Dear colleagues, my name is Sam Baknin and I am a professor of psychology in the South and Federal University in Ostov-on-Don, Russian Federation. I am also a professor of finance and a professor of psychology in CSCFs, the Center for International Advanced and Professional Studies. I have authored the book Malignant Self-Rat Masses and Revisited, among other books on Personality Disorders. Welcome to the International Congress on Neurology and Drink Disorders, September 2019, London, the United Kingdom. Today I would like to talk to you about dreams. Are dreams a source of reliable divination? Generation upon generation seem to have thought so. They incubate dreams by travelling afar, by fasting, by engaging in all other manner of self-deprivation or intoxication. Today we have the modern variant, which is lucid dreaming. With the exception of this highly dubious role, though, dreams do seem to have three important functions at least. The first one is to process repressed memories, wishes in Freud's speech, and other mental content which was suppressed and stored in the unconscious during the day. The second role is to auditify, and generally pigeonhole, conscious experiences of the day or days preceding the dreaming. These are known as day residues. A partial overlap with the formal function is inevitable. Some sensory input is immediately relegated to the darker and dimmer kingdoms of the subconscious and unconscious, without being consciously processed at all. And the third function is to stay in touch with the outside world. External sensory input is interpreted by the dream, incorporated in the dream, and represented in its unique language of symbols and disjunction, surrealistic language. Research has shown this to be a rare event, though. And this is independent of the timing of the stimuli, whether the stimulus is delivered during sleep or immediately prior in the hypnagogic or the hypnopompic stages. It's still very rarely incorporated in the dream. When it doesn't happen, it seems that even when the interpretation is dead wrong, the substantial information is preserved. So a collapsing bedpost, as in Mori's famous dream, will become a French guillotine, for example. The message is concerned. There is a physical danger to the neck and head in both cases. All three functions are, in my view, a part of a much bigger one. The continuous adjustment of the model one has of oneself and of one's place in the world to the incessant stream of sensory external input and of mental internal input. This modification of the model is carried out through an intricate, symbol-laden dialogue between the dreamer and himself. It probably also has therapeutic side benefits. It will be a novel simplification to say that the dream carries messages, even if we were to limit it to correspondence with oneself. The dream does not seem to be in a position of privileged information or privileged knowledge. The dream functions more like a good friend would. The dream listens, advises, shares, experiences, provides access to remote territories of the mind, puts events in perspective and in proportion, and sometimes provokes. The dream induces relaxation and acceptance and a better functioning of the client. It does so mostly by analyzing discrepancies and incompatibilities. No wonder that it is mostly associated with bad emotions, anger, hurt, fear. This also happens in the course of successful psychotherapy, exactly the same thing. And so defenses are gradually dismantled, and a new, more functional view of the world is established via the dream or via the therapeutic process. This is a painful and a frightening process. This function of the dream is more in line with Jung's view of dreams as compensatory. The previous three functions are complementary, and therefore they are more Freudian. It would seem that we are all constantly engaged in maintenance, in preserving that which exists and inventing new strategies for coping. We are all in constant psychotherapy, administered by ourselves to ourselves, day in and night out. Dreaming is just the awareness of this ongoing process, and it's simple and content. We are more susceptible, vulnerable and open to dialogue while we sleep normally. The dissonance between how we regard ourselves and what we really are, and between our, let's say, expectations and dreams as incorporated in the model of the world, in the model of reality. This dissonance is so enormous that it calls for a continuous routine of evaluation, mending and reinvention. Otherwise, the more enemies might crumble. The delicate balance between us, the dreamers, and the world might be shattered, leaving us defenseless and dysfunctional. To be effective, dreams must come equipped with the key to their interpretation. We all seem to possess an intuitive copy of just such a key, uniquely tailored to our needs, to our data and to our circumstances. This arreo-critica helps us to decipher the true and motivating meaning of the dialogue. This is one reason why dreaming is discontinuous. Time must be given to interpret and to assimilate the new model preferred by the dream. Four to six sessions of dreaming take place in a typical night. A session missed will be held the night after. If a person is prevented from dreaming on a permanent basis, he will become irritated, neurotic, and then psychotic. In other words, the person's model of himself and of the world will no longer be tenable and usable. It will be out of sync. It will represent both reality and the non-dreamer, wrongly. So, to put it more succinctly, it seems that the famous reality test used in psychology to set apart the functioning normal individuals from those who are not, reality test is maintained by dreaming. Dreaming helps us to separate internal objects from external objects. The reality test fast deteriorates when dreaming becomes impossible. This link between the correct apprehension of reality model as psychosis and dreaming has yet to be explored in depth, but I can make a few predictions. First of all, the dream mechanism is of paramount importance. It's often pretty neglected. The dream mechanism and or dream contents of psychotics must be substantially different and distinguished from the dream mechanism and dream content of healthy people. Their dreams must be dysfunctional, unable to tackle the pleasant, bad emotional residue of coping with reality. Psychotic dialogue must be disturbed. They must be represented rigidly in their dreams. Reality must not be present in these dreams at all. So, studying the dreaming of psychotics is of crucially importance. Second thing, most of the dreams, most of the time, probably deal with mundane matters. Their content must not be exotic, surrealistic or extraordinary or hyper-realistic. Dreams must be chained to the dreamer's reality, these daily problems, people that he knows, situations that he had encountered or is likely to encounter, dilemmas that he is facing and conflicts that he would have liked to resolve. This indeed is the case. Unfortunately, this is heavily disguised by the simple language of the dream and by the disjointed, disjunctive, dissociative manner in which it proceeds jerkyly. But a clear separation must be made between subject matter, mostly mundane, dull, relevant to the dreamer's life, and the script or mechanism of dreaming. The mechanism involves colourful symbology, discontinuity of space and time, disjointed, purposeful action, inversion of cause and effect, so very creative. And so, the dreamer must be the main protagonist of his dreams, the hero of his dreamy narratives. This overwhelmingly is indeed the case. Dreams are egocentric, they are concerned mostly with the patient, and they use other figures, settings, locales, situations to cater to the dreamer's needs, to reconstruct his reality test and to adapt it to the new input from outside and from within. The fourth assumption is that if dreams are mechanisms which adopt the model of the world and the reality test to daily inputs, we should find a difference between dreamers and dreams in different societies and different cultures. The more information heavy the culture, the more the dreamer is bombarded with messages and data, the fiercer should the dream activity be. We can even say that dreaming is a cultural bound activity. Very external data, likely to generate a shower of internal data, should manifest in dreaming. And so, dreamers in the West should engage in a qualitatively different type of dreaming. We will elaborate on this as we continue. Suffice it to say at this stage that dreams in information cluttered societies, such as ours, employ more symbols, weave them more intricately, and the dreams are much more erratic and discontinuous. As a result, dreamers in information-rich societies never mistake a dream for reality. They never confuse the two. In information poor cultures and societies, where most of the daily inputs are actually internal, such confusion between dream and reality arises very often. It is even enshrined in religion or in the prevailing theories regarding the world. The famous story, am I a man dreaming that he is a butterfly or a butterfly dreaming that he is a man? Anthropology confirms that this indeed is the case. In information poor societies, dreams are less symbolic, less erratic, more continuous, more real, and the dreamers often tend to fuse the two, dream and reality, into one whole and act upon this whole. Reality tests in information poor societies include dreaming as a part of reality. To complete their mission successfully, and remember the mission is adaptation to the world using the model of reality by modifying it. So to complete this mission successfully, dreams must make themselves felt.  