Open policy ontology

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The open policy ontology describes the information structures that are needed to document shared understanding of a complex decision situation.

Question

What information structures and information tools are needed to document shared understanding in such a way that

it can be operationalised and managed and used for automatic inferences by a computer,
it can systematically organise information objects used in open assessment, such as variables and statements,
it can represent each participant's views systematically as a part of the whole even if people disagree,
it is intuitive enough to be used by non-experts?

Answer

Shared understanding aims at producing a description of different views, opinions, and facts related to a specific topic such as a decision process. The open policy ontology describes the information structures that are needed to document shared understanding of a complex decision situation. The purpose of the structure is to help people identify hidden premises, beliefs, and values and explicate possible discrepancies. This is expected to produce better understanding among participants.

The basic structure of a shared understanding is a network of items and relations between them. This network uses Resource description framework, which is an ontology standard used to describe many Internet contents. Items and relations (aka properties) are collectively called things. Each item is typically of one of the types mentioned below. This information is documented using property instance of (e.g. Goherr assessment is instance of assessment).

Different item types have different levels of standardisation and internal structure. For example, variables are web pages that always have headings question, answer and rationale, and the information is organised under those headings. Some other items describe e.g. statements that are free-text descriptions about how a particular thing is or should be (according to a participant), and yet some others are publications. A common feature is that all items contain information that is relevant for a decision.

In the open policy ontology, each item may have lengthy texts, graphs, analyses or even models inside them. However, the focus here is on how the items are related to each other. The actual content is often referred to as one key sentence only (description). Each item also has a unique identifier URI that is used for automatic handling of data. Voting age is an example discussion and shows a structured description in table format.

**Open policy ontology**
Items (information objects)	Properties (relations)
Assessment. Assessment has parts Scope, Answer and Rationale. Scope has part Decisions and scenarios. Decision may be used independently. Rationale has part Stakeholder. It may be used independently. Variable has parts Question, Answer and Rationale. The Question of a variable may be called Topic and used independently. Topic may also be objective. Method has parts Question, Answer and Rationale. Discussion. Discussion has parts Statement, Resolution and Argumentation. Statement has subclasses Value statement, Fact statement. Statement may be used independently. Action. Action has parts Who, When, What. Action has subclass Decision. It may be used without applying internal structure. Publication	set theoretical (instance of, subclass of, has context) logical (if - then, and, or, not,... ) causal (affects, increases, decreases, prevents) referential (makes relevant; associates to; has reference, tag, category) evaluative (has truthlikeness, value, popularity, finds important) argumentative (attack, defend, comment) topical where the object is always a decision (substance of, decision process of, task of, method of, stakeholder of, irrelevant to)

Rationale

Item types

This ontology is specifically about decision making, and therefore actions (and decisions to act) are handled explicitly. However, any natural, social, ethical or other phenomena may relate to a decision and therefore the vocabulary has to be very generic. When we descbribe actions under planning, those descriptions are called "Decision processes", while all other descriptions are called "Substance".

The properties described below are used in the following kind of sentences: "Information X describes Y of decision Z" where X is a particular piece of information that describes a phenomenon, Y is the topical information area that is described, and Z is a particular decision.

Substance (information about a substantive topic or phenomenon itself): What issues relate to a decision Z? What causal connections exist between issues? What scientific knowledge exist about the issues? What actions can be chosen? What are the impacts of these actions? What are the objectives and how can they be reached? What values and preferences exist?
Decision process (information about how a decision Z will be made): What will be decided? When will it be decided? Who has the authority to decide? Who are involved? How is the decision prepared? What political realities and restrictions exist?
Tasks (information about organising the information work to support decision making): What tasks are needed to collect and organise the information? When do these tasks need to be done? Who is responsible of what? How is information work organised? Tasks are also important afterwards to distribute merit and evaluate the process: Who did what? How did information evolve? Where did data come from?
Methods (information about methods used in the information work): How to perform information work? What methods are available for a task? How to participate in the work? How to use statistical and other methods and tools?
Stakeholders (information about stakeholders and decision makers in the information work): Who participates? Who should participate? Who has necessary skills for contributing? How to motivate participation? How to measure merit of contributions?
Irrelevant issues: Information that do not fall into any of the previous categories is thus irrelevant for a particular decision Z. If there is no identified relation between an information object and a decision, it implies that the information object is irrelevant. However, because not all relevant relations have been considered and documented, it is often useful to explicate the irrelevance, especially if people may (falsely) think that it is relevant.

