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I recently read Francesca Polletta‘s book It was like a fever: Storytelling in protest and politics (2006, University of Chicago Press).

I recommend it! It will appeal to researchers interested in topics such as narrative, strategic communication, (narrative) argumentation, or epistemology (here, of narrative). Parts may also interest activists.

The book’s case studies are drawn from the Student Nonviolent Coordinating Committee (SNCC) (Chapters 2 & 3); online deliberation about the 9/11 memorial (Listening to the City, summer 2002) (Chapter 4); women’s stories in law (including, powerfully, battered women who had killed their abusers, and the challenges in making their stories understandable) (Chapter 5); references to Martin Luther King by African American Congressmen (in the Congressional Record) and by “leading back political figures who were not serving as elected or appointed officials” (Chapter 6). Several are extended from work Polletta previously published from 1998 through 2005 (see page xiii for citations).

The conclusion—”Conclusion: Folk Wisdom and Scholarly Tales” (pages 166-187)—takes up several topics, starting with canonicity, interpretability, ambivalence. I especially plan to go back to the last two sections: “Scholars Telling Stories” (pages 179-184)—about narrative and storytelling in analysts’ telling of events—and “Towards a Sociology of Discursive Forms” (pages 185-187)—about investigating the beliefs and conventions of narrative and its institutional conventions (and relating those to conventions of other “discursive forms” such as interviews). These set forward a research agenda likely useful to other scholars interested in digging in further. These are foreshadowed a bit in the introduction (“Why Stories Matter”) which, among other things, sets out the goal of developing “A Sociology of Storytelling”.

A few quotes I noted—may give you the flavor of the book:

page 141: “But telling stories also carries risks. People with unfamiliar experiences have found those experiences assimilated to canonical plot lines and misheard as a result. Conventional expectations about how stories work, when they are true, and when they are appropriate have also operated to diminish the impact of otherwise potent political stories. For the abused women whom juries disbelieved because their stories had changed in small details since their first traumatized [p142] call to police, storytelling has not been especially effective. Nor was it effective for the citizen forum participants who did not say what it was like to search fruitlessly for affordable housing because discussions of housing were seen as the wrong place in which to tell stories.”

pages 166-167: “So which is it? Is narrative fundamentally subversive or hegemonic? Both. As a rhetorical form, narrative is equipped to puncture reigning verities and to uphold them. At times, it seems as if most of the stories in circulation are subtly or not so subtly defying authorities; at others as if the most effective storytelling is done by authorities. To make it more complicated, sometimes authorities unintentionally undercut their own authority when they tell stories. And even more paradoxically, undercutting their authority by way of a titillating but politically inconsequential story may actually strengthen it. Dissenters, for their part, may find their stories misread in ways that support the very institutions that are challenging….”For those interested in the relations between storytelling, protest, and politics, this all suggests two analytical tasks. One is to identify the features of narrative that allow it to [p167] achieve certain rhetorical effects. The other is to identify the social conditions in which those rhetorical effects are likely to be politically consequential. The surprise is that scholars of political processes have devoted so little attention to either task.”

pages 177-8 – “So institutional conventions of storytelling influence what people can do strategically with stories. In the previously pages, I have described the narrative conventions that operate in legal adjudication, media reporting, television talk shows, congressional debate, and public deliberation. Sociolinguists have documented such conventions in other settings: in medical intake interviews, for example, parole hearings, and jury deliberations. One could certainly generate a catalogue of the institutional conventions of storytelling. To some extent, those conventions reflect the peculiarities of the institution as it has developed historically. They also serve practical functions; some explicit, others less so. I have argued that the lines institutions draw between suitable and unsuitable occasions for storytelling or for certain kinds of stories serve to legitimate the institution.” [specific examples follow] ….”As these examples suggest, while institutions have different conventions of storytelling, storytelling does some of the same work in many institutions. It does so because of broadly shared assumptions about narrative’s epistemological status. Stories are generally thought to be more affecting by less authoritative than analysis, in part because narrative is associated with women rather than men, the private sphere rather than the public one, and custom rather than law. Of course, conventions of storytelling and the symbolic associations behind them are neither unitary nor fixed. Nor are they likely to be uniformly advantageous for those in power and disadvantageous for those without it. Narrative’s alignment [179] along the oppositions I noted is complex. For example, as I showed in chapter 5, Americans’ skepticism of expert authority gives those telling stories clout. In other words, we may contrast science with folklore (with science seen as much more credible), but we may also contrast it with common sense (with science seen as less credible). Contrary to the lamentation of some media critics and activists, when disadvantaged groups have told personal stories to the press and on television talk shows, they have been able to draw attention not only to their own victimization but to the social forces responsible for it.“

I am not aware of a consensus definition of knowledge graph. I’ve been discussing this for awhile with Liliana Giusti Serra, and the topic came up again with my fellow organizers of the knowledge graph session at US2TS as we prepare for a panel.

