Here you’ll find news about bitpuf, tips for using our app, posts about what’s happening in the content-sharing and privacy space, and an occasional wildcard. We hope you’ll check in often.
Here you’ll find news about bitpuf, tips for using our app, posts about what’s happening in the content-sharing and privacy space, and an occasional wildcard. We hope you’ll check in often.
Social networks and email providers retain your shared content and build detailed personal profiles. We know that some things need to be shared differently.
Photos, files, instant messages… How many apps do you use to share your content?
Auto-erasing content keeps it off the record. Why archive it if you don’t need to?
You know it when you see it. Simplicity + ease of use = delight!
…and we’ll never stop looking for ways to make the experience even better.
We’re launching into 2017 with a fresh look. Version 1.3 is now available and it makes bitpuf even simpler and more convenient.
What’s new for 2017? Powerful productivity and effortless exchange!
All Your Content, One View, Always Current
With images and files now displayed together, you present all of your content in a single gallery view.
This makes bitpuf perfect for visual work and projects that involve multiple content types. It’s all right there for you to see. And updates are reflected instantly.
No Account Needed
Viewers don’t need an account—they just tap a link to see your Clip! They can even send you comments.
Better Business with bitpuf
You probably know that bitpuf is great for sharing personal content like photos and videos.
But did you know that businesses and professionals like using bitpuf to exchange confidential documents, contracts, and other sensitive content like invoices, signed forms, tax or financial data?
Instant Delivery, No Digital Footprint
Most electronic exchanges leave digital footprints. In-person exchanges do not.
Using bitpuf, you get the benefits of both: it’s like having a sealed envelope hand-delivered instantly.
|Control version dispersion
There’s nothing more frustrating and less efficient than trying to keep track of shared documents or files. When you are working with a team, bitpuf makes it simple‐-updates are reflected instantly so everyone will always be accessing the latest version.
|Keep content secure
When sharing with other bitpuf users, you maintain tight control over access. To view your content, viewers must login.
You can also share content via a link to make your content accessible without logging in.
It’s your choice.
There’s no need to switch to a messaging app to communicate. You can comment right in the bitpuf app.
Of course, there’s no better way to keep your content secure than to make it go away after it’s reached its recipients.
With bitpuf, you can get very granular and set your expiration time down to the hour.
And once it’s gone, it’s gone.
We don’t archive.
In biological ecosystems, organisms flourish in favorable environments and languish in unfavorable ones. Coral is suited for life in tropical waters not the desert. Different kinds of data also require different conditions to thrive.
As the data-driven economy matures, the forces shaping it are differentiating data (and by extension content) into more refined morphological branches, where particular species occupy the habitats (or market niches) with which they have co-evolved.
Intrinsic to this evolution is the systematic classification of the data being collected, manipulated, analyzed, bought and sold: health data (clinical, genetic, pharmacological), open data, personal data, scientific data, student data, financial data, systems data, metadata, audit data, business-critical data, sensor data, polling data.
In spite of this rich lexicon, too often we refer to data in generalized terms, as a vaguely homogeneous mass. This is a mistake.
Data is anything but uniform.
Derived from a variety of sources, used in innumerable applications, data requires disparate protection and maintenance routines to maximize its utility, protect its integrity, and honor its value.
Recent polls demonstrate that the non-expert public also recognizes differences among data types in the digital biome, choosing, for example, to avoid interactions online that require disclosing personal information.
This is not the same, however, as fully grasping the logical next step.
Data that is not uniform—in terms of format, lifespan, value, vulnerability, etc.—should not be treated uniformly.
This is especially true where sensitive, private, personal data is concerned.
Just as different species inhabit different ecosystem niches suited to their particular physical and behavioral traits, different data types will thrive or vitiate under different conditions.
Data itself takes multiple forms: words, numbers, pixels, coded content organized in a table or grid. Some data is highly complex; some is simple. It’s critical to be aware of all facets of a given body of data and to understand what constitutes favorable or unfavorable conditions.
This requires unraveling data attributes and evaluating them.