In short, dreams must be an integral part of the whole mental apparatus. Dreams seem to do exactly this. They are remembered in about half of all cases. Dreams are probably achieved without need for cognitive, conscious processing, in the other unremembered or disremembered cases. Dreams greatly influence the immediate mood after awakening. They are discussed, interpreted, they force people to think and rethink. Dreams are dynamos of internal and external dialogue long after they have faded into the recesses of the mind. Dreams directly influence actions, and many people firmly believe in the quality of the advice provided by dreams. In this sense, dreams are inseparable part of reality. In many celebrated cases, dreams even induced works of art, inventions or scientific discoveries. But think for a minute, what are works of art? What are scientific discoveries and what are inventions? They are all adaptations of all defunct reality models and modifying these models, creating new ones. And this is precisely what dreams do. So dreaming would be intimately connected to creative acts, to art, to science, to literature, to thinking. In numerous documented cases, dreams tackled head-on issues that bothered the dreamers during their waking hours, in this case of very gukulain, and the benzene molecule. So how does this theory that dreaming is a mechanism for adopting the model of reality, how does this theory fit with the hard facts? Dreaming is also known as de-state, or de-activity. It is associated with a special movement of the eyes, under the closed eyelids, and this special movement is called rapid eye movement, or REM. Dreaming is also associated with changes in the pattern of electrical activity of the brain, electroencephalogram, e.g. A dreaming person has the pattern of someone who is wide awake and alert. This seems to sit well with the theory of dreams as active therapists engage in the arduous task of incorporating new, often contradictory and incompatible information into an elaborate personal model of the self and the reality that it occupies. There are two types of dreams, visual dreams and they are thought-like dreams, cognitive dreams if you wish. The cognitive ones leave an impression of having been awake on the dreamer. The cognitive dreaming happens without any REM or EEG changes. It seems that the model adjustment activities require abstract thinking, reclassification of sonomic activity, theorizing, predicting, testing, construction of theory, a theory of mind, and a theory of the world. The relationship is very much like the one that exists between intuition and formalism, aesthetics and scientifically, feeling and thinking, mentally creating and committing one's creation to a specific, rigid medium. All models exhibit the same REM EEG patterns and may therefore be dreaming as well. Some birds do it, some reptiles do it as well. Dreaming seems to be associated with the brainstem, the pontine pigmentum, and with the secretion of norepinephrine and serotonin in the brain. The rhythm of breathing and the pulse rate change and the skeletal muscles are relaxed to the point of paralysis, presumably to prevent injury if the dreamer would disciple engage in actually enacting his dream. Blood flows to the genitals and induces piniv erections in male dreamers. The uterus contracts and the muscles of the base of the tongue enjoy a relaxation in electrical activity. These facts would indicate that dreaming is a very primordial activity. It is essential to survival. It is not necessarily connected to higher functions, like speech, but it seems to be somehow related to reproduction and to the biochemistry of the brain.  Such a model of reality can be innate and genetic in very simple forms of life because the amount of information that needs to be incorporated is limited by definition. But beyond a certain amount of environmental information that the individual is likely to be exposed to daily, there are two new needs, emergent needs. The first is to maintain the model of the world by eliminating noise and by realistically incorporating negating data. The second need is to pass on the function of modeling and remodeling to a much more flexible structure to the brain. In a way, dreams are about the constant generation construction and testing of theories. Popper would have liked it, loved it. It's a form of falsification. And this ongoing activity regards the dreamer and his ever-changing internal and external environments. Dreams are the scientific community of the self that men carried it further in invented scientific activity on a larger external scale is no wonder. Physiology also tells us the differences between dreaming and other hallucinatory states like nightmares, psychosis, sleepwalking, daydreaming, hallucinations or merely imagining something. The REM EEG patterns in all these other activities are absent, and the latter states are much less real. Dreams are mostly set in familiar places. They obey the laws of nature contrary to misinformation. At the very least, they obey some inner logic. Their hallucinatory nature is a hermeneutic imposition. It derives mainly from their erratic, abrupt behavior, space, time and goal discontinuities. But this is one of the elements in hallucinations. Hallucinations have many more characteristics which are absent in dreams. Why is dreaming conducted while we sleep? Why not while we're awake? Well probably there is something in it which requires what sleep has to offer, a limitation of external sensory inputs, especially visual ones. And this perhaps is the reason why dreams have a compensatory, very strong visual element to try to offset the missing visual input. An artificial environment is sought in order to maintain this periodical self-imposed deprivation, static state and reduction in bodily functions. In the last six to seven hours of every sleep session, 40% of people wake up. About 40%, probably the same dreamers, report that they had a dream in the relevant night. As we descend into sleep, the hypnogobing state, and as we emerge from sleep, the hypnopomping state, we all have visual dreams that are different. It is as though we are thinking these dreams. They have no emotional correlate, they are transient, undeveloped and abstract, and expressly deal with the day's residues.  Day residues which clearly do not need to be processed by dreams are swept under the carpet of consciousness, maybe even erased. Physiologically, there's a whole drainage system which carries literal trash, broken molecules, used up materials, waste products from the brain to the spine during the night. This may be, still needs to be studied, but this drainage waste disposal operation, which is a physical activity, may be the physiological correlate or equivalent of dreaming. Suggestable people dream what they have been instructed to dream in hypnosis, but not what they have been so instructed while partly awake and under direct suggestion. This further demonstrates the independence of the dream mechanism. It almost does not react to external sensory stimuli while in operation. It takes an almost complete suspension of judgment in order to influence the contents of dreams. It would all seem to point at another important feature of dreams, their economy. Dreams are subject to four articles of faith which govern all phenomena of life. Number one is homeostasis, the preservation of the internal environment, an equilibrium between different but interdependent elements which make up the whole. Second equilibrium, the maintenance of an internal environment in balance with the external one. Third, optimization, also known as efficiency, the securing of maximum results with minimum investment resources and minimum damage to other resources not directly used in the process. And perhaps the most important one is parsimony, also known as Occam's razor, the utilization of a minimal set of mostly known assumptions, constraints, boundary conditions, symbols and initial conditions in order to achieve maximum explanatory or modeling power. Sorry, in compliance with the above four principles, dreams had to resort to visual symbols. The visual is the most condensed and efficient form of packaging information. A picture is worth a thousand words. The same goes, studies have supported this. And computer users know that to store images requires more memory than any other type of data. But dreams have an unlimited capacity of information processing at their disposal, the brain at night. In dealing with gigantic amounts of information, the natural preference when processing power is not limited would be to use visuals. Moreover, non-isomorphic polyvalent forms will be preferred. In other words, symbols that can be mapped to more than one meaning, symbols that have more than one meaning, and symbols that carry a host of other associated symbols and meanings with them, these symbols would be preferred. They're like shorthand. So symbols hold a great amount of information. Most of it is stored in the recipient's brain and provoked by the symbol. This is a little like the Java applets in modern programming. The application is divided to small modules, which are stored in a central computer. The symbols generated by the user's computer, again using the Java programming language, provoke this to surface. The result is a major simplification of the processing terminal, the NetPC, and an increase in its cost efficiency. I hope the metaphor is not lost, at least on computer savvy business. Both collective symbols and private symbols are used in dreams. Jung would have been very happy with this discovery. Collective symbols, Jung's archetypes, prevent the need to reinvent the wheel. They are assumed to constitute a universal language, usable by dreamers everywhere, regardless by the way of culture and society. The dreaming brain has therefore to attend to and to process only the semi-private language elements and the culture-bound and society-bound elements. This is less time-consuming, and the conventions of a universal language apply to the communication between the dream and the dreaming. Even the discontinuities have arisen. A lot of the information that we absorb in process is either noise or repetitive. This fact is known to the authors of all the file compression applications in the world. Computer files can be compressed to one-tenth the size without appreciably losing any information. It means that 90% of the information is trash, not needed. A redundant repetitive. The same principle is applied in speed reading, skimming the unnecessary bits, getting straight to the point. So the dream employs the same