Data Sprint: Emergence of Adaptation in International Climate Politics

In the debates around whether and how to adapt to a changing climate, much hinges on how adaptation is defined. And there is still lots of disagreement on this front since there are a multitude of actors and institutions trying to define the terms of the debate through a variety of different discourses. One way to get a handle on such an untethered problem of language is to begin with genealogy: where and when did the concept of adaptation emerge, how has it evolved over time, what other concepts does it lean on for support and who uses it in which ways?

One of our first attempts to gain clarity on these questions will be to treat a number of large corpora related to debates on adaptation in international negotiations (documents from the UNFCCC database and the whole collection of the Earth Negotiations Bulletin) as well as in the scientific literature (across all the IPCC reports and adaptation relevant scientific literature) with some of the textual analysis and network visualization software of Science Po’s médialab.  We are working in collaboration with the Stanford Literary Lab of Stanford University on the corpora in a sort of « battle of the digital humanities bands », to compare the results of our different tools and approaches. We are also working closely with experts from IDDRI, at Sciences Po, who are helping us define and select our corpora.

Below is an outline of our preliminary steps toward visualization and analysis.

Datasets, objectives and people.
General Objective

The aim of this sprint is less to produced final maps (visualization ready to be published) than to develop a clear and as-simple-as-possible procedure to extract data from the datasets listed below.
The expected output of the sprint are processed data tables that could be:
– easily opened and exploited with tools such as Gephi, Libreoffice, ManyEyes and such;
– easily updated as new data pours into the datasets without too much technical intervention.

1. Scientific literature on adaptation

  • Source: http://www.scopus.com/
  • During the sprint: prepare a script that compile and parse a csv exported from Scopus and generates various gexf (for relational information) and csv (for temporal series). (Mathieu, Tommaso, Liam)
  • Before the sprint: collect the data from Scopus (Tommaso)

2. Scientific literature in ISI on adaption

  • Source: http://webofknowledge.com/
  • During the sprint: prepare a script that compile and parse a txt exported from ISI WoK and generates various gexf (for relational information) and csv (for temporal series). (Mathieu, Tommaso, Liam)
  • Before the sprint: collect the data from ISI WoK (Tommaso)

3a. IPCC report

4. Earth Negotiations Bulletin on UNFCCC

  • Source: http://www.iisd.ca/vol12/
  • During the sprint: Analyse with Pattern the pds and extract monopartite network of countries names appearing in the same sentences; bipartite network of countries names and issues nominal groups appearing in the same sentence; monopartite networks of issues nominal groups appearing in the same sentence; network of who is speaking of whom “NAME OF COUNTRY for NAME OF THE GROUP” (Paul, Axel, Daniele)
  • Before the sprint: scrape and select the relevant ENB documents (Axel, Benjamin O.)

5. UNFCCC document

  • Source: http://unfccc.int/documentation/documents/items/3595.php
  • During the sprint: Index the documents and query it manually to generate various gexf (for relational information) and csv (for temporal series). (Julien, Romain, Ian, Benjamin, Audrey)
  • Before the sprint: Before the sprint: create an dictionary on interesting n-grams (with merge) (Ian, Nicolas, Axel, Benjamin, Audrey) –> convertir les pdf en txt pour qu’on puisse ensuite les indexer en vue de les requeter (? c’est bien ça qu’il faut faire ???) + faire une liste manuelle de mots clés pertinents.

6. UNFCCC side events

7. weADAPT.org, through their website API

  • Source:  http://weadapt.org/, http://api.weadapt.org/docs/
  • During the sprint: Generate bi-partite network of organisations and projects; mono-partite network of organisations (sharing projects); mono-partite network of projects (sharing organisations). Generate bi-partite network of tags and projects; mono-partite network of tags (sharing projects); mono-partite network of projects (sharing tags). Generate bi-partite network of tags and organisations; mono-partite network of tags (sharing organisations); mono-partite network of organisations (sharing tags). (Benjamin, Tommaso, Liam)
  • Before the sprint: nothing

8. Websites on adaptation through Hyphe

  • Source:
  • During the sprint: Crawl the seed, sieve the neighbours, iterate 2 or 3 times. (Benjamin, Tommaso, Audrey L.)
  • Before the sprint: Prepare a list of seed websites. (Ian, Nicolas, Axel)


More information on the datasets
(Unities = rows, documents, unit level,
Entities = columns, features, subelement/annotations, fields, data-object)
1. Scientific literature in Scopus on adaptation –