Consider, for example, a digital image whose geo-location is embedded in its metadata. Though seemingly innocuous, when digital images are compiled and overlaid on a map, they can reveal more than you might think. Publically available images posted on social media have disclosed the precise addresses of pet owners and helped track down criminals.
When delivery to a recipient is all that’s needed or when time-sensitive data expires, archiving it doesn’t make sense. The distinction between permanent and impermanent content is of paramount importance given the volume of data we generate. Storing it might be cheap (in terms of dollars if not environmental impact), but managing and securing it all is not. Data that does need to be retained faces the challenges of digital preservation (such as long-term readability and bit rot).
Incompatible files, “not supported on this device,” are frustrating. Some file types are so specialized that the data they contain is accessible only to those with an exclusive key. Computational biologists, for example, need proprietary bioinformatics tools to visualize in 3-D the interactions of drugs and their genetic targets.
Source and access
As with the shift from Linnaean classification to Phylogenetic nomenclature, our classification of data types will be fluid, adapting to outside forces of science, business, and culture. General categories today outline both the origins of and access to different types of data, including open data, restricted data (e.g., data subject to government regulations like COPPA, HIPAA, and Privacy Shield), proprietary data, and personal/sensitive/confidential/private data (e.g., PII, ePHI, genetic data, student data).
Data itself is but one element of the information ecosystem. The expertise needed to do something useful with it embodies one of the forces driving the co-evolution of data and its market, prompting the wild growth of analytics and data visualization, influencing our behavior online, shifting the fulcrum of the adtech-adblocking seesaw, and tightening our focus on data protection.
Consider for example how these factors interact within the information ecosystem:
To more fully understand the next life stage of this evolution, we need a taxonomic language and generally accepted classification criteria.
Big data is patently imprecise. “Big” describes a certain volume, but it implies nothing about wide-ranging sources and uses.
Small data is an even more egregious misnomer: according to most definitions, there are vast quantities of it, yet there is no consensus on what it is.
If we imagine Data electronicum as the order, below this might be the families of big data and small data, which can themselves be divided into personal data and non-personal data, which in turn include myriad species each with numerous facets that define them.
Mapping out data types by classifying them might be construed merely as an exercise in content management. One might argue that nomenclature is nothing more than an abstraction. So why does data differentiation matter?
It matters because we need to know what we are fishing for. Knowing what we are after affects the tools we use, the areas of the ocean we trawl, the season and time of day we cast our nets.
Imagine concentric rings expanding outward from the singular point of our identities.
Data furthest from us might be historical data or data over which we have little or no control like roadway images or government records.
Closer in are things like health information and records of financial transactions, student records and HR files: these are held by fewer institutions but still beyond our reach.
Closest are those things that we can or might wish to control like personal photos, email, and text messages.
All of this data is nominally “ours.” It is, after all, about us. And it is often generated by us. But much of it is collected, shared, or stored unnecessarily, without our consent, or without a fair exchange.
Have you ever wondered why a weather app needs to check your location every 10 minutes? Or whether a photo-sharing app really needs access to the physical addresses, birthdays, and other notes recorded in your digital rolodex?
All of the bycatch in data collectors’ nets crowds out legitimate uses, exposes latent data to misuse, and expends resources unnecessarily.
Defining data with greater precision by citing attributes relevant to a specific use will help us control more and waste less.
Issues of controlling and protecting data and using it efficiently pivot on the value we assign to it. When we make decisions about collecting, retaining, and securing data, we must first appraise it and consider its utility, usability, ROI.
Some correlations are completely spurious. A lot of data is unstructured and difficult to decipher or inaccessible because of regulatory restrictions. And in some cases, its shelf life is too short to bother with.
Sometimes what we catch isn’t worth the bait.
You won’t find a tropical plant in the Arctic. Fish belong in water.
A retail coupon serves no purpose once it has expired. Genetic data doesn’t belong in the digital vault of an online bank.
We need to stop treating data as uniform and develop and implement tools and policies that allow us to act on distinctions appropriately by looking at all of the characteristics that define a given type of data.
Differentiating data can be a win-win: fewer resources, greater security, better ROI.
Image: junko | Pixabay
A picture might be worth a thousand words, but a thousand pictures are worth little if we retain them because of inertia, indecision, or failure to filter.
