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turbot/hypothesis

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steampipe plugin install hypothesissteampipe plugin install hypothesis

hypothesis_profile hypothesis_search

Table: hypothesis_search - Query Hypothesis Searches using SQL

Hypothesis is a service that allows users to annotate web pages and PDFs, fostering conversations within the text. It is used by educators, journalists, publishers, and researchers to anchor discussions, express opinions, and share insights directly on top of digital content. Hypothesis Searches are a resource within this service that allows users to query and retrieve these annotations.

Table Usage Guide

The hypothesis_search table provides insights into Hypothesis Searches within the Hypothesis service. As a researcher or educator, explore annotation-specific details through this table, including the text, tags, and user who made the annotation. Utilize it to uncover information about annotations, such as those with specific tags, the users who made them, and their corresponding details.

Important Notes

Searches for Hypothesis annotations matching a query. If you authenticate you'll search the Hypothesis public layer plus all your private annotations, and annotations in private groups you belong to. If you don't authenticate you'll just search the public layer.

Examples

Find 10 recent notes, by `judell`, that have tags

Explore the recent activity of a specific user, 'judell', to identify instances where they have added tags to their notes. This is useful for understanding their areas of interest and their tagging habits.

select
  created,
  uri,
  tags,
  group_id,
  username
from
  hypothesis_search
where
  query = 'user=judell'
  and jsonb_array_length(tags) > 0
order by
  created desc
limit
  10;

select
  created,
  uri,
  tags,
  group_id,
  username
from
  hypothesis_search
where
  query = 'user=judell'
  and json_array_length(tags) > 0
order by
  created desc
limit
  10;

Find notes tagged with both `media` and `review`

Explore the instances where notes are tagged with both 'media' and 'review', allowing you to focus on specific areas of interest. This can be particularly useful when you're looking for overlaps in topics or themes. NOTE This matches notes with:

"media" and "review"
"social media" and "review"
"social media" and "peer review"

select
  uri,
  tags
from
  hypothesis_search
where
  query = 'tag=media&tag=review';

select
  uri,
  tags
from
  hypothesis_search
where
  query = 'tag=media&tag=review';

Find notes tagged with `social media` and `peer review`

Explore the instances where notes are tagged with both 'social media' and 'peer review', which can be useful for understanding the intersection of these two topics in your data.

select
  uri,
  tags
from
  hypothesis_search
where
  query = 'tag=social+media&tag=peer+review';

select
  uri,
  tags
from
  hypothesis_search
where
  query = 'tag=social+media&tag=peer+review';

Find notes on the New York Times home page, by month

Explore the frequency of annotations made on the New York Times homepage in a given month. This can help you understand the level of engagement or significant events during specific periods.

with data as (
  select
    substring(
      created
      from
        1 for 7
    ) as month,
    uri
  from
    hypothesis_search
  where
    query = 'uri=https://www.nytimes.com'
)
select
  month,
  count(*)
from
  data
group by
  month
order by
  count desc;

with data as (
  select
    substr(created, 1, 7) as month,
    uri
  from
    hypothesis_search
  where
    query = 'uri=https://www.nytimes.com'
)
select
  month,
  count(*)
from
  data
group by
  month
order by
  count(*) desc;

Find URLs and note counts on articles annotated in the Times' Opinion section

Explore which articles in the Times' Opinion section have been annotated and understand the frequency of these annotations. This can be useful to identify the most discussed or controversial articles.

with data as (
  select
    uri
  from
    hypothesis_search
  where
    query = 'wildcard_uri=https://www.nytimes.com/*/opinion/*'
)
select
  count(*),
  uri
from
  data
group by
  uri
order by
  count desc;

with data as (
  select
    uri
  from
    hypothesis_search
  where
    query = 'wildcard_uri=https://www.nytimes.com/*/opinion/*'
)
select
  count(*),
  uri
from
  data
group by
  uri
order by
  count(*) desc;

Find page notes (i.e. notes referring to the URL, not a selection) on www.example.com

Determine the instances where notes were made on the entire webpage of www.example.com, rather than a specific selection. This is useful for identifying overall feedback or comments about the webpage as a whole.