Item types(-)
Obs	Class	English name	Finnish name	Description
1	resource	item	asia	Relevant pieces of information related policy making. Sometimes also refers to the real-life things that the information is about. Items are shown as nodes in insight networks.
2	resource	relation	relaatio	Information about how items are connected to each other. Relations are shown as edges in insight networks.
3	item	substance	substanssi	Items about a substantive topic or phenomenon itself: What issues relate to a decision? What causal connections exist between issues? What scientific knowledge exist about the issues? What actions can be chosen? What are the impacts of these actions? What are the objectives and how can they be reached? What values and preferences exist?
4	item	stakeholder	sidosryhmä	Items about people or organisations who have a particular role in a policy process, either as actors or targets of impacts: Who participates in a policy process? Who should participate? Who has necessary skills for contributing? Who has the authority to decide? Who is affected by a decision?
5	item	process	prosessi	Items about doing or happening in relation with a topic, especially information about how a decision will be made): What will be decided? When will it be decided? How is the decision prepared? What political realities and restrictions exist?
6	item	method	metodi	Items about how to deal with information related to a topic: How to perform information work? What methods are available for a task? How to participate in a decision process? How to use statistical and other methods and tools? How to motivate participation? How to measure merit of contributions?
7	item	action	toiminta	Items about organising decision support, decision making, implementation, and evaluation: What tasks are needed to collect and organise necessary information? When do these tasks need to be done? Who is responsible of what? How is information work organised? Tasks are also important afterwards to distribute merit and evaluate the process: Who did what? How did information evolve? Where did data come from?
8	relation	causal link	syylinkki	The subject has causal effect on the object (or vice versa in the case of an inverse relation)
9	causal link	negative causal link	negatiivinen syylinkki	The subject reduces or diminishes the object.
10	causal link	positive causal link	positiivinen syylinkki	The subject increases or enhances the object.
11	relation	participatory link	osallisuuslinkki	The subject is a stakeholder that has a particular role related to the object
12	relation	operational link	toimintolinkki	The subject has some kind of practical relation to the object (a fairly wide class)
13	relation	evaluative link	arvostuslinkki	The subject shows preference of relevance about the object
14	relation	referential link	viitelinkki	The subject is used as a reference of a kind for the object
15	relation	argumentative link	argumenttilinkki
16	operational link	logical link	looginen linkki
17	item	information object	tieto-olio	A specified structure containing information about substance, stakeholders, processes, methods, or actions.
18	information object	knowledge crystal	tietokide	information object with a standardised structure and contribution rules
19	knowledge crystal	assessment	arviointi	Describes a decision situation and typically provides relevant information to decision makers before the decision is made (or sometimes after the decision about its implementation or success). It is mostly about the knowledge work, i.e. tasks for decision support.
20	knowledge crystal	variable	muuttuja	Describes a real-world topic that is relevant for the decision situation. It is about the substance of the topic.
21	knowledge crystal	method	metodi	Describes how information should be managed or analysed so that it will answer the policy-relevant questions asked. It is about methods.
22	information object	discussion part	keskustelun osa	Information object that is used to organise discussions into a specified structure. The purpose of the structure is to help validation of statements and facilitate machine learning.
23	discussion part	discussion	keskustelu	Discussion, or structured argumentation, describes arguments about a particular statement and a synthesis about an acceptable statement. In a way, discussion is (a documentation of) a process of analysing the validity of a statement.
24	discussion	fact discussion	faktakeskustelu	Discussion that can be resolved based on scientific knowledge.
25	discussion	value discussion	arvokeskustelu	Discussion that can be resolved based on ethical knowledge.
26	discussion part	statement	väite	Proposition claiming that something is true or ethically good. A statement may be developed in a discussion by adding and organising related argumentation (according to pragma-dialectics), or by organising premises and inference rules (according to Perelman).
27	statement	value statement	arvoväite	Proposition claiming that something is ethically good, better than something else, prioritised over something, or how things should be.
28	statement	fact statement	faktaväite	Proposition claiming how things are or that something is true.
29	value statement	true value statement	tosi arvoväite	A statement that has not been successfully invalidated.
30	value statement	false value statement	epätosi arvoväite	A statement that has been successfully invalidated.
31	fact statement	true fact statement	tosi faktaväite
32	fact statement	false fact statement	epätosi faktaväite
33	statement	true statement	tosi väite
34	statement	false statement	epätosi väite
35	statement	opening statement	avausväite	A statement that is the basis for a structured discussion, a priori statement.
36	statement	closing statement	lopetusväite	A statement that is the resolution of a structured discussion, a posteriori statement. Closing statement becomes an opening statement when the discussion is opened again.