Digital imaging has vastly simplified photography but complicated the processing of its prolific output.
As pixel resolution increases, our resolution to select, manage, and preserve our image collections weakens. The result: an inverse relationship between the volume of digital images we create and our ability to control them.
Who enjoys sorting through the 60 or 100 photos taken over a weekend, culling out the duplicates, the blurry ones, the backlit and poorly composed, selecting only those worth keeping? Who among us performs this chore routinely?
Dead wood in the tree of knowledge
If digital data were a living thing, it would constitute the roots of information-economy flora. Although nothing can grow without these roots, they alone will not generate a tree of knowledge, let alone a blossom. Often they create an impenetrable tangle.
Big data, small data, the Internet of Things (IoT), the thousands of digital images that we amass every year…much of it is dead wood and should be pruned judiciously.
Although we recognize that excessive, indiscriminate collecting gives rise to all kinds of dysfunction, we don’t wield the shears to cut it down to size.
Data economics don’t make sense
The deleterious effects of data hoarding and information overload are widespread and longstanding. Futurist Alvin Toffler wrote about these in 1970, well before the first digital camera appeared on the market in 1991.
As these phenomena progressed, the terms describing them evolved as well—information glut, data glut, data smog, digital noise—and gave rise to new terms for related issues—filter failure, time famine, information fatigue syndrome, and data exhaust.
Note the numbers
First, consider the rate at which data flow and connectivity will increase; it is staggering.
By the way, 1,000 GB ≈ 1 TB (Terabyte); 1,000 TB ≈ 1 PB (Petabyte); 1,000 PB ≈ 1 EB (Exabyte); 1,000 EB ≈ ZB (Zettabyte)
Personal data represents a remarkable proportion of these totals (and companies are taking notice, collecting personal data and combining it with big data from other sources in order to improve analytics and by extension the personalized offers presented to consumers).
The digital-image share of this personal data is also astounding: an estimated 1 trillion photos captured in 2015.
Next, consider the costs of storage.
One storage vendor notes: “No one can look at all their data anymore; they need algorithms just to decide what to look at.” Indeed only 0.5% of data gathered is even analyzed. If it’s good data, it might reveal something useful; if it’s bad data, it can be misleading.
Obviously, it all comes down to making choices, evaluating what we capture, collect, and store, controlling the impulse to hold on to it all, just in case.
The logic of selecting and deleting
If we address the behavior that drives data overload, we can nip it in the bud rather than pruning the full-grown results.
Every time we snap a photo, post it, share it, or send it to the cloud, we need to ask: Do I really need to save this? Every digital artifact we create should either be destined for deletion or properly prepared for preservation.
History is constructed from artifacts that survive. Physical preservation is one factor in their survival. Another is the very act of selection.
Shakespeare famously left behind little for posterity to examine. Many visual artists destroy their own work (e.g., Monet and Picasso). Deletion is a highly effective strategy for protecting one’s reputation and legacy.
Implicit in this tradition is the acknowledgement that
So what of the impulse today to chronicle every inane element of our lives? What compels this micro-documentation?
These are questions for sociologists, anthropologists, and psychologists, but the behavior itself concerns technologists, data scientists, and security experts. (Because it isn’t just photos. Sensitive content of all kinds is left to dangle indefinitely in cyberspace at significant risk.)
Some materials do acquire value over time. The personal correspondence of literary greats and other famous people satisfy our nostalgia, voyeurism, and celebrity worship, and they provide a sightline into the creative lives of artistic genius.
The fact is, in the digital age, the issue of volume is more acute.
Taking a photo used to be a deliberate act; it required taking notice of the angle of the sun, ensuring proper focus, framing the composition, waiting for Cartier-Bresson’s “decisive moment.”
Now we think nothing of taking 20 photos to get a single winner. Unfortunately, we rarely look at the other 19.
When we postpone the acts of filtering and eliminating (telling ourselves that we’ll do it later), the volume of data we generate quickly becomes overwhelming! (Concierge photo organizers will do this for those who can justify the expense. There’s also software for automatic album creation.)