principles. It skims. It gets straight to the point. It zips. It compresses. And from the point, it gets yet to a lot of points. And this creates a sensation of being erratic, of a brightness, of the absence of spatial or in temporal smoothness, logic, or purposefulness. But this all serves the same purpose, actually, to succeed to finish the herculean task of refitting the model of the self, the model of the world, these theories of mind and theory of world in one night. This all has to be done in one night. So the brain skips a lot of redundant information, a lot of trash, a lot of repetition, a lot of noise. It filters it out. It uses sophisticated filtering. And it skips from one data point to the next. A little like quantum tunneling, the particle disappears. And suddenly reappears, not having crossed any space in between. This is dreaming, is conscious tunneling, where the consciousness hopes, like on pebbles in the shore, hopes from one data point to another, without having crossed anything in between. Hence, the disjointedness and discontinuity of dreaming. Thus, the selection of visuals, symbols, and collective symbols and of the discontinuous model presentation, the preference of alternative models, methods of presentation, representation. These are not accidental. This is the most economic and unambiguous way of representation. And therefore, the most efficient one, most in compliance with the four aforementioned principles. In cultures and societies where the mass of information to be processed is less mountainous, these features are less likely to occur. Indeed, dreaming in more primitive societies is much more narrative-like, much more story-like.  On the face of it, dreaming is a colossal waste of energy and psychic resources. Dreams carry no overt information content. They bear little resemblance to reality. They interfere with the most critical biological maintenance function. Sleep. They don't seem to be goal-oriented. They have no discernible objective. They make us feel bad very often. In this age of technology and precision, efficiency and optimization, dreams seem to be a somewhat anachronistically quaint relic of our life in the savanna. Scientists are people who believe in the aesthetic preservation of resources. They believe that nature is intrinsically optimal, palcimonious, and in this sense, beautiful in wives. Scientists dream of symmetries, laws of nature, minimalist theories. They believe that everything is a reason and a purpose. In scientific approach to dreams and dreaming, scientists commit all these scenes combined. They anthropomorphize nature. They engage in theological explanations. They attribute purpose and paths to dreams, aesthetic values, where there might be none. So they say that dreaming is a maintenance function, the processing of the preceding day's experiences. Or the scientists say that it keeps the sleeping person alert and aware of his environment. But no one knows for sure. We dream. No one knows why. We are dreaming beings. Dreams have elements in common with dissociation, with hallucinations. But they are neither. They employ visions because this is the most efficient way of packing and transferring information. But what information? Freud's interpretation of dreams is a mere literary exercise. It is not a serious scientific work, which does not detract from its awesome penetration and beauty, of course. I've lived in Africa. I've lived in the Middle East, North America, Western Europe, Eastern Europe. Dreams fulfill different societal functions and have distinct cultural roles in each of these civilizations. In Africa, dreams are perceived to be a mode of communication as real as the internet is to us. Dreams are pipelines through which messages flow, flow from the beyond, life after death, for example, or from other people, such as shamans, remember Castaneda, or flow, dream convey messages from the collective, Jung, from reality, and this is the closest to Western interpretation, from the future, precognitive dreams, or from assaulted divinities. These are all attempts to relate to dreams in these cultures. The distinction between dream states and reality is very blurred in places like Africa. People act on messages contained in dreams as they would on any other information they obtain in their waking hours. This state of affairs is quite the same in Middle East and Eastern Europe, where dreams constitute an integral and important part of institutionalized religion and the subject of serious analysis or contemplation. In North America, the most narcissistic of these cultures, dreams have been construed as communications within the dreaming person. Dreams no longer mediate between the person and his environment, but between different constructs and representations, inner objects, internal objects, and introjects inside the person. They are the representation of interactions between different structures of the self. The role of dreaming in the West is therefore far more limited and their interpretation is far more arbitrary and impoverished in value because it is highly dependent on personal circumstances and the psychology of a specific dream. Apropos narcissism. In many respects, narcissism is a dream state. The narcissist is totally detached from his human milieu, devoid of empathy and obsessively centered on the procurement of narcissistic supply, attention, adulation, admiration. The narcissist is unable to regard other people as three-dimensional beings with their own needs, rights, wishes, preferences, priorities, lives, and emotions. And this mental picture of narcissism can easily serve as a good description of the dream state where other people are mere representations or symbols in a hermeneutically sealed thought system. Both narcissism and dreaming are autistic states or more precisely, sort of cystic states of mind with severe cognitive and emotional distortions. By extension, one can talk about narcissistic cultures as dream cultures doomed to a wound awakening. It is interesting to note that most narcissists I know from my work have a very poor dream-like, dream life and dreamscape. They remember almost nothing of their dreams and are rarely, if ever, motivated by insights contained in their dreams. Perhaps the reason is that narcissists are in a constant dream state anyhow, even when they are so-called awake. The internet is the sudden and voluptuous embodiment of dreams. It is too good to be true, so in many ways it isn't. I think mankind, at least in the rich industrialized countries, is moonstruck. It serves this beautiful white landscape in suspendent disbelief. It holds its breath as the internet unfolds almost autonomically. People don't their belief and don't believe the hopes and the scapes presented by the internet. The internet has therefore become a collective phantasm at times a dream, at times a nightmare. Entrepreneurship involves massive amount of dreaming, of course, daydreaming and dreaming, and the internet is pure entrepreneurship. We are all entering a kind of dream state. In 2010, there was a movie called Inception, which presented a series of concepts related to dreaming. In the film Inception, Dom Cobb, a character, is an extractor. He steals confidential information by hacking into a subject's brain during a dream and calling the victim into disclosing his over-secrets. This intellectually challenging and visually captivating film makes a series of assumptions about dreaming, none of which withstands close scrutiny, and gives us to study this movie in depth as a way of closing my argument. The dream starts by assuming that it would be possible to share dreams, the movie starts, I'm sorry, by assuming that it would be, at one time in the future, it would be possible to share dreams, dream sharing. The film's fundamental assumption is that dreams are objective entities akin to buildings, for example, whose existence is independent of the observer and are therefore accessible to all and sundry. But dreams are highly subjective experiences, they're not objective. External and internal cues are interpreted by an integrated into complex, shape-shifting, and highly idiosyncratic neural networks resident in the head of the dreaming individual. One cannot tap into another person's subjectivity, thoughts, emotions, dreams, even in principle. And this is, of course, the infamous problem of intersubjectivity. While we can communicate and discuss our inner world, meta representation, meta phase, metaphysics, if you wish, of our internal world, we cannot share it in any meaningful sense. We cannot invite visitors or tourists into our inner landscape. Lucid and directed dreaming is possible, but dream sharing is not. If we were to enter someone else's mind, we would merely experience our reactions to her mind, not her mind itself. Intersubjectivity is defined by the Oxford companion to philosophy, this way. Intersubjectivity refers to the state of being somehow accessible to at least two, usually all in principle, minds or subjectivities. It does implies that there is some sort of communication between those minds, which in turn implies that each communicating mind is aware not only of the existence of the other minds, but also of its intention to convey information to the other minds. The idea for theorists is that if subjective processes can be brought into agreement, then perhaps that is as good as the unattainable status of being objective, completely independent of subjectivity. The question facing such theorists is whether intersubjectivity is definable without presupposing an objective environment in which communication takes place. So there must be some kind of wiring between A and B. At a less fundamental level, however, the need for intersubjective verification of scientific hypothesis has been long recognized. Intersubjectivity is a barrier. We have a theory of mind about other people's minds. And of course, we assume that they have minds, but this is all very solucistic and very arbitrary. The second assumption in the movie is confusion between defenses and dreams. The film cannot make up its mind. Cope tells the aptly named Ariadne, the architect, the dream designer, that