37	opening statement	fact opening statement	avausfaktaväite
38	closing statement	fact closing statement	lopetusfaktaväite
39	opening statement	value opening statement	avausarvoväite
40	closing statement	value closing stetement	lopetusarvoväite
41	discussion part	argument	argumentti	A statement that has also contains a relation to its target as an integral part. Due to this relation, arguments appear inside discussions and target directly or indirectly the opening statement.
42	relation	argumentative link	argumenttilinkki
43	argumentative link	comment	kommentti	The subject comments the object but does not change its validity DO WE NEED THESE?
44	argumentative link	defend	puolustus	The subject defends the validity of the object.
45	argumentative link	attack	hyökkäys	The subject attacks the validity of the object.
46	argumentative link	relevant argument	relevantti argumentti	An argument that it is relevant in its context and therefore may have an effect on its child (if it is also true).
47	argumentative link	irrelevant argument	epärelevantti argumentti	An argument that does not have an effect on its child because it is irrelevant in its context.
48	information object	knowledge crystal part	tietokideosa
49	knowledge crystal part	question	kysymys	A research question asked in a knowledge crystal. The purpose of a knowledge crystal is to answer the question.
50	knowledge crystal part	answer	vastaus	An answer or set of answers to the question of a knowledge crystal, based on any relevant information and inference rules.
51	knowledge crystal part	rationale	perustelut	Any data, discussions, calculations or other information needed to convince a critical rational reader that the answer of a knowledge crystal is good.
52	knowledge cryatal part	result	tulos	The actual, often numerical result to the question, conditional on relevant indices.
53	knowledge crystal part	index	indeksi	A list of possible values for a property. Typically used in describing the result of an ovariable.
54	knowledge crystal part	ovariable	ovariable	A practical implementation of a knowledge crystal in modelling code. Ovariable takes in relevant information about data and dependencies and calculates the result. Typically implemented in R using OpasnetUtils package and ovariable object type.
55	ovariable	key ovariable	avainovariable	An ovariable that is shown on an insight network even if some parts are hidden due to practical reasons.
56	information object	publication	julkaisu	Any published report, book, web page or similar permanent piece of information that can be unambiguously referenced.
57	information object	topic	aihe	A description of an area of interest. It defines boundaries of a content rather than defines the content itself, which is done by statements. When the information structure is improved, a topic often develops into a question of a variable, while a statement develops into an answer of a variable.
58	information object	decision	päätös	Describes a particular event where a decision maker chooses among defined alternatives. This may also be a part of an assessment under heading Decisions and scenarios.
59	information object	objective	tavoite	A desired outcome of a decision. In shared understanding description, it is a topic (or variable) that has value statements attached to it.
60	substance	risk factor	riskitekijä
61	substance	indicator	indikaattori	Piece of information that describes a particular substantive item in a practical and often standard way.
62	indicator	risk indicator	riski-indikaattori	Indicator about (health) risk or outcome
63	indicator	effectiveness indicator	vaikuttavuusindikaattori	Indicator about effectiveness of an action
64	indicator	operational indicator	toimintaindikaattori	Indicator about amount of actions taken
65	information object	data	tietoaineisto
66	work	data work	tietotyö
67	work	data use	tiedon käyttö
68	substance	priority	prioriteetti
69	substance	value judgement	arvovalinta	This is depreciated. Use value statement instead.
70	substance	expense	kustannus
71	substance	health impact	terveysvaikutus
72	stakeholder	agent	toimija
73	stakeholder	social and health organsation	sote-organisaatio
74	stakeholder	ministry	ministeriö
75	stakeholder	expert organisation	asiantuntijalaitos
76	stakeholder	administrative organisation	hallinto-organisaatio
77	process	action	toiminta	Action is a generic term for taking actions to produce information for a decision, make a decision, or implement it. It may have parts Who, What and When, but its internal information structure has not been standardised.
78	action	task	toimenpide	action to be taken when the option has been selected
79	action	decision	päätös	action to be taken when the option is yet to be selected
80	action	work	työ	continuous actions of the same kind and typically independent of the decision at hand. If the decision changes work routines, the action to make this change happen is called task.
81	work	prevention	ennaltaehkäisy	trying to prevent something
82	work	treatment	hoito	trying to fix something when something has already happened
83	work	support	tuki	work that aids in the completion of the selected option, in whatever way
84	task	task 1	toimenpide 1	Numbering is used to differentiate different sources of tasks in insight networks, e.g. tasks that come from different policies.
85	task	task 2	toimenpide 2
86	task	task 3	toimenpide 3
87	task	task 4	toimenpide 4
88	task	task 5	toimenpide 5
89	knowledge crystal	assessment	arviointi
90	knowledge crystal	method	metodi
91	method	analysis	analyysi
92	method	reporting	raportointi
93	method	measurement	mittaus
94	information object	study	tutkimus
95	method	procedure	toimintamalli
96	method	principle	periaate
97	objective	expense objective	kustannustavoite