At least as important as the issue of quantity is the question of quality, or more precisely, value.
“Self-showing…can be…a sort of charming ritual of daily inventory,” writes cultural critic Adam Gopnick.
An occasional dose of charm is understandably appealing. But rituals exist in defined time and space, not on a continuum. Once performed, a ritual’s purpose is exhausted. So why preserve it?
This is not a criticism of the impulse to capture memorable moments, but a consideration of the confounding consequences:
To say nothing of what relying on digital records does to the physiological construction of our personal histories.
What kind of emotional imprint can we create in our minds when we experience things through the lens of a smartphone screen? Our memories are so much richer when encoded through the input of all five senses (smelling the salt air, hearing laughter, feeling the warmth of the sun).
Neverlasting is natural
A very short-lived species of mayfly takes its name from the Greek word ephemera, meaning “lasting one day.” In their abbreviated life span, these insects serve their purpose and then expire.
We might do well to take notice of this cycle as we consider the volume and value of the data we generate, consume, and store.
Let’s do ourselves a favor by sharing in the moment, relieving ourselves of the “selection” burden, and letting go of the impulse to save every digital communication we create.
Differentiate content. Favor quality over quantity. Define value. Eliminate dead wood.
You can start by using bitpuf. It’s designed for sharing impermanent content.
Image: hotblack | morgueFile
We’ve all heard the refrain about poor data: garbage in, garbage out. A less well-recognized issue concerns data that is collected and stored but not used.
Many companies draw on only a fraction of the data they posses and often fail to derive anything useful from it. The explosion in data analytics will help redress this gap, enabling organizations to identify patterns, make predictions, and personalize products and services. The advanced analytics market is projected to grow to nearly $30B by 2019.
But data analytics rely on seeing the data that is being analyzed and some shades of big data are difficult to discern. Most organizations retain vast quantities of this darker stuff. Some estimate that as much as 90% of big data is so-called “dark data.” Though not always shady, it is not always a valuable resource either.
Hidden in the cloud or dark matter of cyberspace, either way the dark data you harbor can be an unseen force—for better or worse.
What is Dark Data and Why Does It Matter?
Dark data refers to data that is collected and stored, then neglected. It may include data of minimal value or great potential.
Email is a prime example. Though often archived as a matter of policy, it is unlikely to be cataloged in a content-management system. Because there are privacy laws specific to email, knowing where it resides and what it contains is paramount.
Undetected dark data might also include personal files, like music and video that employees store on company machines, or worse on unsanctioned cloud apps on third-party servers. The storage costs accumulate quickly.
According to a study of companies in the UK, “A typical midsize company with 500 terabytes of data wastes nearly a million pounds [$1.5 million] each year maintaining trivial files, including … personal photos stored by 57 percent of employees, personal ID and legal documents by 53 percent, as well as music, games and videos, stored by 45 percent, 43 percent and 29 percent respectively.”
There is a treasure trove of information locked up in libraries, museums, and research collections: e.g., objects, photographs, even metadata in card catalogs. These are unequivocally worth preserving in digital form, contributing as they do to innovation and scholarship.
Got ROT? Deal with Your Databerg in Four Steps
Whether perceived as a business risk or potential asset, caring for this all of this data is a Herculean task.
“Databergs” threaten to rip a hole in information systems. ROT alone is projected to cost organizations $891B by 2020 in storage, migration, and security.
The intangible costs of data protection are equally significant. Trust is considered the “cornerstone of the digital economy,” yet the reputational and financial risks of data breaches are too often recognized after a hacking incident not before.
Minimizing these risks is essential. How?
Though no one wants to talk about it, most data breaches are the result of accidental or deliberate unauthorized access by employees. What to do? Training in data ethics and implementing and executing clear information governance policies.
Data is delicate with a relatively short shelf-life: it must be periodically accessed and migrated to ensure its integrity.
Storage media can be unstable and prone to corruption or defect, but they must be readable in the future. File formats, especially proprietary formats, quickly become outdated, as the applications needed to view them become incompatible with current operating systems and devices.
One person’s ROT might be another’s loot and it should be periodically purged. (Obsolescence and triviality make a strong case for temporary content–neverlasting as we like to call it!)
