privacy, anonymity, informed consent and the sensitivity of data. Given that social media is part of society’s tendency to liquefy and blur the boundaries between the private and the public, labour/leisure, production/consumption (Fuchs, 2015a: Chapter 8), research ethics in social media research is par-ticularly complex.

One important aspect of critical social media research is the study of not just ideolo-gies of the Internet but also ideologies on the Internet. Critical discourse analysis and ideology critique as research method have only been applied in a limited manner to social media data. Majid KhosraviNik (2013) argues in this context that ‘critical dis-course analysis appears to have shied away from new media research in the bulk of its research’ (p. 292). Critical social media discourse analysis is a critical digital method for the study of how ideologies are expressed on social media in light of society’s power structures and contradictions that form the texts’ contexts.

t has, for example, been common to study contemporary revolutions and protests (such as the 2011 Arab Spring) by collecting large amounts of tweets and analysing them. Such analyses can, however, tell us nothing about the degree to which activists use social and other media in protest communication, what their motivations are to use or not use social media, what their experiences have been, what problems they encounter in such uses and so on. If we only analyse big data, then the one-sided conclusion that con-temporary rebellions are Facebook and Twitter revolutions is often the logical conse-quence (see Aouragh, 2016; Gerbaudo, 2012). Digital methods do not outdate but require traditional methods in order to avoid the pitfall of digital positivism. Traditional socio-logical methods, such as semi-structured interviews, participant observation, surveys, content and critical discourse analysis, focus groups, experiments, creative methods, par-ticipatory action research, statistical analysis of secondary data and so on, have not lost importance. We do not just have to understand what people do on the Internet but also why they do it, what the broader implications are, and how power structures frame and shape online activities

Challenging big data analytics as the mainstream of digital media studies requires us to think about theoretical (ontological), methodological (epistemological) and ethical dimensions of an alternative paradigm

Who communicates what to whom on social media with what effects? It forgets users’ subjectivity, experiences, norms, values and interpre-tations, as well as the embeddedness of the media into society’s power structures and social struggles. We need a paradigm shift from administrative digital positivist big data analytics towards critical social media research. Critical social media research combines critical social media theory, critical digital methods and critical-realist social media research ethics.

de-emphasis of philosophy, theory, critique and qualitative analysis advances what Paul Lazarsfeld (2004 [1941]) termed administrative research, research that is predominantly concerned with how to make technologies and administration more efficient and effective.

Big data analytics’ trouble is that it often does not connect statistical and computational research results to a broader analysis of human meanings, interpretations, experiences, atti-tudes, moral values, ethical dilemmas, uses, contradictions and macro-sociological implica-tions of social media.

Such funding initiatives privilege quantitative, com-putational approaches over qualitative, interpretative ones.

There is a tendency in Internet Studies to engage with theory only on the micro- and middle-range levels that theorize single online phenomena but neglect the larger picture of society as a totality (Rice and Fuller, 2013). Such theories tend to be atomized. They just focus on single phenomena and miss soci-ety’s big picture

Data extraction is a piece of a larger puzzle called data integration (getting the data you want to a single place, from different systems, the way you want it), which people have been working on since the early 1980s.

For n < 5 we recommend showing the individual data points.

Thanks also to this example from the D3 gallery for demonstating how to create sunburst charts.

The main priorities of different ELN features

GIS and Spatial Analytics Market: Global Size

Size of the warehouse management systems (WMS) market worldwide, from 2015 to 2024

Let’s take a look at one more visitor, Arel::Visitors::Dot. The visitor generates the Graphviz’s Dot format and we can use it to create diagrams out of an AST.