arg6195: . tehtäväkokonaisuus, osiotyyppi, HNH2035-toimenpide, JHS-luokka ovat vain olioita jotka kytkeytyvät asioihin relaatiolla has index. --Jouni (talk) 05:24, 3 November 2018 (UTC) (type: truth; paradigms: science: relevant attack)

Relation types

Relation types(-)
Obs	Class	English name	Finnish name	English inverse	Finnish inverse	Description
1	negative causal link	decreases	vähentää	is decreased by	vähentyy	VAI: VÄHENTÄJÄNÄ, LISÄÄJÄNÄ JNE?
2	positive causal link	increases	lisää	is increased by	lisääntyy
3	negative causal link	worsens	huonontaa	is worsened by	huonontuu
4	positive causal link	improves	parantaa	is improved by	parantuu
5	negative causal link	prevents	estää	is prevented by	estyy
6	positive causal link	enhances	edistää	is enhanced by	edistyy
7	negative causal link	impairs	heikentää	is impaired by	heikentyy
8	positive causal link	sustains	ylläpitää	is sustained by	ylläpitäytyy
9	causal link	affects	vaikuttaa	is affected by	vaikuttuu
10	causal link	indirectly affects	vaikuttaa epäsuorasti	indirectly affected by	vaikuttuu epäsuorasti
11	causal link	cause of	syy	caused by	johtuu	Wikidata property P1542
12	causal link	immediate cause of	välitön syy	immediately caused by	johtuu välittömästi	Wikidata property P1536
13	causal link	prevents	estää	prevented by	estyy
14	causal link	contributing factor of	vaikuttava tekijä			Wikidata property P1537
15	participatory link	performs	toteuttaa	performer	toteuttajana	who does a task?
16	participatory link	decides	päättää	decider	päätäjänä
17	participatory link	asks	kysyy	asker	kysyjänä
18	participatory link	participates	osallistuu	participant	osallistujana
19	participatory link	accepts	hyväksyy	accepted by	hyväksyjänä
20	participatory link	develops	kehittää	developed by	kehittäjänä
21	participatory link	proposes	ehdottaa	proposed by	ehdottajana
22	participatory link	answers	vastaa	answered by	vastaajana
23	participatory link	responsible for	vastuussa	responsibility of	vastuullisena
24	participatory link	negotiates	neuvottelee	negotiated by	neuvottelijana
25	participatory link	recommends	suosittelee	recommended by	suosittelijana
26	participatory link	controls	kontrolloi	controlled by	kontrolloijana
27	participatory link	claims	väittää	claimed by	väittäjänä
28	participatory link	owns	omistaa	owned by	omistajana
29	participatory link	does	tekee	done by	tekijänä
30	participatory link	maintains	ylläpitää	maintained by	ylläpitäjänä
31	participatory link	oversees	valvoo	overseen by	valvojana
32	operational link	has option	omistaa vaihtoehdon	option for	vaihtoehtona
33	operational link	has index	omistaa indeksin	index for	indeksinä
34	operational link	tells	kertoo	told by	kertojana
35	operational link	describes	kuvaa	described by	kuvaajana
36	operational link	maps	kartoittaa	mapped by	kartjoittajana
37	operational link	contains data	sisältää dataa	data contained in	data sisältyy
38	operational link	data for	on datana	gets data from	saa datansa
39	operational link	uses	käyttää	is used by	on käytettävänä	an input (object) for a process (subject)
40	operational link	produces	tuottaa	is produced by	tuottajana	Object is an output of a process produced by a stakeholder (subject)
41	operational link	provides	varustaa	is provided by	varustajana
42	operational link	part of	osana	has part	sisältää osan	is a part of a bigger entity, e.g. Venus is part of Solar System. Wikidata property P361 (part of) & P527 (has part). Previously we had relations about a decision: substance of, decision process of, stakeholder of, method of, task of, irrelevant to. But these are depreciated and replaced by has part, because the class of the object makes specific relations redundant.