Notwithstanding the costs and risks of keeping data that holds no value, determining what to retain also has legal and cultural implications.
Cybersecurity today must protect not only the data itself, but the data used to authenticate access to it (biometrics both physical and behavioral hold promise in some applications but can also be stolen for nefarious use).
Dark Data Checklist
In the simplest terms, any approach to caring for dark data will involve:
And this will mean addressing some rotten habits:
Keeping Private Data in the Dark
With nearly every move we make online generating a steady stream of digital bits, dark data touches all of us.
And we can support the use of personal data to customize an offer when it benefits all parties involved.
But we must insist that possessing and using sensitive data conveys a big responsibility. To help ensure that it is well protected and treated ethically, organizations should focus on obtaining transparent consent, collecting only what is needed, selecting what’s valuable, and eliminating the rest.
If you believe privacy matters…
Image source: Pixabay
Human history is punctuated with examples of new science and technologies gaining powerful momentum before society considered the repercussions of their applications and established guidelines for their uses.
American drivers were bumping along in Model T Fords for several years before they were required to obtain licenses and moviegoers had been buying tickets for decades when motion picture and television rating systems were introduced.
Our uniquely human drive to discover, invent, and improve is a wondrous thing, but we can get ahead of ourselves by adopting advances before considering the potential for undesirable consequences or taking measures to avoid them (Nobel laureate Alexander Fleming, who discovered penicillin, predicted antibiotic resistance as a result of misuse but his warnings went unheeded for generations).
How did personal computing become personalized ads?
Progress empowers; it enables and enriches. It also introduces new challenges as we see now with the rise of big data and the “personal information economy.” Our ability to capture and crunch data has leapfrogged ahead of a framework to guide its responsible use.
Early triumphs of the digital age arose from computing power—the ability to grind through calculations at an unprecedented rate. The advent of personal computing saw word processing replace the typewriter and the introduction of desktop publishing.
Then came the Internet and email, web search and browsing, e-commerce, and eventually social networks. Each of these developments contributed to the next one and each incrementally encroached upon our online privacy.
Today data, much of it personally identifiable information (PII), drives a significant portion of the global economy and contributes inestimably to our daily activities and interactions.
Retail transactions, traffic apps, fitness trackers, private communications, even media consumption involve surrendering various fragments of data that can easily be combined to create rich profiles and to identify and locate users with great specificity.
We cede this personal data in exchange for convenience, or so the argument goes. Yet in the absence of a universal, or at least widely adopted, ethical framework to guide the responsible use of data, we expose ourselves to questionable manipulation and outright abuse. It’s very difficult to know where to draw the line.
To move forward, we must first step back
Perhaps it will become clearer if we step back and take the long view. It’s fair to say that we are collectively realizing the need to reexamine the very concept of privacy, to redefine it in light of changes wrought by information technology, just as we had to redefine labor in the industrial age to address child welfare, public health, and urbanization.
The modern factory became emblematic of the industrial age, embodying both its promise and peril. The Internet represents the multifarious face of today’s technology: globalization, speed, connectivity, convenience, and scale, but also unintended exposure, inconsistent regulations, and every imaginable scam.
Automation, as a driver of the industrial age, transformed both manufacturing and labor. Initially, in a rush to reap its benefits, we failed to account for the human factor and treated workers as machines.
Debating ethical use, responsibility, and regulations
We find ourselves at a similar junction today as we debate how to use data responsibly. Having rushed headlong into our current state, we must now retreat and reconsider the physical and tacit boundaries that once demarcated private spaces.
Fierce competition among data brokers and the potential for anti-trust actions against those with the most valuable troves indicate just how high the stakes have become.
So what next?
We all hold the reins
Having acknowledged that left unbridled our digital world is becoming increasingly vulnerable (data breaches and the hacking of Wi-Fi enabled toys starkly illustrate its darker side), we can direct our forward momentum toward an acknowledgement that regulation is needed.
It’s not an all-or-nothing issue. We’ve traveled too far down the path of progress to roll back the conveniences we’ve come to enjoy.