I’ve proposed the following main features:

• RDF-compatible, has a defined schema (usually an OWL ontology)
• items are linked internally
• may be a private enterprise dataset (e.g. not necessarily openly available for external linking) or publicly available
• covers one or more domains

Below are some quotes.

I’d be curious to hear of other definitions, especially if you think there’s a consensus definition I’m just not aware of.

“A knowledge graph consists of a set of interconnected typed entities and their attributes.”

by the aid of symbolism, we can make transitions in reasoning almost mechanically by the eye which would otherwise call into play the higher faculties of the brain.

…Civilization advances by extending the number of important operations that we can perform without thinking about them. Operations of thought are like cavalry charges in a battle — they are strictly limited in number, they require fresh horses, and must only be made at decisive moments.

One very important property for symbolism to possess is that it should be concise, so as to be visible at one glance of the eye and be rapidly written.

– Whitehead, A.N. (1911). An introduction to mathematics, Chapter 5, “The Symbolism of Mathematics” (page 61 in this version)
HT to Santiago Nuñez-Corrales (Illinois page for Santiago Nuñez-Corrales, LinkedIn for Santiago Núñez-Corrales) who used part of this quote in a Conceptual Foundations Group talk, Nov 29.

From my point of view, this is why memorizing multiplication tables is not now irrelevant; why new words for concepts are important; and underlies a lot of scientific advancement.

Sally Jackson explicates the notion of the “disagreement space” in a new Topoi article:

“a position that remains in doubt remains in need of defense” ((p 12, Sally Jackson. Reason-Giving and the Natural Normativity of Argumentation. Topoi. 2018 Online First. http://doi.org/10.1007/s11245-018-9553-5))

“The most important theoretical consequence of seeing argumentation as a system for management of disagreement is a reversal of perspective on what arguments accomplish. Are arguments the means by which conclusions are built up from established premises? Or are they the means by which participants drill down from disagreements to locate how it is that they and others have arrived at incompatible positions? A view of argumentation as a process of drilling down from disagreements suggests that arguers themselves do not simply point to the reasons they hold for a particular standpoint, but sometimes discover where their own beliefs come from, under questioning by others who do not share their beliefs. A logical analysis of another’s argument nearly always involves first making the argument more explicit, attributing more to the author than was actually said. This is a familiar enough problem for analysts; my point is that it is also a pervasive problem for participants, who may feel intuitively that something is seriously wrong in what someone else has said but need a way to pinpoint exactly what. Getting beliefs externalized is not a precondition for argument, but one of its possible outcomes.” ((p 10, Sally Jackson. Reason-Giving and the Natural Normativity of Argumentation. Topoi. 2018 Online First. http://doi.org/10.1007/s11245-018-9553-5))

From Sally Jackson’s Reason-Giving and the Natural Normativity of Argumentation. ((Sally Jackson. Reason-Giving and the Natural Normativity of Argumentation. Topoi. 2018 Online First. http://doi.org/10.1007/s11245-018-9553-5))

The original treatment of disagreement space is cited to a book chapter revising an ISSA 1992 paper ((Jackson S (1992) “Virtual standpoints” and the pragmatics of conversational argument. In: van Eemeren FH, Grootendorst R, Blair JA, Willard CA (eds) Argument illuminated. International Centre for the Study of Argumentation, Amsterdam, pp. 260–226)), somewhat harder to get one’s hands on.

…language does do much of our thinking for us, even in the sciences, and rather than being an unfortunate contamination, its influence has been productive historically, helping individual thinkers generate concepts and theories that can then be put to the test. The case made here for the constitutive power of figures [of speech] per se supports the general point made by F.L. Holmes in a lecture addressed to the History of Science Society in 1987. A distinguished historian of medicine and chemistry, Holmes based his study of Antoine Lavoisier on the French chemist’s laboratory notebooks. He later examined drafts of Lavoisier’s published papers and discovered that Lavoisier wrote many versions of his papers and in the course of careful revisions gradually worked out the positions he eventually made public (Holmes, 221). Holmes, whose goal as a historian is to reconstruct the careful pathways and fine structure of scientific insights, concluded from his study of Lavoisier’s drafts

We cannot always tell whether a thought that led him to modify a passage, recast an argument, or develop an alternative interpretation occurred while he was still engaged in writing what he subsequently altered, or immediately afterward, or after some interval during which he occupied himself with something else; but the timing is, I believe, less significant than the fact that the new developments were consequences of the effort to express ideas and marshall supporting information on paper (225).