the dreaming person's defenses are down and all vigilance is gone. And this vulnerability is what makes it possible to extract. It makes possible the art of extraction and renders counter-extraction a necessity, renders neuro-security, defensive tactics against thieving extractors, such as Cope. Yet throughout the movie, the invaded subjects subconscious, should be of course unconscious, keeps attacking the extraction team. It keeps sending out hostile environment and murderous projections, fragments to eliminate the extractors. Cope even compares these apparitions to white blood cells. So which is it in a dream state? Defenses down or defenses at a maximum? As Freud, the surrealist and Dadais knew well, dreams are audio-visual manifestations of the unconscious, the seat of all psychological defense mechanisms. In dreams, we are not under-vigilant, but hyper-vigilant. In dreams, we are paranoid. One cannot compare the subject to reveal secrets even under hypnosis, let alone while dreaming. Moreover, dreams provide access only to the unconscious, but secrets reside exclusively in the conscious part of the mind. The extractors are looking for confidential information in the wrong place. Finally, dreams use symbols and representations. They require interpretation. Even the most pedestrian information is thoroughly encrypted using a highly idiosyncratic private language. The film Earth makes a mistake in that it depicts dreams as merely augmented reality or the heat of a highly imaginative and creative soul. Dreams are not augmented reality. Dreams are coded messages, not representations of the world. In this sense, every dreaming person is a solipsist and an extraterrestrial alien with a language of his own. The movie deals with the issue of waking up and the stability of dreams immediately following wake-up. In the film, there are only two or three methods of terminating the dream state and waking up. In reality, the repertory of what makes us wake up is infinite, unlimited. We wake up for hundreds of reasons, including metabolic processes, pain, environmental stimuli, anxiety, compulsive thinking, intrusive thoughts, circadian awareness, habits, fears, you name it. Dreams are highly unstable states. So unstable in effect that many scholars believe that this precisely is the role of dreaming to keep us alert on our toes even as we sleep. The use of sedatives as in the film actually suppresses dreaming, making them highly counterproductive as far as the extractors are concerned. And then in the movie, there's a dream-time dilation, and this is a long-discarded myth. Dream-time is roughly equal to real-time. One hour in a dream translates to one hour in reality. It is true, though, that the laws of physics are sometimes suspended while we dream. Distances contrapped or vanish, for instance. And this gives the erroneous impression of time dilation. The movie raises an interesting issue of totems and the realities. The film warrants against the blurring of boundaries and distinctions between dream and reality, especially if one leverages one's memories in the framework of lucid dreaming and incorporates them in the design of new fantasma gorillas. The film seems to imply, seems to put us on notice that dreamers may use the reality test and remain unable to tell the two states apart. They wouldn't know if they are dreaming or awake. To guard against this ominous psychosis, extractors use totems, objects whose behavior is different in a dream to their true and everyday conduct. Cobb carries a spinning top, which in his dreams, never stops spinning, an oddity which informs him of his slumberous state, of course. So if the top doesn't stop spinning, it means I'm dreaming. While it is true that objects acquire unfamiliar, even outlandish properties and behaviors in our dreams, their deviations and abnormal characteristics vary from one dream instance to another and they are utterly unpredictable. In one dream, the spinning top will spin forever, but in another dream, it will refuse to spin at all. And in a third dream, it will turn into a dove. Totems, therefore, would be useless as a litmus test. Far better to use a classic reality check, try to go through a solid object, levitate, look at the face of an analog clock or flick a light switch on and off. Moreover, it is not strictly true that all dreams feel real. Some dreams do, some dreams don't. We often know that we are dreaming even when we are in the throes of an unfolding visual narrative that is inexorable. We sometimes test ourselves in the dream or even will ourselves to wake up. This ability to tell dream from reality is the heart of our certainty, of which is which. Nor is it universally true that dreams have no discernible or remembered beginning and that we find ourselves inexplicably immersed in them. The professional literature contains numerous descriptions of dreams with neat beginnings. More often, dreams lack an ending. These absent resolutions and closures provoke and elicit in us, psychodynamic processes which are conducive to personal transformation, to growth, even to healing. There's the issue of nested dreams. False awakening, a dream within a dream, is a documented, albeit rare, phenomenon. The dreamer usually dreams that he is waking up, but is actually a dream. There are three caveats, though. One, most nested dreams occur in familiar surroundings, one's bed, home, workplace. Two, the nested dreams share subject matter, some continuity, narrative, plot, storyline. Number three, invariably the dreamer realizes that he's dreaming. Only the second condition is made to a limited extent in the film, Inception. But what's the connection between dreaming, creation, discovery, and inspiration? I alluded to it at the beginning of my presentation. And in the movie, everyone around Corbett sees that Inception implanted an idea in someone's dreaming mind so that he feels that he has come up with it once he wakes up. Inception is an impossibility. Dreaming, Arthur says, involves pure creation. It is a process that feels like discovery or inspiration rather than the laborious and tedious constructs that we come up with when we are awake. Corbett tells Ariadne that our brain is far more active and far more efficiently deployed when we dream, which, by the way, is completely untrue, judging by brainwave activity. According to these cinematic extractors, implanted ideas would therefore feel alien, absent the essential experiences of discovery and inspiration. The subject is bound to react with violence and aggression to the dimly perceived invasion in mind or dream snatching. It is the extracted team's job to avoid these defenses against intrusion by convincing the subject that the foreign idea that they had implanted in his mind is actually his idea. I can't say move, because I'm not a spoiler, and the movie is worth every minute of your time. But can we really make the distinction between our ideas and ideas that we have been exposed to and absorbed? Ideas whose source is external. How often do we plagiarize unconsciously? Is this taxonomy of endogenous versus exogenous? Ideation? Correct. The answer is a resounding number. We cannot reliably attribute our ideas to their various sources, and we cannot credibly tell their origins. Nor do we try to, actually. We assimilate means and make them ours because such plagiarism has survival value, not only to us as individuals, but to the species. The unhindered dissemination of strange notions to borrow Seito's phrase in the film. This unhindered dissemination has untold beneficial effects as any internet addicts will attest. Furthermore, inspiration and intuition are often cloaked as reasoning and rationalization. We feel that certain discoveries, certain theories, certain words of art are the outcomes of our toil and rational investment, even when they are actually the tip of an unconscious iceberg. Dreams are no different. When we are in the dreams, we obey this or that logic. We construct theories about our environment, events, other actors, and about ourselves. We assume ownership of our ideas and actions regardless of their source. We are alive in the dreams. We never bother to stop or ask the absurd and unanswerable question. Wait a minute. Whose idea was this in the first place? And so the premise on which the entire film is built is juvives, because we continue our life seamlessly when we dream. Thank you for listening.


So the one, two, three of data sharing agreements. This webinar is being brought to you by the Australian Research Data Commons, the ARDC. For those of you who don't know us, we have a purpose to provide Australian researchers with a competitive advantage through data with a mission to accelerate research and innovation by driving excellence in the creation analysis and retention of high quality data assets. Before I begin, I would like to do an acknowledgement of country. So we acknowledge and celebrate the first Australians on whose traditional lands we meet, and we pay our respects to their elders past, present and emerging. And for me, that is the Gadigal people of the Eora nation here in Sydney. So firstly, some welcomes and introductions. So welcome to all of you. Thank you for coming along to this webinar. It's great to have so many people on board and to see the interest that is out there within data sharing agreements. My name is Robin Burgess and I'm the research data specialist in data governance at the ARDC. And I have a real interest in the ways in which we're able to share and reuse data. And I've had many questions since joining the ARDC around the creation of data sharing agreements, which brought about the development of the documents that I wish to share with you today. And looking at the potential kind of one, two, three key areas that I think are important when it comes to data sharing agreements. Also, this is an opportunity to hear from those who have created data sharing agreements and have been working with them. So we've got Paula and Jake from the UNS from UNSW and Thomas from Swinburne University. He'll be giving their examples. And any of you on the call, if you'd like to share your experiences in chat or any