So let’s balance economic benefits with individual rights by agreeing to basic ground rules: broadly speaking in the form of data ethics, and more narrowly in the form of specific implementations, e.g., architectures, privacy policies, and business models.
It seems neither practical nor desirable to eliminate completely the capture and use of personal data. Our expectations and habits have changed. But it is entirely within our power to demand and create a code of ethics, to pull back on the reins a bit and return things to a workable order.
As we look ahead to the coming year, our eyes are inevitably drawn to the digital landscape and the billions of personal data points that map its contours.
Nearly every what-to-watch-in-2016 list refers to data privacy. And nearly every one points to a significant shift in the balance of control over personal data: tipping away from AdTech and toward consumers.
To relinquish or control, that is the question
People are bristling at the unbridled collection and use of data about their behavior online, their every move through physical space, and literally thousands of facets of their “persona” (up to 4,000 data points on a single user—one journalist asks whether he could come up with that many data points on his spouse!).
And we consumers are footing the bill: the frenetic pop-ups and “vexing videos” that plague our mobile screens have voracious appetites for bandwidth, sometimes consuming more than the content itself.
Yet consumer opinion remains divided, largely along generational and cultural lines, about the risks and benefits of permitting data collection.
Some, especially “digital natives,” are accustomed to letting their private lives spill out in full view of the online public. (Though cybersecurity specialists predict that Millennials will take a closer look at privacy.) Many others shrink from the spotlight, wondering what really lies behind the glow.
Of course, there is no immutable law of information technology declaring that we must relinquish our personal data and privacy in order to participate as digital citizens. We can demand control.
Blocking, faking, refusing
Has data-driven personalization reached its limit? It certainly has met its match in ad-blocking technology and consumers’ evasive strategies.
Big data is bittersweet
Big data has many worthwhile and legitimate uses but the anonymization of personal data is notoriously difficult and the data collected often far exceeds what is needed for a given service or transaction, for example:
Forks in the road: what can we do?
We can choose more palatable paths through the digital world. Consider these 5 alternatives:
All of these options implicitly treat personal data as a monetizeable asset. Given that we are the source of this in-demand resource, shouldn’t we exercise our right to determine its value and the conditions of its exchange?
Shouldn’t we demand more than the simple convenience that data controllers point to as the current trade-off? (An Annenberg School for Communication survey reveals that most Americans don’t buy this “tradeoff fallacy” anyway.)
More bandits, more breaches
As we explore these options, cybercriminals will continue to test our systems’ vulnerabilities relentlessly and will penetrate inadequate defenses. The incidence of data breaches continues to increase (780 in the U.S. in 2015), as does the sophistication of the attacks. Those seeking unauthorized access to personal data are devising increasingly subtle ploys. Social-engineering fraud preys on our gullibility and turns our socially-shared information against us.
The profusion of connected devices spawned by the Internet of Things (IoT) will expose still more of our data to additional “controllers” and attacks. The Gartner Group estimates that the number of connected things will reach 25 billion by 2020.
And the range of entities seeking to use information about our behavior and demographic data keeps expanding: note the granularity of voter profiling in the current U.S. presidential race. Psycho-graphic, behavioral microtargeting is providing candidates’ campaigns with detailed information gleaned from voters’ “Like” patterns on social media.
As with any data stored in the cloud, these records can be leaked. A researcher was able to access 191 million voting records from one database a few weeks ago and an additional 56 million records from another.
New rules of the road
We can all expect to be rated on our data-ethics performance and our reliability vis-à-vis privacy and security. Driven by both consumer pressure and the risks of cybercrime, businesses will continue to adapt by creating new roles (chief privacy officer), adopting new regulations, developing new privacy-enhancing technologies (so-called PETs), and implementing new policies and training, all addressing data security and data ethics. The economic and reputational risks of failing to do so could be crippling.
So who says privacy is dead? 93% of Americans feel that it is important to control who can get information about them and 90% feel it’s important to control what information is collected. Those numbers unequivocally refute any claim to privacy’s demise. To ignore them is akin to junk food marketers asserting that healthy eating is dead.
Privacy will be dead when we digital citizens give it up. Nothing indicates that moment is near.