– page xi of Rhetorical Figures in Science by Jeanne Fahnestock, Oxford University Press, 1999.

She is quoting Frederich L. Holmes. 1987. Scientific writing and scientific discovery. Isis 78:220-235. DOI:10.1086/354391

As Moore summarizes,

Lavoisier wrote at least six drafts of the paper over a period of at least six months. However, his theory of respiration did not appear until the fifth draft. Clearly, Lavoisier’s writing helped him refine and understand his ideas.

Moore, Randy. Language—A Force that Shapes Science. Journal of College Science Teaching 28.6 (1999): 366. http://www.jstor.org/stable/42990615
(which I quoted in a review I wrote recently)

Fahnestock adds:
“…Holmes’s general point [is that] there are subtle interactions ‘between writing, thought, and operations in creative scientific activity’ (226).”

Today I am at the Health Data Analytics summit. The title of the keynote talk is Achieving Care transformation by Infusing Electronic Health Records with Wisdom. It’s a delight to hear from a medical informaticist: David M. Liebovitz (publications in Google Scholar), MD, FACP, Chief Medical Information Officer, The University of Chicago. He graduated from University of Illinois in electrical engineering, making this a timely talk as the engineering-focused Carle Illinois College of Medicine gets going.

David Liebovitz started with a discussion of the data problems — problem lists, medication lists, family history, rules, results, notes — which will be familiar to anyone using EHRs or working with EHR data. He draws attention also to the human problems — both in terms of provider “readiness” (e.g. their vision for population-level health) as well as about “current expectations”. (An example of such an expectation is a “main clinician satisfier” he closed with: U Chicago is about to turn on outbound faxing from the EHR!) He mentioned also the importance of resilience.

He mentioned customizing systems as a risk when the vendor makes upstream changes (this is not unique to healthcare but a threat to innovation and experimentation with information systems in other industries.) Still, in managing the EHR, there is continual optimization, scored based on a number of factors. He mentioned:

• Safety
• Quality/patient experience
• Regulatory/legal
• Financial
• Usability/productivity
• Availability of alternative solutions

As well as weighting for old requests.

He emphasized the complexity of healthcare in several ways:

• “Nobody knew that healthcare could be so complicated.” – POTUS
• Showing the Medicare readmissions adjustment factors
• Pharmacy pricing, an image (showing kickbacks among other things) from “Prices That Are Too High”, Chapter 5, The Healthcare Imperative: Lowering Costs and Improving Outcomes: Workshop Series Summary (2010)  National Academies Press doi:10.17226/12750

An image from “Prices That Are Too High”, Chapter 5, The Healthcare Imperative: Lowering Costs and Improving Outcomes: Workshop Series Summary (2010)

• Icosystem’s diagram of the complexity of the healthcare system

Icosystem – complexity of the healthcare system

• Another complexity is the modest impact of medical care compared to other factors
  • such as the impact of socioeconomic and political context on equity in health and well-being (see the WHO image below).
  • For instance, there is a large impact of health behaviors, which “happen in larger social contexts.” (See the Relative Contribution of Multiple Determinants to Health, August 21, 2014, Health Policy Briefs)

Solar O, Irwin A. A conceptual framework for action on the social determinants of health. Social Determinants of Health Discussion Paper 2 (Policy and Practice).

Given this complexity, David Liebovitz stresses that we need to start with the right model, “simultaneously improving population health, improving the patient experience of care, and reducing per capita cost”. (See Stiefel M, Nolan K. A Guide to Measuring the Triple Aim: Population Health, Experience of Care, and Per Capita Cost. IHI Innovation Series white paper. Cambridge, Massachusetts: Institute for Healthcare Improvement; 2012).

Table 1 from Stiefel M, Nolan K. A Guide to Measuring the Triple Aim: Population Health, Experience of Care, and Per Capita Cost. IHI Innovation Series white paper. Cambridge, Massachusetts: Institute for Healthcare Improvement; 2012.

Given the modest impact of medical care, and of data, he suggests that we should choose the right outcomes.