comments you have that would be great. Also, hopefully there'll be time for questions. We'll do questions at the end of all the presentations. And I'm keen to also look at determining what next steps in the area could be and any further support you might be looking for from the ARDC. So do use the chat function as a way to for conversations. First, what is a data sharing agreement? I'm sure you're pretty much all across what these are having potentially worked with them. So they can be seen as a legal document and an agreement between individuals or groups wanting to share or access data. There are tool and document that will help protect the misuse of data from a project. And it can also be said that they're very much tailored for a specific project or organization. There really is no single template for a data sharing agreement. I've added an example here from the ONDC who have been working very heavily with data sharing agreements and they've produced a template to support with the access and sharing of government related data. So they will be running a session on data sharing agreements as well. These slides will be shared with you so you'll be able to click on the links that are within the present. So data sharing agreements guidelines is the first one that I want to present to you. So within this document. We look at commenting on what a data sharing agreement is, when data sharing agreements are needed, common types of data sharing agreements, the components that consist within the data sharing agreement and how to go about creating a data sharing agreement. So I just want to point out some of the key components of a data sharing agreement because this is often been a question that I've received. So we can very much look at ideas around the information about the data, the parties and the context of the agreement. So this is looking at details of the data to be shared, the purpose of sharing the data, any time periods affiliated to the sharing of the data and roles and responsibilities. The next section is related to the actual conditions of sharing. So this relates to what the data could potentially be useful and if there's any constraints in place with the use. Also sensitivity, security and retention of the data. Commentary on the methods of how the data will be accessed and actual details around the data such as formats. And then there can be some final sections and aspects related to the agreement to include such as a simple title for the document. So if you want to include aspects related to licensing or copyright conditions, you might have reporting requirements once the data has been shared, and it's also good to comment on risks and variations that might have occurred in the data prior to sharing it. So the second document that the ARDC has produced is related to data sharing policies. So within this document we comment on the types of data and the agent, the agencies have in their custody. The principles and strategies around sharing of that data commentary on governance and management procedures, when the policy might be needed, and once again key components of the policy. So comment on some of the key components that we list in this document. So the first is related to regulatory requirements, whether there's any other policies that are already in place that impact on your data sharing such as a research data management policy or open access policy. Also commentary on data governance require requirements are important. So this looks at the idea of ethics, roles and responsibilities and access to the data. It also touches upon the actual procedures for access in the data. So how will the data be accessed and what is the data request procedure. Other aspects include licensing and change management, and also a technical framework might be applied, looking at what technology and tools are out there that will support the data being shared. And also importantly with regards data is understanding the classification of the data, whether it's sensitive data or freely available data. So now we'll just a quick comment on the 123 of data sharing agreements. So these are the three key areas that I feel are very important when it comes to understanding and the application of data sharing agreements. So the one. So the first aspect that I'm, I would say you need to consider is do you actually need a data sharing agreement. So you might actually have data that you might actually just be able to make available through a simple license, or there might be another agreement process that could be in place for the sharing of your data. The second one is to review and understand the components of the data sharing agreement. So those are the areas I've commented on in this presentation so far. And to look at the creation of a template to support this and to subsequently complete the required sections. And finally one that I think is really important is that of getting support for the completion of the data sharing agreement document. This support might come from your legal office at your university or organization, and also you should also have many discussions with those for whom you were wanting to share the data with or receive the data from to ensure that there's compliance and there's compliance with regards the content of the data sharing agreement. And then finally ensure that the document gets signed off. And this is most likely to be done by legal entity. So just finally from me before we move on to the case studies. I'd like to ask you to kind of comment in the chat and I'll make note of any comments you make kind of what further support would you require with regard to data sharing agreements. Would you be looking for further guidelines, the idea of templates or examples. My final question is what sort of elements of data sharing agreements do you currently find the hardest, or is there an aspect that you find the easiest. So I'll be happy for you to share any thoughts on those questions within the chat. I'll stop sharing my screen, and I will hand over to Paula, Jake and Thomas, who will share their experiences with data sharing agreements. Thank you. And I apologize for the slight mishaps with the sharing and stuff that happened. So two of us from UNSW, myself, I work in the data governance area and Jake Simon who works in research technology and and research data management all the way. Jake explain when you get to him. Next slide please. So the data governance at UNSW, we've been doing data governance, first of all, high level, since about 2015 when take her others my manager, the chief data officer established the data governance framework. And then the work that came straight out of that was to put together the data governance policy suite. We've got quite an extensive data governance policy suite as a result. Policy sets out roles and responsibilities, including data ownership. We call it, we call our data owners, data controllers. So if I slip up and say data owner or data controller, that's what I'm talking about. And also other the role the policies also talk about quality and integrity classification and security. We've got a data classification standard. We have data handling guidelines which has just recently been superseded by a whole suite of cybersecurity standards. We've got data breach policy and procedure data retention procedure and a data sharing agreement procedure which is basically just formalizing what we've developed over the past few years. Then within that data governance policy suite we also have the data governance for research data. So Jake may touch on those and then related policies that we have privacy record keeping and cyber security. So all of those together guide what we do in terms of putting together data sharing agreements, which I'll touch on as we go to the next slide. So with data sharing at UNSW, we have a much more, I use the word mature, but it's probably got connotation. We've been doing data sharing agreements for teaching and admin data in a centralized way, much longer than we have for research data. But we're applying the things that work and are relevant in that area to research data as well as Jake will mention. But I thought it's worth taking you through what we've been doing with teaching and admin data. So, and we've got about 150 data sharing agreements in place for the teaching and admin data. So basically, whenever data is going to be used from one of our enterprise systems in another, or if it's going to be used for an enterprise system in one business unit by a different business unit, then there's a requirement for a data sharing agreement to be put in place. We've been doing this now since I think I've found some data sharing agreements that go back to 2017-2018. But I have to say that it's still coming as a terrible shock to some people within the organization when they hit one of our gatekeepers and are asked whether they have a data sharing agreement in place for this. So it's still a very organic process, but that's the basis on which we're putting data sharing agreements in place from one enterprise system to another from one enterprise system in one business unit to another. And then of course, if we, if we procure or use an external service platform system, what have you, then there must be a data sharing agreement between us and the provider of that service system platform. I mentioned gatekeepers. So we have policies. And as you all very well know, it's one thing to have policies and it's another thing to enforce them. And it's a learning experience for everyone. Over time we've established a set of informal gatekeepers that help us to enforce data sharing agreements. Of course, the data controllers, the owners custodians, the system owners, the data providers, cyber and the research ethics committee. All of those are that in a formal sense or an informal sense depending on the different policies and procedures that are in place. Say to someone who's requesting data, do you have a data sharing agreement for that? And if they don't, then they get sent to me. So I am the central point within university for dealing with data sharing agreements. They come to me or they use this, our SharePoint