with target_keys_to_rows as (
  select
    id,
    username,
    created,
    text,
    uri,
    target,
    jsonb_object_keys(target -> 0) as target_key
  from
    hypothesis_search
  where
    query = 'uri=https://www.example.com'
  group by
    id,
    username,
    created,
    text,
    uri,
    target
  order by
    id
)
select
  distinct 'https://hypothes.is/a/' || id as link,
  *
from
  target_keys_to_rows
where
  target_key = 'Selector'
  and target -> 0 ->> 'Selector' is null
order by
  created desc;

with target_keys_to_rows as (
  select
    id,
    username,
    created,
    text,
    uri,
    target,
    json_each(target, '$[0]') as target_key
  from
    hypothesis_search
  where
    query = 'uri=https://www.example.com'
  group by
    id,
    username,
    created,
    text,
    uri,
    target
  order by
    id
)
select
  distinct 'https://hypothes.is/a/' || id as link,
  *
from
  target_keys_to_rows
where
  target_key.key = 'Selector'
  and json_extract(target, '$[0].Selector') is null
order by
  created desc;

Find notes, in the Times' Opinion section, that quote selections matching "covid"

Discover the segments that quote selections matching a specific term within the Times' Opinion section. This is useful for exploring user-generated annotations and comments on current events or trending topics, such as 'covid'.

select
  'https://hypothes.is/a/' || id as link,
  uri,
  username,
  created,
  exact
from
  hypothesis_search
where
  query = 'wildcard_uri=https://www.nytimes.com/*/opinion/*'
  and exact ~* 'covid'
order by
  created desc;

select
  'https://hypothes.is/a/' || id as link,
  uri,
  username,
  created,
  exact
from
  hypothesis_search
where
  query = 'wildcard_uri=https://www.nytimes.com/*/opinion/*'
  and exact LIKE '%covid%'
order by
  created desc;

Find annotated GitHub repos, join with info from GitHub API

Explore annotated GitHub repositories and gain insights into their associated details from the GitHub API. This can help you identify patterns or trends in the data, enhancing your understanding of these repositories. NOTE This will take a minute or so. Once it's done, it's cached for 5 minutes, or another duration you can specify, so queries that touch the same data are instantaneous.

with annotated_urls as (
  select
    regexp_matches(uri, 'github.com/([^/]+)/([^/]+)') as match,
    *
  from
    hypothesis_search
  where
    query = 'wildcard_uri=http://github.com/*&limit=1000'
  order by
    uri
),
and_repos as (
  select
    *,
    match [ 1 ] || '/' || match [ 2 ] as repository_full_name
  from
    annotated_urls
  order by
    uri
)
select
  distinct g.name,
  g.description,
  g.owner_login,
  r.uri,
  r.id,
  r.username
from
  github_repository g
  join and_repos r on g.full_name = r.repository_full_name;

with annotated_urls as (
  select
    uri,
    *
  from
    hypothesis_search
  where
    query = 'wildcard_uri=http://github.com/*&limit=1000'
  order by
    uri
),
and_repos as (
  select
    *,
    uri as repository_full_name
  from
    annotated_urls
  order by
    uri
)
select
  distinct g.name,
  g.description,
  g.owner_login,
  r.uri,
  r.id,
  r.username
from
  github_repository g
  join and_repos r on g.full_name = r.repository_full_name;

Order annotated GitHub repos by count of annotations

This query is used to analyze the frequency of annotations made by users on different GitHub repositories. It can be beneficial to identify which repositories are receiving the most attention or interaction, potentially indicating areas of high interest or activity.

with annotated_urls as (
  select
    id,
    created,
    uri,
    username,
    regexp_matches(uri, 'github.com/([^/]+)/([^/]+)') as match
  from
    hypothesis_search
  where
    query = 'wildcard_uri=http://github.com/*&limit=100'
  order by
    uri
),
and_repos as (
  select
    a.*,
    a.match [ 1 ] || '/' || a.match [ 2 ] as repository_full_name
  from
    annotated_urls a
  order by
    a.uri
),
joined as (
  select
    distinct g.name,
    g.owner_login,
    r.uri,
    r.id,
    r.username
  from
    github_repository g
    join and_repos r on g.full_name = r.repository_full_name
)
select
  count(j.*),
  j.name,
  j.owner_login,
  j.uri
from
  joined j
group by
  j.name,
  j.owner_login,
  j.uri
order by
  count desc;

Error: The corresponding SQLite query is unavailable.

