“Clocks slay time… time is dead as long as it is being clicked off by little wheels; only when the clock stops does time come to life.”
The melting of digital fences between enterprises and business environments is putting a new light on the way time has to be taken into account.
The shift can be illustrated by the EU GDPR: by introducing legal constraints on the notifications of changes in personal data, regulators put systems’ internal events on the same standing as external ones and make all time-scales equal whatever their nature.
Ontological Limit of WC3 Time Recommendation
The W3C recommendation for OWL time description is built on the well accepted understanding of temporal entity, duration, and position:
While there isn’t much to argue with what is suggested, the puzzle comes from what is missing, namely the modalities of time: the recommendation makes use of calendars and time-stamps but ignores what is behind, i.e time ontological dimensions.
Out of the Box
As already expounded (Ontologies & Enterprise Architecture) ontologies are at their best when a distinction can be maintained between representation and semantics. That point can be illustrated here by adding an ontological dimension to the W3C description of time:
Ontological modalities are introduced by identifying (#) temporal positions with regard to a time-frame.
Time-frames are open-ended temporal entities identified (#) by events.
It must be noted that initial truth-preserving properties still apply across ontological modalities.
Conclusion: OWL Descriptions Should Not Be Confused With Ontologies
Languages are meant to combine two primary purposes: communication and symbolic representation, some (e.g natural, programming) being focused on the former, other (e.g formal, specific) on the latter.
The distinction is somewhat blurred with languages like OWL (Web Ontology Language) due to the versatility and plasticity of semantic networks.
That apparent proficiency may induce some confusion between languages and ontologies, the former dealing with the encoding of time representations, the latter with time modalities.
Contrary to security breaks and information robberies that can be kept from public eyes, crashes of business applications or internet access are painfully plain for whoever is concerned, which means everybody. And as illustrated by the last episode of massive distributed denial of service (DDoS), they often come as confirmation of hazards long calling for attention.
Things Don’t Think
To be clear, orchestrated attacks through hijacked (if unaware) computers have been a primary concern for internet security firms for quite some time, bringing about comprehensive and continuous reinforcement of software shields consolidated by systematic updates.
But while the right governing hand was struggling to make a safer net, the other hand thoughtlessly brought in connected objects to a supposedly new brand of internet. As if adding things with software brains cut to the bone could have made networks smarter.
And that’s the catch because the internet of things (IoT) is all about making room for dumb ancillary objects; unfortunately, idiots may have their use for literary puppeteers with canny agendas.
Think Again, or Not …
For old-timers with some memory of fingering through library cardboard, googling topics may have looked like dreams: knowledge at one’s fingertips, immediately and comprehensively. But that vision has never been more than a fleeting glimpse in a symbolic world; in actuality, even at its semantic best, the web was to remain a trove of information to be sifted by knowledge workers safely seated in their gated symbolic world. Crooks of course could sneak in as knowledge workers, armed with fountain pens, but without guns covered by the second amendment.
So, from its inception, the IoT has been a paradoxical endeavor: trying to merge actual and symbolic realms that would bypass thinking processes and obliterate any distinction. For sure, that conundrum was supposed to be dealt with by artificial intelligence (AI), with neural networks and deep learning weaving semantic threads between human minds and networks brains.
Not surprisingly, brainy hackers have caught sight of that new wealth of chinks in internet armour and swiftly added brute force to their paraphernalia.
But in addition to the technical aspect of internet security, the recent Dyn DDoS attack puts the light on its social perspective.
Things Behavior & Social Responsibility
As far as it remained intrinsically symbolic, the internet has been able to carry on with its utopian principles despite bumpy business environments. But things have drastically changed the situation, with tectonic frictions between symbolic and real plates wreaking havoc with any kind of smooth transition to internet.X, whatever x may be.
Yet, as the diagnose is clear, so should be the remedy.
To begin with, the internet was never meant to become the central nervous system of human societies. That it has happened in half a generation has defied imagination and, as a corollary, sapped the validity of traditional paradigms.
As things happen, the epicenter of the paradigms collision can be clearly identified: whereas the internet is built from systems, architectures taxonomies are purely technical and ignore what should be the primary factor, namely what kind of social role a system could fulfil. That may have been irrelevant for communication networks, but is obviously critical for social ones.
The world is the totality of facts, not of things.
As the so-called internet of things (IoT) seems to bring together people, systems and devices, the meaning of real-time activities may have to be reconsidered.