David Liebovitz says that “not enough attention has been paid to usability”; I completely agree and suggest that information scientists, human factors engineeers, and cognitive ergonomists help mainstream medical informaticists fill this gap. He put up Jakob Nielsen’s 10 usability heuristics for user interface design A vivid example is whether a patient’s resuscitation preferences are shown (which seems to depend on the particular EHR screen): the system doesn’t highlight where we are in the system. For providers, he says user control and freedom are very important. He suggests that there are only a few key tasks. A provider should be able to do ANY of these things wherever they are in the chart:

• put a note
• order something
• send a message

Similarly, EHR should support recognition (“how do I admit a patient again?”) rather than requiring recall.

Meanwhile, on the decision support side he highlights the (well-known) problems around interruptions by saying that speed is everything and changing direction is much easier than stopping. Here he draws on some of his own work, describing what he calls a “diagnostic process aware workflow”

David Liebovitz. Next steps for electronic health records to improve the diagnostic process. Diagnosis 2015 2(2) 111-116. doi:10.1515/dx-2014-0070

Can we predict X better? Yes, he says (for instance pointing to Table 3 of “Can machine-learning improve cardiovascular risk prediction using routine clinical data?” and its machine learning analysis of over 300,000 patients, based on variables chosen from previous guidelines and expert-informed selection–generating further support for aspects such as aloneness, access to resources, socio-economic status). But what’s really needed, he says, is to:

• Predict the best next medical step, iteratively
• Predict the best next lifestyle step, iteratively
• (And what to do about genes and epigenetic measures?)

He shows an image of “All of our planes in the air” from flightaware, drawing the analogy that we want to work on “optimal patient trajectories” — predicting what are the “turbulent events” to avoid”. This is not without challenges. He points to three:

• Data privacy (He suggests Google DeepMind and healthcare in an age of algorithms. Powles, J. & Hodson, H. Health Technol. (2017). doi:10.1007/s12553-017-0179-1
• Two sorts of mismatches between the current situation and where we want to go:
  • For instance the source of data being from finance
  • Certain basic current clinician needs  (e.g. that a main clinician satisfier is that UChicago is soon to turn on outbound faxing from their EHR — and that an ongoing source of dissatisfaction: managing volume of inbound faxes.)

He closes suggesting that we:

• Finish the basics
• Address key slices of the spectrum
• Descriptive/prescriptive
• Begin the prescriptive journey: impact one trajectory at a time.

Here is a glimpse into scholarly communication 20 years ago, from a paper about Alzforum, the Alzheimer Research Forum website. “In July of 1996, the website made its debut at the International Conference on Alzheimer’s Disease and Related Disorders in Osaka, Japan.” ((page 458, Kinoshita, June, and Gabrielle Strobel. “Alzheimer Research Forum: a knowledge base and e-community for AD research.” in Alzheimer: 100 Years and Beyond, Mathias Jucker, Konrad Beyreuther, Christian Haass, Roger M. Nitsch, Yves Christen, eds. Berlin Heidelberg:Springer-Verlag, 2006: 457-463.))

Having established a foothold in cyberspace, the challenge for Alzforum was and continues to be to define new types of scientific publishing that take advantage of the speed and wide distribution of the Web and to curate and add value to information available from other public sources. This is a perennial challenge, thanks to the rapid advances in biomedical resources on the Web.

This uphill struggle, however, seems less strenuous when we compare the current situation with the “old days.” Recall that in 1996, PubMed did not exist! (PubMed was launched in June of 1997.) Medical institutions had access to Medline, but in order for Alzforum to produce its Papers of the Week listings, the editor had to ask the Countway Medical Library at Harvard Medical School to provide weekly text files listing newly indexed AD papers. The Alzforum hired a curator to paraphrase each abstract so that this information could be posted without violating journal copyrights. These documents were manually edited, sent out in a weekly email to the advisors for comments, and compiled into a static HTML page. Looking back, we can see that the entire process seems as antiquated as the hand-copying of manuscripts in the Middle Ages.

(emphasis mine)

From pages 459-460 of “Alzheimer Research Forum: a knowledge base and e-community for AD research” ((Kinoshita, June, and Gabrielle Strobel. “Alzheimer Research Forum: a knowledge base and e-community for AD research.” in Alzheimer: 100 Years and Beyond, Mathias Jucker, Konrad Beyreuther, Christian Haass, Roger M. Nitsch, Yves Christen, eds. Berlin Heidelberg:Springer-Verlag, 2006: 457-463.))