Find URIs with conversational threads spanning more than one day

with thread_data as (
  select
    uri,
    count(*),
    min(created) as first,
    max(created) as last,
    sum(jsonb_array_length(refs)) as refs,
    array_agg(distinct username) as thread_participants
  from
    hypothesis_search
  where
    query = 'limit=1000'
  group by
    uri
)
select
  uri,
  count as annos,
  refs,
  first,
  last,
  date(last) - date(first) as days,
  thread_participants
from
  thread_data
where
  date(last) - date(first) > 0
  and refs is not null

Error: The corresponding SQLite query is unavailable.

Fetch the most recent 10000 annotations

Determine the areas in which the most recent 10,000 annotations exist. This is useful for gaining insights into the latest trends and patterns in your data, especially when dealing with large volumes of annotations that are continuously accumulating.

select
  *
from
  hypothesis_search
where
  query = 'limit=10000';

select
  *
from
  hypothesis_search
where
  query = 'limit=10000';

NOTE When you use limit in the query string, it means: If there are limit annotations that match your query, fetch all of them. They will be stored in the Steampipe cache for 5 minutes by default, or longer if you add an options argument to your hypothesis.spc file and adjust the cache_ttl to a longer duration.

options "connection" {
  cache = "true"
  cache_ttl = 300 # default 5 minutes
}

Merging historical and live data

Suppose you have 500,000 annotations and are continuing to accumulate them at the rate of several thousand per day. (This is a real scenario.) You could stash the 500,000 in a table, or in a materialized view, like so:

create materialized view my_hypothesis_annotations as (
  select
    *
  from
    hypothesis_search
  where
    query = 'group=my_group&limit=500000'
) with data;

Error: SQLite does not support materialized views directly.

You could then merge those with live data like so.

with historical as (
  select
    *
  from
    my_hypothesis_annotations
),
new as (
  select
    *
  from
    hypothesis_search new
  where
    query = 'group=my_group&limit=5000'
    and not exists (
      select
        *
      from
        historical
      where
        historical.id = new.id
    )
),
select
  *
from
  historical
union
select
  *
from
  new

Error: The corresponding SQLite query is unavailable.

Schema for hypothesis_search

Name	Type	Operators	Description
_ctx	jsonb		Steampipe context in JSON form.
created	text		The creation date of the annotation.
document	jsonb		An element that contains the title and maybe other metadata.
exact	text		The text of the selection (aka quote) to which the annotation anchors.
group_id	text		The annotation's group: __world__ or a private group id.
id	text		The annotation id, works with https://hypothes.is/a/{ID}.
query	text	=	The search query.
refs	jsonb		IDs forming the reference chain to which this annotation belongs.
sp_connection_name	text	=, !=, ~~, ~~, !~~, !~~	Steampipe connection name.
sp_ctx	jsonb		Steampipe context in JSON form.
tags	jsonb		Tags on the annotation, as a JSONB array of strings.
target	jsonb		The selectors that define the document selection to which the annotation anchors.
text	text		Textual body of the annotation, as MarkDown/HTML.
title	text		The HTML doctitle of the annotated URL.
updated	text		The last update date of the annotation.
uri	text		URL of the annotated resource.
username	text		The Hypothesis username of the person who created the annotation.

Export

This table is available as a standalone Exporter CLI. Steampipe exporters are stand-alone binaries that allow you to extract data using Steampipe plugins without a database.

You can download the tarball for your platform from the Releases page, but it is simplest to install them with the steampipe_export_installer.sh script:

/bin/sh -c "$(curl -fsSL https://steampipe.io/install/export.sh)" -- hypothesis

You can pass the configuration to the command with the --config argument:

steampipe_export_hypothesis --config '<your_config>' hypothesis_search