Things, Facts, Events
To begin with, as illustrated by marketed solutions like SIGFOX, the IoT can be described as a fast and stripped-down communication layer carrying not so much things than facts and associated raw (i.e non symbolic) events. That seems to cut across traditional understandings because the IoT is dedicated to non symbolic devices yet may include symbolic systems, and fast communication may or may not mean real-time. So, when applications network requirements are to be considered, the focus should be on the way events are meant to be registered and processed.
Business Environments Cannot be Frozen
Given that time-frames are set according primary events, real-time activities can be defined as exclusive ongoing events: their start initiates a proprietary time-frame perceived from the outside as being without duration, i.e as if nothing could happen until their completion, with activities targeting the same domain supposed to be frozen.
That principle can be understood as a generalization of the ACID (Atomicity, Consistency, Isolation, Durability) scheme used to guarantee that database transactions are processed reliably. Along that understanding a real-time business transaction would require that, whatever its actual duration, no change from other transactions would be accepted to its domain representation until the business transaction is completed and its associated outcomes duly committed. Yet, the hitch is that, contrary to systems transactions, there is no way to freeze actual business ones which will continue to be carried out notwithstanding suspended registrations.
In that case the problem is not so much one of locks on DB as one of dynamic alignment of managed representations with the changing state of affairs in their actual counterpart.
Yoking Systems & Environments
As Einstein famously said, “the only reason for time is so that everything doesn’t happen at once”. Along that reasoning coupling constraints for systems can be analyzed with regard to the way events are notified and registered:
Input flows: what happens between changes in environment (aka facts) and their recording by applications (a).
Processing: could the application be executed fully based on locally available information, or be contingent on some information managed by systems at domain level (b).
Output flows: what happens between actions triggered by applications and the corresponding changes in the environment (c).
It’s important to remind that real-time activities are not defined in absolute time units: they can be measured in microsecond as well as in aeons, and carried out by light sensors or by snails.
A Simple Decision Routine
Deciding on real-time requirements can therefore follow a straightforward routine:
Should changes in relevant external objects, processes, or expectations, be instantly detected at system’s boundaries ? (a)
Could the interpretation and processing of associated events be carried out locally, or be contingent on information shared at domain level ? (b)
Should subsequent actions on relevant external objects, processes, or expectations be carried out instantly ? (c)
Positive answers to the three questions entail real-time requirements, as will also be the case if access to shared information is necessary.
What about IoT ?
Strictly speaking, the internet of things is characterized by networked connections between non symbolic things. As it entails asynchronous communication and some symbolic mediation in between, one may assume that the IoT cannot support real-time activities. That assumption can be checked with some business cases given as examples.
The world is the totality of facts, not of things.
At its inception, the young internet was all about sharing knowledge. Then, business concerns came to the web and the focus was downgraded to information. Now, exponential growth turns a surfeit of information into meaningless data, with the looming risk of web contents being once again downgraded. And the danger is compounded by the inroads of physical objects bidding for full netizenship and equal rights in the so-called “internet of things”.
As it happens, that double perspective coincides with two basic search mechanisms, one looking for identified items and the other for information contents. While semantic web approaches are meant to deal with the latter, it may be necessary to take one step further and to bring the problem (a web of things and meanings) and the solutions (search strategies) within an integrated perspective.
Down with the System Aristocrats
The so-called “internet second revolution” can be summarized as the end of privileged netizenship: down with the aristocracy of systems with their absolute lid on internet residency, within the new web everything should be entitled to have a voice.
But then, events are moving fast, suggesting behaviors unbecoming to the things that used to be. Hence the need of a reasoned classification of netizens based on their identification and communication capabilities:
Humans have inherent identities and can exchange symbolic and non symbolic data.
Systems don’t have inherent identities and can only exchange symbolic data.
Devices don’t have inherent identities and can only exchange non symbolic data.
Animals have inherent identities and can only exchange non symbolic data.
Along that perspective, speaking about the “internet of things” can be misleading because the primary transformation goes the other way: many systems initially embedded within appliances (e.g cell phones) have made their coming out by adding symbolic user interfaces, mutating from devices into fully fledged systems.
Physical Integration: The Meaning of Things
With embedded systems colonizing every nook and cranny of the world, the supposedly innate hierarchical governance of systems over objects is challenged as the latter calls for full internet citizenship. Those new requirements can be expressed in terms of architecture capabilities :
Anywhere (Where): objects must be localized independently of systems. That’s customary for physical objects (e.g Geo-localization), but may be more challenging for digital ones on they way across the net.