43	operational link	about	aiheesta			a task is about a topic. This overlaps with has topic; merge them?
44	operational link	context for	kontekstina	has context	omistaa kontekstin	Original definition: subject given that object is true. However, this has not been used for that purpose. Unclear if this is needed.
45	operational link	has subclass	omistaa alajoukon	subclass of	alajoukkona	Wikidata property P279
46	operational link	has instance	omistaa instanssin	instance of	instanssina	Object belongs to a set defined by the subject and inherits the properties of the set. Sysnonym for has item, which is depreciated. Wikidata property P31
47	logical link	opposite	vastakohta			subject is opposite of object, e.g. black is opposite of white. Wikidata property P461; it is its own inverse
48	logical link	inverse	toisinpäin			a sentence is equal to another sentence where subject and object switch places and has the inverse relation. This is typically needed in preprocessing of insight networks, and it rarely is explicitly shown of graphs. Wikidata property P1696; it is its own inverse
49	logical link	if - then	jos - niin	if not - then not	jos ei - niin ei	If subject is true, then object is true. Also the negation is possible: if - then not. This links to logical operators and, or, not, equal, exists, for all; but it is not clear how they should be used in an insight network.
50	operational link	prepares	valmistelee	prepared by	valmistelijana
51	operational link	pays	kustantaa	paid by	kustantajana
52	operational link	rationale for	perustelee	has rationale	perusteltuu
53	operational link	offers	tarjoaa	offered by	tarjoajana
54	operational link	executes	suorittaa	executed by	suorittajana
55	operational link	has option	sisältää vaihtoehdon	option of	vaihtoehtona
56	operational link	irrelevant to	epärelevantti asiassa			If there is no identified relation (or chain of relations) between a subject and an object, it implies that the subject is irrelevant to the object. However, sometimes people may (falsely) think that it is relevant, and this relation is used to explicate the irrelevance.
57	evaluative link	finds important	kokee tärkeäksi	is found important	tärkeäksi kokijana
58	evaluative link	makes relevant	tekee relevantiksi	is made relevant	relevantiksi tekijänä	if the subject is valid in the given context, then the object is relevant. This typically goes between arguments, from a variable to value statement or from a value statement to a fact statement. This is a synonym of 'valid defend of type relevance'.
59	evaluative link	makes irrelevant	tekee epärelevantiksi	is made irrelevant	epärelevantiksi tekijänä	Opposite of 'makes relevant'. Synonym of 'valid attack of type relevance'.
60	evaluative link	makes redundant	tekee turhaksi	is made redundant	turhaksi tekijänä	Everything that is said in the object is already said in the subject. This depreciates a object because it brings no added value. However, it is kept for archival reasons and to demonstrate that the statement was heard.
61	evaluative link	has opinion	on mieltä			Subject (typically a stakeholder) supports the object (typically a value of fact statement). This is preferred over 'values' and 'finds important' because it is more generic without loss of meaning.
62	evaluative link	values	arvostaa	valued by	arvostajana	A stakeholder (subject) gives value or finds an object important. Object may be a topic or statement. Depreciated, use 'has opinion' instead.