I sent off my revised abstract to ECA Lisbon 2015, the European Conference on Argumentation. Evidence informatics, in 75 words:

Reasoning and decision-making are common throughout human activity. Increasingly, human reasoning is mediated by information technology, either to support collective action at a distance, or to support individual decision-making and sense-making.

We will describe the nascent field of “evidence informatics”, which considers how to structure reasoning and evidence. Comparing and contrasting evidence support tools in different disciplines will help determine reusable underlying principles, shared between fields such as legal informatics, evidence-based policy, and cognitive ergonomics.

A genre comprises a class of communicative events, the members of which share some set of communicative purposes. These purposes are recognized by the expert members of the parent discourse community and thereby constitute the rationale for the genre. This rationale shapes the schematic structure of the discourse and influences and constrains choice of content and style. Communicative purpose is both a privileged criterion and one that operates to keep the scope of a genre as here conceived narrowly focused on comparable rhetorical action. In addition to purpose, exemplars of a genre exhibit various patterns of similarity in terms of structure, style, content and intended audience. If all high probability expectations are realized, the exemplar will be viewed as prototypical by the parent discourse community. The genre names inherited and produced by discourse communities and imported by others constitute valuable ethnographic communication, but typically need further validation. ((Genre defined, from John M. Swales, page 58, Chapter 3 “The concept of genre” in Genre Analysis: English in academic and research settings. Cambridge University Press 1990. Reprinted with other selections in
The Discourse Studies Reader: Main currents in theory and analysis (see pages 305-316).))

Today I’m presenting a talk in the ISWC 2014 Workshop on Linked Science 2014—Making Sense Out of Data (LISC2014). The LISC2014 paper is joint work with Paolo Ciccarese, Tim Clark and Richard D. Boyce. Our goal is to make the evidence in a scientific knowledge base easier to access and audit — to make the knowledge base easier to maintain as scientific knowledge and drug safety regulations change. We are modeling evidence (data, methods, materials) from biomedical communications in the medication safety domain (drug-drug interactions).

The new architecture for the drug-drug interaction knowledge base is based on:

• the new, best-in-class argumentation ontology for scientific publishing, the Micropublication Ontology,described in Tim, Paolo, and Carole Goble‘s Journal of Biomedical Semantics article in July 2014 (doi:10.1186/2041-1480-5-28); or see the ontology itself)
• the Open Annotation Data Model for linking quotes (in our case to link claims, data, methods, and materials in Micropublications directly to the source text in biomedical papers and drug labels)
• the Drug Interaction Knowledge Base (DIKB) an existing, hand-constructed knowledge base of evidence about drug-drug interactions, including its evidence taxonomy

This is part of a 4-year National Library of Medicine project, “Addressing gaps in clinically useful evidence on drug-drug interactions” (1R01LM011838-01)

Abstract of our paper, “Using the Micropublications ontology and the Open Annotation Data Model to represent evidence within a drug-drug interaction knowledge base.”:

Semantic web technologies can support the rapid and transparent validation of scientific claims by interconnecting the assumptions and evidence used to support or challenge assertions. One important application domain is medication safety, where more efficient acquisition, representation, and synthesis of evidence about potential drug-drug interactions is needed. Exposure to potential drug-drug interactions (PDDIs), defined as two or more drugs for which an interaction is known to be possible, is a significant source of preventable drug-related harm. The combination of poor quality evidence on PDDIs, and a general lack of PDDI knowledge by prescribers, results in many thousands of preventable medication errors each year. While many sources of PDDI evidence exist to help improve prescriber knowledge, they are not concordant in their coverage, accuracy, and agreement. The goal of this project is to research and develop core components of a new model that supports more efficient acquisition, representation, and synthesis of evidence about potential drug-drug interactions. Two Semantic Web models—the Micropublications Ontology and the Open Annotation Data Model—have great potential to provide linkages from PDDI assertions to their supporting evidence: statements in source documents that mention data, materials, and methods. In this paper, we describe the context and goals of our work, propose competency questions for a dynamic PDDI evidence base, outline our new knowledge representation model for PDDIs, and discuss the challenges and potential of our approach.

Citation: Schneider, Jodi, Paolo Ciccarese, Tim Clark, and Richard D. Boyce. “Using the Micropublications ontology and the Open Annotation Data Model to represent evidence within a drug-drug interaction knowledge base.” Linked Science 2014 at ISWC 2014.