Anytime (When): behaviors must be synchronized over asynchronous communication channels. Existing mechanism used for actual processes (e.g Network Time protocol) may have to be set against modal logic if it is used for their representation.
Anybody (Who): while business systems don’t like anonymity and rely on their interfaces to secure access, things of the internet are to be identified whatever their interface (e.g RFID).
Anything (What): objects must be managed independently of their nature, symbolic or otherwise (e.g 3D printed objects).
Anyhow (How): contrary to business systems, processes don’t have to follow predefined scripts and versatility and non determinism are the rules of the game.
Taking a sortie in a restaurant for example: the actual event is associated to a reservation, car(s) and phone(s) are active objects geo-localized at a fixed place and possibly linked to diners, great wines can be authenticated directly by smartphone applications, phones are used for conversations and pictures, possibly for adding to reviews, friends in the neighborhood can be automatically informed of the sortie and invited to join.
As this simple example illustrates, the internet of things brings together dumb objects, smart systems, and knowledgeable documents. Navigating such a tangle will require more than the Semantic Web initiative because its purpose points in the opposite direction, back to the origin of the internet, namely how to extract knowledge from data and information.
Moreover, while most of those “things” fall under the governance of the traditional internet of systems, the primary factor of change comes from the exponential growth of smart physical things with systems of their own. When those systems are “embedded”, the representations they use are encapsulated and cannot be accessed directly as symbolic ones. In other words those agents are governed by hidden agendas inaccessible to search engines. That problem is illustrated a contrario (things are not services) by services oriented architectures whose one of primary responsibility is to support services discovery.
Semantic Integration: The Actuality of Meanings
The internet of things is supposed to provide a unified perspective on physical objects and symbolic representations, with the former taken as they come and instantly donned in some symbolic skin, and the latter boiled down to their documentary avatars (as Marshall McLuhan famously said, “the medium is the message”). Unfortunately, this goal is also a challenge because if physical objects can be uniformly enlisted across the web, that’s not the case for symbolic surrogates which are specific to social entities and managed by their respective systems accordingly.
With the Internet of Systems, social entities with common endeavors agree on shared symbolic representations and exchange the corresponding surrogates as managed by their systems. The Internet of Things for its part is meant to put an additional layer of meanings supposedly independent of those managed at systems level. As far as meanings are concerned, the latter is flat, the former is hierarchized.
That goal raises two questions: (1) what belongs to the part governed by the internet of things and, (2) how is its flattened governance to be related to the structured one of the internet of systems.
A World of Phenomena
Contrary to what its name may suggest, the internet of things deals less with objects than with phenomena, the reason being that things must manifest themselves, or their existence be detected, before being identified, if and when it’s possible.
Things first appear on radar when some binary footprint can be associated to a signalling event. Then, if things are to go further, some information has to be extracted from captured data:
Coded data could be recognized by a system as an identification tag pointing to recorded known features and meanings, e.g a bar code on a book.
The whole thing could be turned into its digital equivalent, and vice versa, e.g a song or a picture.
Context and meanings could only be obtained by linking the captured data to representations already identified and understood, e.g a religious symbol.
Whereas things managed by existing systems already come with net identities with associated meaning, that’s not necessarily the case for digitized ones as they may or may not have been introduced as surrogates to be used as their real counterpart: if handshakes can stand as symbolic contract endorsements, pictures thereof cannot be used as contracts surrogates. Hence the necessary distinction between two categories of formal digitization:
Applied to symbolic objects (e.g a contract), formal digitization enables the direct processing of digital instances as if performed on actual ones, i.e with their conventional (i.e business) currency. While those objects have no counterpart (they exist simultaneously in both realms), such digitized objects have to bear an identification issued by a business entity, and that put them under the governance of standard (internet of systems) rules.
Applied to binary objects (e.g a fac-simile), formal digitization applies to digital instances that can be identified and authenticated on their own, independently of any symbolic counterpart. As a corollary, they are not meant to be managed or even modified and, as illustrated by the marketing of cultural contents (e.g music, movies, books …), their actual format may be irrelevant. Providing agreed upon de facto standards, binary objects epitomize internet things.
To conclude on footprint, the Internet of Things appears as a complement more than a substitute as it abides by the apparatus of the Internet of Systems for everything already under its governance, introducing new mechanisms only for the otherwise uncharted things set loose in outer reaches. Can the same conclusion hold for meanings ?
Organizational vs Social Meanings
As epitomized by handshakes and contracts, symbolic representations are all about how social behaviors are sanctioned.