63	evaluative link	has truthlikeness	on totuudellinen			A subjective probability that subject is true. Object is a numeric value between 0 and 1. Typically this has a qualifier "according to X" where X is the person or archetype who has assigned the probability.
64	evaluative link	has preference	mieltymys	preference of	mieltymyksenä	Subject is better than object in a moral sense.
65	evaluative link	has popularity	on suosiossa			A measure based on likes given by users.
66	evaluative link	has objective	omaa tavoitteen	objective of	tavoitteena
67	argumentative link	agrees	samaa mieltä
68	argumentative link	disagrees	eri mieltä
69	argumentative link	comments	kommentoi	commented by	kommentoijana
70	argumentative link	defends	puolustaa	defended by	puolustajana
71	argumentative link	attacks	hyökkää	attacked by	hyökkääjänä
72	referential link	topic of	aiheena	has topic	aiheesta	This is used when the object is a publication and the subject is a (broad) topic rather than a statement. In such situations, it is not meaningful to back up the subject with references. Useful in describing the contents of a publication, or identifying relevant literature for a topic.
73	referential link	discussed in	kerrotaan	discusses	kertoo
74	referential link	reference for	viitteenä	has reference	viite	Subject is a reference that backs up statements presented in the object. Used in the same way as references in scientific literature are used.
75	referential link	states	väittää	stated in	väitetään kohteessa	Describes the source of a statement; may also refer to a person.
76	referential link	tag for	täginä	has tag	omistaa tägin	Subject is a keyword, type, or class for object. Used in classifications.
77	referential link	category for	kategoriana	has category	kuuluu kategoriaan
78	referential link	associates with	liittyy			Subject is associated with object in some undefined way. This is a weak relation and does not affect the outcomes of inferences, but it may be useful to remind users that an association exists and it should be clarified more precisely. This is its own inverse.
79	referential link	answers question	vastaa kysymykseen	has answer	vastaus	Used between a statement (answer) and a topic (question). In knowledge crystals, the relation is embedded in the object structure.
80	indicator	indicator	indikaattori			Depreciated. Use item class indicator and relation describes.
81	indicator	risk indicator	riski-indikaattori			Depreciated. Use item class risk indicator and relation describes.
82	indicator	effectiveness indicator	vaikuttavuusindikaattori			Depreciated. Use item class effectiveness indicator and relation describes.
83	indicator	operational indicator	toimintaindikaattori			Depreciated. Use item class operational indicator and relation describes.
84	irrelevant argument	irrelevant comment	epärelevantti kommentti			We don't need inverses, because the relation is always tied with an argument (the subject).
85	irrelevant argument	irrelevant attack	epärelevantti hyökkäys
86	irrelevant argument	irrelevant defense	epärelevantti puolustus
87	relevant argument	relevant comment	relevantti kommentti
88	relevant argument	relevant attack	relevantti hyökkäys
89	relevant argument	relevant defense	relevantti puolustus
90	judgement	value judgement	arvovalinta			DO WE NEED THESE OR DO WE RATHER USE RELATION 'MAKES RELEVANT' OR SOMETHING ELSE?
91	judgemenet	value resolution	arvopäätös
92	judgemenet	value	arvostus
93	value judgemenet	reach	ulottuvuus
94	fact judgemenet	fact judgement	faktavalinta			WHAT ARE THE EXACT MEANINGS OF THESE?
95	fact judgemenet	estimate	arvio
96	fact judgemenet	fact resolution	faktapäätös