intranet to request the data sharing agreement. And then I get the process going. Next slide please, Jack. So it is a centralized process. I'm the hub and basically I then negotiate with and deal with all of the other elements that are spelled out here. So the form comes to me first and we ask them the basic information in high level terms. What's the data that you want? What's the source system? How are you going to transfer it? And how often what are your user and access controls? What are you going to be using it for? Are you going to distribute it any further? And how are you going to store it? Where are you going to store it? So sovereignty is obviously and storage sovereignty is obviously an issue. So the area that I work in on the data governance manager and myself and my boss are the data governance officer. Once I've gathered that first bit of information, then I will request additional information. I'll need a spreadsheet of every single data field that's required because I know that the data controllers will want to see that. We'll look at them all. I will help the data user classify all of the data fields. I will determine whether cyber has assessed either the solution that they're using in-house or the solution that's being procured. I will talk to the privacy officers to see if there's any privacy considerations either relating to the data itself or the procurement contract. And as I said, I'll talk to cyber and then I will draft together a data sharing agreement. We have a template, but I've discovered that the template only goes so far and that pretty much every situation requires a bespoke data sharing agreement. Having gathered all of that information, then we have an approval meeting. We'll hold it with the data user, the data controller, privacy officer, system owner. And essentially the data controller interrogates the data sharing agreement and the data user to get to their comfort that the data will be used appropriately for an appropriate purpose. We'll have all of the access controls in place. And the system, the data user understands that they can only use it for the purpose that's been approved in this agreement. Generally speaking, the data sharing agreement has been approved for three years. That's general. Sometimes only for six months, if for example, cyber is still doing penetration testing and is happy to give an interim approval, but not a long term approval. So, you know, the timing may change. Next slide. Thanks, Jake. Thanks over to you to talk about how we're applying this, these learnings into the research data sharing space. Yeah, thanks Paula. So I'm from research technology services. As Paula mentioned earlier, we have a function within that, which is the research data management single point of contact IDM at UNSW. I use just an email address really, but so that's been our main point of contact with people who want to know about how to do a research data sharing agreement. And because we've had some inquiries on that Paula actually wrote a sort of version of her teaching and admin data sharing agreement as a research one. So adding research things and changing bits and using some stuff from other templates that we found. So that's it on the right there. So we have that template. I don't know that I think we've had one person that asked for it and not sure if anyone's actually used it yet. So that was it's been around for a year or so now. I think our main interest main sort of contact with these data sharing agreements is that we don't see a lot of them we're assuming that there are there are some happening in the background but when we mainly know about them when they come to our email address when they have some sort of problem or they're asking questions about us and then we work with Paula usually to try and figure out what is happening and what we need to do to help them out. In my experience we've been doing this IDM at UNSW for years, something like that now and we haven't had too many data sharing agreement inquiries during that time. We have had some and we've usually what has been our experience is that people come to us with a data sharing agreement because they're asking for data from probably a government body health district, someone like that. And they've brought a template, their own data sharing agreement to UNSW that presented that to UNSW and somebody wants to know some details about how to fill it in. So usually it's not sharing agreement that we have there it's something that's coming from someone else. They have a pre filled agreement sometimes it's you know it's pretty good sometimes it's very vague or it's designed for companies to fill out or something like that. But we've helped people with fill them in there's some considerations there I think Robin covered a lot of this stuff earlier. But that's what we're trying to make sure is is detailed appropriately in the data sharing agreement. And often what happens is that the data sharing agreement is presented to us, we have we give it a read it's legal ease often. And so we have to fix the road and make sure that we're not promising things that we can't do. Because we're research technology services, I often are involved in the technical bits about data storage or systems that have to be used requirements that come from the external people about what systems were allowed to use, trying to match those with requirements that our own cybersecurity and other policies cover. So that make sure that we're not sort of conflicting but what is that that's ended up being is a negotiation, I find it is an interesting output of what that is is that they come with an agreement which looks like a legal thing. But it ends up being you know they say oh you have to use this system or that system and we can't comply with that because we're a university or we don't have access or the researcher doesn't have a budget or something and so we have to have a back and forth with the data controller or the data provider and figure out what we can do and what we're allowed to do. And most of the time that's been pretty good sometimes we have had a couple where it's gone it's gone away and never come back so possibly they haven't been able to get the data because they haven't been able to come to terms that we're agreeable with the data provider. The template that we've got here was created actually when a data provider hadn't done it before and was asking if we had a template that they could use to to form an agreement because they didn't really know how to do it and so we said okay this is what it looks like. So it was a thing that a template like with the sort of things you see there and then they helped them and the researcher that was asking for the data filled those out. We have had these are the sort of some of the places that we've seen data agreements happen. German Bureau of Statistics is common ATO we've had, there's a consumer data right page, which I've recently been involved with some people trying to get some data from there. So it's a very complicated and high requirements for security and systems and and certifications from that one which was interesting. So these people. So I think that's been the most of the things that we've got from sort of health districts. And now this consumer data right so they those people all sort of brought their own data sharing agreements that we were sort of asked to sign basically or the researcher was asked to sign. I just wanted to mention data place because Paul has been doing a lot of work with this and hopefully it's going to be somehow helping us with with data sharing agreements. It's just the Australian government website has not quite gotten online yet, but the idea being that you can sign your institution up for it and then the Institute government based data sharing stuff will go through there and we again we sort of have had a few people go through Paula. She can talk more about that if people are interested maybe but to try and use that a place for creating data sharing agreements or negotiating data sharing agreements. But at the moment, it's sort of half made so I don't think we have a lot to talk about there yet because it's not quite ready. So that's all I was going to talk about there. So maybe we can pass it on to the next person. Sure. That was fantastic thank you Paula and Jay for giving it as an insight into the areas that you're working on with regards data sharing agreements what's working what's not and the kind of logistics and the number of people who are kind of involved in the process. And you mentioned data place there yeah. The RDC have actually got a date place data accreditation meeting happening tomorrow at three o'clock if anyone's interested I can send you a link to that meeting it's a support group to discuss aspects around data place and gaining accreditation as a data user within the platform. And so at this point, as I mentioned we'll take questions at the end so I'll hand over to Thomas, and hopefully you'll be able to share your screen. Well let's have a go. All right so hopefully screen sharing shout out if I'm not looking good. I'm just more informal than the last presentation and I'm going to focus mostly on a little bit of the process and the outcome of a template that I developed. Ironically, before I had seen Robin's really nice data sharing agreement development documentation that's been really interesting, looking at the alignment between it and that document. I think part of the RDC institutional underpinnings project and I was running part of the policy development thread of that larger project within Swinburne. Part of that, initially, the aim was to just put together a policy that could be kind of modular and used between universities and adapt it and things like that around research data management. This came out of the fact that Swinburne did not have any research data management policy at all at the time which is, I think, a big oversight for a university with technology in the name. But as part of that project it became increasingly clear that actually there was a whole load of an ancillary material around it that was needed you know you can't just have a standalone policy