Read additional perspectives on what to expect in the privacy space in 2016:
Photo credit: Russell Johnson
Message in a bottle
Journalist John Markoff recently reported on a potential breakthrough in storage technology that could make it possible to store all the world’s data on synthetic DNA. It would fit in 12 wine bottles.
The Library of Congress holds more than 160 million items in 470 languages stored on approximately 838 miles of bookshelves: works of literature, scientific data, presidential papers, sheet music, rare manuscripts and maps…there are so many things worth preserving and archiving.
But there are even more that are not: grocery lists, casual emails and text messages, social media posts, telephone conversations, memos, homework assignments, doodles…Think about what it takes to store all the content produced by a single person in one year!
Digital is different
While we must file away important documents in a safe place—a signed original, for example—we do not want multiple digital copies stored indefinitely elsewhere. Yet that is precisely what happens when we share content using email and many file-sharing services.
Often, we cannot take the steps we’d like to protect sensitive information: deleting a file after it’s delivered digitally isn’t always the same as shredding its physical equivalent. In many cases, once we’ve sent it, its fate is out of our control.
And then there’s all of the not-worth-saving stuff that clutters our digital lives.
We’ve become digital hoarders
In transitioning to the digital world, we have failed to apply the same selectivity that drives our behavior in sorting through our physical materials. When was the last time you culled outdated files from your computer or old messages from your inbox? If we were to retain every piece of paper that passes through our lives, we’d be buried in it.
Here are 5 distinctly un-storage-worthy kinds of digital content.
1. Every photo ever taken
Today’s mobile phones produce fantastic, high-quality images and it’s very tempting to tap the screen. So much easier than working with manual focus cameras, cellulose film, the developing process, and leather-bound albums.
There’s a powerful impulse to capture a scene, a moment, a memorable event, to create a visual reminder, to save ourselves the time and effort of writing something down. Few of us enjoy the task of selecting, deleting, transferring, and uploading these digital images. But just because we can keep all of this stuff, doesn’t mean we should.
2. Casual communications
R u home yet? We need more milk. Are we still on for 1?
Once uttered, these exchanges lose all of their value. Digital advertisers might want to know that you have run out of milk or where you are at 1:00. But what further value do the messages bring you?
3. Time-sensitive content
A coupon expires after a certain date, a reminder is pointless after the fact, an invitation no longer needed following an event. Keeping these around wastes energy and space.
4. Confidential material
The convenience of electronic delivery is one of the great universal upsides of information technology. Just don’t forget the downsides: data breaches, identity fraud, lack of privacy control. When you email a copy of your 1099 to your accountant, or SMS a password to your spouse, you usually lose the ability to “shred” these digitally.
5. Private information
Who hasn’t expressed a private thought in an email to a friend? Maybe we’ve disclosed things that we’d prefer to be forgotten. The spoken word is ephemeral and more easily left behind. Our digital trifles follow us around.
We need to be more discerning with our digital content, to distinguish what we share by its intended lifespan and its vulnerability once it leaves our fingertips.
For neverlasting content, there’s always bitpuf.
Photo credit: dolphfyn / Fotolia
Are you capturing the value of bitpuf in your professional work?
bitpuf offers an easy-to-use, secure platform for sharing content, from images and videos to confidential documents.
Attorneys, accountants, investment advisors, doctors, engineers, realtors, and designers exchange files with clients, patients, and colleagues every day. Often these documents contain sensitive information (e.g., tax, financial, or medical data, business IP, contracts). How do you ensure that they remain secure? How much time do you spend managing the whole exchange?
We’ve highlighted below some of the business benefits of the bitpuf platform. Have a look and discover for yourself its simplicity, security, convenience, and control.
Secure and Private
Easy to Use
For more information, contact us at email@example.com.
Photo credit: Sergey Nivens / Fotolia
We’ve just launched version 1.2 and we think you’ll love the improvements!
Here’s what’s new:
Do you frequently share business-critical files or confidential documents (tax, financial, legal, proprietary)? bitpuf offers a simple, completely secure channel for exchanging documents in many professional contexts.
Stay tuned for more exciting features coming soon!