How to manage shared understanding

Shared understanding is a structured description of a decision situation. A key idea is that it is much faster to produce than a quantitative assessment, is more usefully organised than a free-format document (not to mention unmoderated discussions), and can distill information from both into a coherent information structure.

What steps does the work process contain?

Take a new piece of information.
Identify a decision situation to which it is relevant (or it is commonly considered relevant even if it is not).
Choose one of the topical relations for the piece.
Link the piece to something else within the decision situation with a relation. If it links to nothing, it is irrelevant.
Add descriptive tags, references etc. as appropriate.
Link the relations to the decision situation the relation part of (this should happen automatically).

Questions for further developing shared understanding:

What are the main questions within each topical area?
What are necessary structures and relations?
What software tools can be used?

Potential tools for managing the information

Google Drive graphical tool [1]
Protégé software for ontologies
Wikidata for RDF database using Wikibase software [2]
Git for version control [3]
Shiny R package for user interface [4] [5]
- Shiny packages for user table output dataTableOutput [6] ShinySky
R and D3 [7][8]

Example of using the structure

Columns that may have several values per risk are marked with *

Riskilomake (a variable with the question: What is a risk that is relevant for the success of THL's mission? There are several variables with an identical question, but each variable describes exactly one risk as an answer.)

Each column is described within the variable answer unless otherwise noted a property that is used to link the column contents to the variable.

id# Tarkastelukohde (yksikkö) * (has tag) Riskialue (aihepiiri karkea) * (has tag) Sisäalue / sisältösivu (aihepiiri tarkka) * (has tag) Riski Tarkennus Todennäköisyys Vakavuus Riskiluku (todennäköisyys*vakavuus) Hallintatoimet (kpl) Muistiinpanot Omistaja Tila Hallintatoimien valmius-% Omat liitteet * Luotu (automatic from version control) Päivitetty (automatic from version control)

Hallintatoimilomake (many-to-many relationship with risks) id# Hallintatoimi Määräpäivä Vastuuhenkilö Tila Omat liitteet * Luotu (automatic from version control) Päivitetty (automatic from version control)

Example about climate neutrality in Helsinki

Example about Arvoprofiili

Example about fisheries management in the Baltic Sea

Susan Star: This is not a boundary object. SSHV 2010

Technical prerequisites

Open policy ontology can be implemented using an RDF database, e.g. Wikibase. These are some links to resources and guidance about that.

Related concepts

Deliberative democracy

James Fishkin, a key proponent of deliberative democracy, describes two approaches to public opinion, raw vs. refined: what people actually think vs. what their opinion would be after it has been tested by the consideration of competing arguments and information coscientiously offered by others who hold contrasting views. Political process can be seen as whether a filter or a mirror. The filter creates counterfactual but deliberative representations of public opinion. The mirror offers a picture of public opinion just as it is, even if it is debilitated or inattentive. The conflicting images suggest a hard choice between the reflective opinion of the filter and the reflected opinion of the mirror.^[1]

It is only through the deliberations of a small face-to-face representative body that one can arrive at the "cool and deliberate sense of the community" (James Madison, Federalist No 63). ... A key desideratum in the Founders' project of constitutional design was the creation of conditions where the formulation and expression of deliberative public opinion would be possible.^[1] A smallish group of randomly selected people are likely to act as a filter, while e.g. a referendum would act as a mirror. During the early days of the United States, James Madison actively designed governance structures that would enable the formation of refined public opinion in the national US policy. The electorate was such a construct, designed to enable informed argumentation about president candidates before the final vote. However, this role has completely disappeared, as nowadays the outcome of the electoral vote is known as soon as the composition of the electorate is known.