and I think everyone knows that it. To have that you are inviting essentially zero percent compliance. So, there was also some guidelines and how tos and FAQs and training material developed around it, as well as a whole comms communication package around it, but also a few templates and that helped people out. The three sort of relevant templates from this point of view was a read me template to describe individual data sets or folders or directories of data set, a research data management plan template, and a data sharing agreement template. The reason behind these was because again we previously didn't have anything so we wanted to make sure that we were putting something out there that was relatively easy as a low bar to start with. So for example, our research data management plan that not in any fancy system or through a control form, they are Word documents, which many universities have previously had and then moved on from. This is, you know, starting from a relatively low bar, but the benefit, I guess, from the pointer from that point of view is that Word documents have quite a useful balance of being able to have, you know, controlled areas where people enter information, but also being highly adaptable. And then it's already been mentioned by basically everyone who's previously spoken. You can't have a strict data sharing agreement template, there's always going to be the particularities of the data set or the signatories that essentially mean that all of, even if you start out with a template it'll inevitably be significantly edited since then. So part of this I went out and I started sniffing around the internet to see if I could find some creative commons license sharing agreements because that would save me a whole load of trouble if I could just adapt an existing data sharing agreement template. I went into a reshare screen actually, because I ended up with this folder full of dark sharing agreements that I've called from around the internet. But interestingly, they kind of fell into two broad camps. One was data sharing agreements written in legalese so they look very much like legal documents with a large amount of text a large amount are typically organized into statements and section and usually kind of organized around big definitions throughout the text. Another category is to have grown out instead from the research data management plan sphere, just kind of the direction that I come from as well. And they look more more like research data management plans to be shared between more than one party, and then everyone essentially signs up for this joint research data management plan. Those are broadly the two camps I've seen things fit into and it's more or less 5050. But it's interesting that they're kind of coming from such different directions. Unfortunately for me none of them were created commons license all of the, all of the data sharing agreement templates that I could find out there online at least at the time this was back in 2022. So, you know, always reserved copyright so no dice and being able to talk up in that direction. So what instead I did, I'll just go back to my original share. Instead, I did was as part of this kind of package of material. I developed a new templates that I was then happy to make creative commons license so I just did the DIY link up in the chat so that people have it just in case it's useful to get access to that. So what I'm going to start up with is this document. So, I'll just quickly screen share it is going to be relatively familiar from anyone who's ever put together a research data management plan because that was the format I guess that we went for. Swinburne livery obviously because we're using it at Swinburne but it's adaptable. I'll just highlight the licensing information down at the bottom, which is that the template is licensed under creative commons by for license. So, if any university out there is in need of a data sharing agreement and wants to cut as a template and wants to use it as a starting point they're welcome to. I already linked to the DIY for the, but there's a no day repository. This is a live document. So, as I gain additional feedback from people I have been updating it over time it's now on version 0.2.5 I think. So it's going to be updated over time but it may be the very useful starting point for different groups. And it actually aligns reasonably closely to what's been talked about already in terms of the kind of logical sections for data sharing agreement to form. There's a few things that are maybe slightly different to it so I thought I would highlight those. The first thing is that this is meant to be flexible enough to be used for requesting data from a third party into to be used within the university and also licensing of data that originated within the university to be shared with a third party. Swinburne does do some medical research where we're interacting with hospitals and other clinical research institution, but we do a lot more research with private corporations and companies we've got a lot of engineering and technology work that goes on here so that tends to be the focus. And one of the things that comes up in that context is having to be quite specific about a project may have multiple data set. And one thing that can be slightly tricky is that not all of those data sets are going to require the same handling. And the other thing that we've come across is in clarity between the original raw data set being provided and derived data sets that are being generated from them. And so that was an all from those. And so that was another thing that we wanted to try and be quite specific around where possible. And so some of this is relatively obvious stuff, the dark date and date, the descriptions of those data sets that were all clear on which data sets we're talking about particularly the project can have dozens of different data sets involved. The usual things that side of things in terms of who has access to the data sets, but also information about, can these data sets be disseminated on to other parties. We have had problems, for example, where researchers have ended over a data set to an external collaborator and that external collaborator has used a platform or a tool, which automatically shares that data on the third party is all vice versa, which is particularly embarrassing from our point of view when we are exposing data to third party platforms unintentionally. And so it's just a work while being clear about whether that's intended or not. In terms of storage, actually, this is already a little bit out of date, of course, because our story is being commissioned by the end of this year so previously we were more or less the options were cloud store, Nectar, or other, particularly, particularly being asking researchers to be clear where it's being stored. Now that our stories being the commission we're likely moving over to using one drive for those same functionalities one and the sort of same functionalities. But in particular, being clear that from the university's point of view, that was being stored both encrypted and within Australian borders. Now this is obviously relevant from very domestic point of view, if we're talking about an international collaboration, it's entirely possible that a copy of that data would need to be stored externally outside of Australia. But again, from the point of view of university data, most Swinburne, for example, informed consent forms around human data will specify that the data is only going to be stored domestically within Australia because of different countries have very different laws around under what circumstances the government of that country can demand access to your data. If a researcher was generating a data sharing agreement for sharing data with a partner internationally, we'd want them to seriously think about what the solution is in that case, the two broad solutions being either okay in that case you're in the evening encryption data to be stored encrypted outside of Australia in which case you might need to check in with the ethics office to see whether that is sufficiently compatible with your informed consent. And with expectations of the legal systems of those other countries, or you can set up a system whereby the only copy of the data, it will still be stored within Australia, but external parties will be able to access that data, API into it or something like that without storing the local copy outside of Australia, for example. When we are talking about transfer of data, again, a common issue we've found within the research ecosystem is sharing data by email, right, and I think that that's pretty standard across most universities, the downside of that being of course that is not encrypted, which really puts a big hole in your security when you're moving something from one encrypted server to another encrypted server via an entirely unencrypted intermediaries sort of undermines the entire thing. Obviously, that doesn't apply if the files are being manually encrypted using some other system attached to an email, and then being received that's fine but that is not the typical way in which researchers interact with email attachments. So these were our standard encryption options within, within Swinburne, but again, the idea would be that it could be adapted to whatever the standard transfer methods are at different universities. And again, this has already been mentioned, you know, what's the, what's the intention around the destruction of these data that it is pretty common within a university research ecosystem or data to be retained way longer than it's actually intended to be. One of the issues around, you know, within the ethics office side of things is already often we're telling participants that data is going to be destroyed after a set period of time. We're actually enforcing that that data is destroyed 15 years after, after the project is not trivial. And the same goes in this case but at least it's important to flag the intention. And just the standard kind of periods of time that one might expect data to be retained for, including the concept of indefinite retention. Importantly