In system-based networks representations and meanings are defined and governed by clearly identified organizations, corporate or otherwise. That’s not necessarily the case for networks populated by software agents performing unsupervised tasks.
The first generations of those internet robots (aka bots) were limited to automated tasks, performed on the account of their parent systems, to which they were due to report. Such neat hierarchical governance is being called into question by bots fired and forgotten by their maker, free of reporting duties, their life wholly governed by social events. That’s the case with the internet of things, with significant consequences for searches.
As noted above, the internet of things can consistently manage both system-defined identities and the new ones it introduces for things of its own. But, given a network job description, the same consolidation cannot be even considered for meanings: networks are supposed to be kept in complete ignorance of contents, and walls between addresses and knowledge management must tower well above the clouds. As a corollary, the overlapping of meanings is bound to grow with the expanse of things, and the increase will not be linear.
That brings some light on the so-called “virtual world”, one made of representations detached from identified roots in the actual world. And there should be no misunderstanding: “actual” doesn’t refer to physical objects but to objects and behaviors sanctioned by social entities, as opposed to virtual, which includes the ones whose meaning cannot be neatly anchored to a social authority.
That makes searches in the web of things doubly challenging as they have to deal with both overlapping and shifting semantics.
A Taxonomy of Searches
Semantic searches (forms and pattern matching should be seen as a special case) can be initiated by any kind of textual input, key words or phrase. As searches, they should first be classified with regard to their purpose: finding some specific instance or collecting information about some topic.
Searches about instances are meant to provide references to:
Locations, addresses, …
Concerts, games, …
Cooking recipes, administrative procedures,…
Status of shipment, health monitoring, home surveillance …
Searches about categories are meant to provide information about:
Products marketing , …
Scholarly topics, market researches…
Customers relationships, …
Business events, …
Business rules, …
Business processes …
That taxonomy of searches is congruent with the critical divide between things and symbolic representations.
Things and Symbolic Representations
As noted above, searches can be heeded by references to identified objects, the form of digital objects (sound, visuals, or otherwise), or associations between symbolic representations. Considering that finding referenced objects is basically a indexing problem, and that pattern matching is a discipline of its own, the focus is to be put on the third case, namely searches driven by words (as opposed to identifiers and forms). From that standpoint searches are best understood in the broader semantic context of extensions and intensions , the former being the actual set of objects and phenomena, the latter a selected set of features shared by these instances.
A search can therefore be seen as an iterative process going back and forth between descriptions and occurrences or, more formally, between intentions and extensions. Depending on the request, iterations are made of four steps:
Given a description (intension) find the corresponding set of instances (extension); e.g “restaurants” > a list of restaurants.
Given an instance (extension), find a description (intension); e.g “Alberto’s Pizza” > “pizzerias”.
Extend or generalize a description to obtain a better match to request and context; e.g “pizzerias” > “Italian restaurants”.
Trim or refine instances to obtain a better match to request and context; e.g a list of restaurants > a list of restaurants in the Village.
Iterations are repeated until the outcome is deemed to satisfy the quality parameters.
The benefit of those distinctions is to introduce explicit decision points with regard to the reference models heeding the searches. Depending on purpose and context, such models could be:
Inclusive: can be applied to any kind of search.
Domain specific: can only be applied to circumscribed domains of knowledge. That’s the aim of the semantic web initiative and the Web Ontology Language (OWL).
Institutional: can only be applied within specific institutional or business organizations. They could be available to all or through services with restricted access and use.
From Meanings to Things, and back
The stunning performances of modern search engines comes from a combination of brawn and brains, the brainy part for grammars and statistics, the brawny one for running heuristics on gigantic repositories of linguistic practices and web researches. Moreover, those performances improve “naturally” with the accumulation of data pertaining to virtual events and behaviors. Nonetheless, search engines have grey or even blind spots, and there may be a downside to the accumulation of social data, as it may increase the gap between social and corporate knowledge, and consequently the coherence of outcomes.
That can be illustrated by a search about Amedeo Modigliani:
A inclusive search for “Modigliani” will use heuristics to identify the artist (a). An organizational search for an homonym (e.g a bank customer) would be dealt with at enterprise level, possibly through an intranet (c).
A search for “Modigliani’s friends” may look for the artist’s Facebook friends if kept at the inclusive level (a1), or switch to a semantic context better suited to the artist (a2). The same outcome would have been obtained with a semantic search (b).
Searches about auction prices may be redirected or initiated directly, possibly subject to authorization (c).