Shared understanding follows these lines of reasoning and aims to produce a deliberative outcome of informed argumentation. However, the major difference is that the deliberative process does not aim to produce a decision by the participants, but a comprehensive description of shared understanding with all relevant points and disagreements. This written description enables other people to learn and form their own opinions of the matter, and thus help in other similar decision situations. Although producing such a description may be time-consuming and labourious, re-usability of the information makes it worth the effort.

Cognitive democracy

Henry Farrell (George Washington University), Cosma Shalizi (Carnegie Mellon University and The Santa Fe Institute). 2012?. An Outline of Cognitive Democracy [9],

Farrell and Shalizi analyze three main approaches to socially achieve results: hierarchies in different forms (with problems that those who are in power are not receiving information from the others); markets (with problems that they converge to individual benefit, which is sometimes in conflict with social benfit), and democracy (with problem how to actually implement the main principle of equal power among individuals). They suggests approaches to improve democracy.

Pol.is

Pol.is is a website for organised democratic discussion. It helps large organizations and communities understand themselves by visualizing what people think.

An example discussion about sote indicators [10] (in progress)
A case study of temperature check [11]
A case study from Taiwan [12]: vTaiwan: Public Participation Methods on the Cyberpunk Frontier of Democracy. In the midst of the signal failure known as the US electoral season, here’s something to be inspired about: a true story about rational deliberation on a national scale.

Professionalism

Jonathan Rauch and Benjamin Wittes. (May 2017) More professionalism, less populism: How voting makes us stupid, and what to do about it. Center for Effective Public Management at Brookings. [13]

Rauhankone

Artificial intelligence may solve some of the structural problems related to development of shared understanding. How this would actually happen is largely unclear. However, professor Timo Honkela is working toward this aim. For more details, see op_fi:Rauhankone.

Inforglobe

A similar but simpler approach is by Mikaeli Langinvainio and Juha Törmänen, who used to work for Crisis Management Initiative. They use statistics to understand views and opinions of different stakeholder groups. (HS 25.6.2017 Voiko rauhanneuvotteluja edistää matematiikalla?) Their company inforglobe produces consulting services based on these ideas. [14]

Their web tool contains these information structures and functionalities (for more details, see Inforglobe link above):

Likelihood of affecting the project vs impact for the project vs knowledge level on the risk or threats vs opportunities

Attributes

Categories (e.g. project planning, logistics and safety, or joker risks)
Participants (e.g. project team, planning organisation, partner organisation, or customer representative)

Issues e.g.

Contractor network (joker)
Cost stucture (planning)
Logistics
Machinery placement (logistics and safety)
Staff competence (planning)

Values e.g.:

Large or small 1-5
Likely 1-5
Knowledge good 1-5

Additional properties

Each value can be enhanced with a suggestion how to mitigate the impact or decrease the likelihood.
Individual answers can be shown with participant attributes and suggestions.
Each issue has a more detailed description.
Based on individual answers, you can make shared conclusions about each issue and how to manage the risks.
Assessment can be done several times.
Participants can be categorised based on position or sector (and maybe other attributes as well)

System dynamic maps

Issues as nodes
Complex system maps: Causal edges between them with strength
Significance of edges (links) is measured in some way and used to select nodes and edges for display
Co-operation: Links can also describe how well items (in this case organisations) communicate with each other.

References

↑ ^1.0 ^1.1 James Fishkin. (2011) When the people speak. Democratic deliberation and public consultancy. Publisher: Oxford University Press. ISBN 978-0199604432

[fishkin2011-1] 1.0 ^1.1 James Fishkin. (2011) When the people speak. Democratic deliberation and public consultancy. Publisher: Oxford University Press. ISBN 978-0199604432

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