indefinite retention doesn't necessarily mean permanent retention indefinite just means, no, I'm not going to tell you how long because I don't know how long but at some point I assume I'm going to delete it. And a statement that's going to be permanently retained is more in the lines of, you know, talking about open research data and things like that, or data that's going to be important in a patent application where you actually do have to make a commitment but no, no, no. We're going to keep this data actually safe and secure. And permanently archive it. And then the next section is much more in terms of the what is permitted to be done with that data set. So again, something that is common within the research sphere is researchers want to say, look, I'm happy to share my data with you, but only for certain purposes. I don't, this isn't carte blanche to do whatever you want with that data set. This necessarily has to be quite reform. There's so many, you know, potential users right you're not going to have a drop down menu or a tick box options for what's going to be done with this data, but there is at least suggestion as to what sort of things we mean in terms of what sort of derived data sets are you expecting to be using this data for what is the scope of the project what other data sets you're going to be combining this with. And similarly, again, we've talked about, well, what was the retention of the original raw data that we initially shared, but there's typically a large number of derived data sets that come from that data. So it's not really, you know, the spirit of a data sharing agreement right is not that you get to get a whole load of raw data, do some trivial manipulation to create a derived data set. In the organization that's okay I deleted the raw data and then keep your derived data set that sort of circumvent the entire process. So being clear around what we're expecting from derived data sets, because almost invariably, those are going to be retained by at least one party and often by both parties, but within a university ecosystem. It's not uncommon for us to, after they were actually the data that we get from you is going to be combined with certain facets of that data is going to be combined with other data sets we have in house, and derived data sets are going to be used as part of a publication, and as part of our responsibilities around that publication we're going to make that derived data set open access is very important to be clear about that because that can be a very different behavioral expectation compared to a lot of private industry where they. are indicated ahead of time. A lot of organizations outside of the university ecosystem may be very surprised by researcher intentions to be quite so public with they de identified or agglomerated or otherwise derived versions of a data set shared with them. So the next couple of sections of very researcher focused and again typically don't come up in terms of the enterprise data sharing agreements. And this is a little bit like, this is more kind of in common with research collaboration agreements that that some researchers do to kind of. prevent arguments over authorship later on. And so broadly it's talking about what what outputs are expected from this data and who's going to be authors on those research outputs, the sort of thing that it typically isn't relevant to. It's a matter and often isn't thought about from from external industry partners point of view but can be extremely front of mind from a researcher point of view. And then finally yeah we've talked about you talked about this offboarding deletion process, what's going to be done with these research outputs. Again, is the partner expecting oh yeah there will be a research output you are writing a report and you're going to give that report just to us. Because our expectation is very different to. Oh no actually we're going to be making a research output that actually going to be made public, either public and paywall or public and open access. So very occasionally some partnerships have expected that there'll be some sort of research output that's only going to be retained by one of those parties. I think that this is actually extremely rarely done but sometimes it's the expectation that a partner can have so again, like I've said a million times, it's just laying out expectations where possible ahead of time. So the human data section is kind of very specific to their kind of the ethics office side of data sharing agreements and then it's simply the last section is the signature section at the bottom, you know organization position name signature date. And very basic stuff so you can see how this is, you know, everything up until that is very much looking like a, an ethics application for a research project or a research data management plan within the university context, very little in terms of the legal of a data sharing agreement. It becomes a little bit more like that with the, with a reasonably long definitions section just so that everyone's on the same page as to what exactly we're talking about when we say sensitive or we say shared. The only other thing that is relevant in this context is I also put together a little kind of description around the logic of this data sharing agreement so if you're using this as the starting point within your own university organization institute whatever. You can see at least what the thought process was that within went into the way that it currently is. That's going to be useful, more useful for some settings than others but at least it gives an idea of what the thought process was behind it. I'm just going to have to cut in there. We're kind of nearing the end of time so if you've got some just final comments that you'd like to share and then can quickly open it up to see if anyone's got any burning questions for the panel. As you may have guessed from the fact that that's the end of the document that's also the end of the main things I wanted to say so I shall unshare now and open it up to questions in general. That was fantastic Thomas so good to see your template and all the steps that are involved and really good that you've added that commentary at the end of the document to support and how to kind of complete that and I think people will definitely have a look at that template to help support the development of their data sharing agreements. So I just want to open up the floor to the participants if anyone's got any burning questions for for the group. We've taken note of the commentary within chat around kind of areas of interest and areas of need. So any questions anyone would like to ask. I'll ask a question if no one else will. For any and all of the presenters. Have they been approached about AI training or model training for any of their data either the administrative data or, or otherwise. As an archive we have been requesting have many requests coming to us on those grounds and we're not sure that our regular contracts kind of cover that because they're not sharing the information again but they are utilizing the information that is tamed to train their model or train their AI. Kind of on sharing that information. Does that make any sense. So I was wondering if any of the three presenters have had similar and data sharing agreements. I'm happy to briefly comment so I have part of my background is in unsupervised machine learning so I haven't done that much supervised machine learning but broadly speaking. But the, you know when training a large language model for example or some other kind of supervised machine learning the current trend is to call it AI but it's kind of, it depends on the exact technique, or any other sort of neural network. I would say that the, the neural network that you end up with is a derived data set. So that's the sort of thing where you would want to be clear as to the methodology but the derived data set and how it's going to be used as the sort of thing that the original participants should be aware of because a lot of those sorts of machine learning models. You can't extract out of them the exact raw data but you can extract out significant aspects of that data. I can add that we've had a couple of data sharing agreements in the teaching and admin space that have been not exactly using AI but say scanning metadata or scanning IP addresses or that type of information. And certainly have been putting data sharing agreements in place because it's Thomas has said it's about who's using the data, what are they using it for and what's the output. So we have been putting those data sharing agreements in place for those types of scenarios. David you've got your hand up. Yes, thank you. Thanks Thomas that was a very detailed document. I saw there was a reference to authorship, whether authorship of a publication or document was part of sharing agreement. But if I remember well in the code for responsible conduct of research, only providing data is not enough to be an offer. Yeah, agreed. And so that's one of the things where I think that sort of expectation needs to be laid out ahead of time. Occasionally it is the case that as part of data sharing agreement there's also the expectation to share interpretation expertise it's not just the data, it's we're giving you the data so that you could see it and we will be collaborating on this. Okay, yeah. I think we're coming to time now so I would just like to thank the speakers for the time they've given to present today during this session. It was really informative really inspiring I would say I've learned a lot myself. I see a lot of various that I would like to kind of work on further to within the ARDC to support the universities and organizations with the concept of data sharing agreements. And it's been great to be able to kind of share the areas of interest and the work that people have been doing here. And this finally I just want to apologize about the technical difficulties at the start of this, sometimes zoom likes to have a mind of its own. So thank you once again everyone for coming along and look out for sessions in the future with regards this sort of information. Thank you again.