  1. Source: http://www.scopus.com/
  2. Query: TS=(« climate change » OR « global warming ») AND TS=(adapt* OR vulnerab* OR resilien*), from 1992
  3. Unities: bibliographical references
  4. Entities: Authors*, Title*, Year*, Source title*, Volume, Issue, Art. No., Page start, Page end, Page count, Cited by*, Link, Affiliations*, Authors with affiliations*, Abstract, Author Keywords*, Index Keywords*, Molecular Sequence, NumbersChemicals/CAS, Tradenames, Manufacturers, Funding Details*, References*, Correspondence Address*, Editors, Sponsors*, Publisher, Conference name*, Conference date, Conference location, Conference code*, ISSN*, ISBN*, CODEN*, DOI*, PubMed ID, Language of Original Document, Abbreviated Source Title*, Document Type*, Source, Link*, URL(?)
  5. Number of unities: about 15.000
  6. File formats: CSV / BibTexT
  7. Notes: we can use the link in csv file between unities and online article

2. Scientific literature in ISI on adaption (repeat what will be done on corpus 1 if possible)

  1. Source: http://webofknowledge.com/
  2. Query: TS=(« climate change » OR « global warming ») AND TS=(adapt* OR vulnerab* OR resilien*), from 1992
  3. Unities: bibliographical references
  4. Entities: FN: File Name, VR: Version Number, PT: Publication Type, AU: Authors*, AF: Author Full Name, CA: Group Authors, TI: Document Title*, ED: Editors, SO: Publication Name*, SE: Book Series Title, BS: Book Series Subtitle, LA: Language, DT: Document Type*, CT: Conference Title, CY: Conference Date, HO: Conference Host, CL: Conference Location, SP: Conference Sponsors, DE: Author Keywords*, ID: Keywords Plus®*, AB: Abstract*, C1: Author Address, RP: Reprint Address*, EM: E-mail Address, FU: Funding Agency and Grant Number*, FX: Funding Text, CR: Cited References*, NR: Cited Reference Count*, TC: Times Cited*, PU: Publisher, PI: Publisher City, PA: Publisher Address, SC: Subject Category, SN: ISSN*, BN: ISBN*, J9: 29-Character Source Abbreviation, JI: ISO Source Abbreviation*, PD: Publication Date, PY: Year Published*, VL: Volume, IS: Issue, PN: Part Number, SU: Supplement, SI: Special Issue, BP: Beginning Page, EP: Beginning Page, AR: Article Number, PG: Page Count, DI: Digital Object Identifier (DOI)*, SC: Subject Category*, GA: Document Delivery Number, UT: Unique Article Identifier, ER: End of Record
  5. Number of unities: about 10.000
  6. File format: TXT

3a. IPCC report

  1. Source: http://www.ipcc.ch/publications_and_data/publications_and_data_reports.shtml#.USNcz1p4a94
  2. Query: IPCC Report 1, 2, 3, 4, 5 (text not available yet)
  3. Unities: Reports of the 3 working groups, Synthesis reports, Special reports (not yet done)
  4. Entities: Title of report, Date, Contributor name, Contributor role, Contributor institution, Contributor nationality, Institution country, Contributor chapter, Chapter’s title. Analytical entities : « chapter content » adressed by reports (e.g. sea level rise), Contributor’s « chapter content »
  5. Number of unities: about 30
  6. File format: PDF

3b. IPCC Report in French

  1. Source: http://ipcc.ch/home_languages_main_french.shtml#.USYAquiKTAg
  2. Query: all documents under publication except “rapports méthodologiques” and « documents de base »
  3. Unities: Rapports de synthèse (2, 3, 4), Résumés pr décideurs + résumés techniques de chaque Working Group (3,4), Rapports spéciaux – résumés pr décideurs,documents techniques, glossaires
  4. Entities: cf. ci-dessus « IPCC Report »
  5. Number of unities: 36
  6. File format: PDF
  7. Notes : Audrey send it to Tom De Smet. He will try “Pattern for french” on it. To be continued …

4. Earth Negotiations Bulletin on UNFCCC

  1. Source: http://www.iisd.ca/vol12/
  2. Query: all the documents on the page
  3. Unities: Daily reports of negotiation, Summaries of negotiation meeting
  4. Entities: Volume*, Report collection number*, Meeting type*, Meeting number*, Date* Meeting place*, Report type*, Text (within the documents titles are in bold – look for « adaptation » and « in the corridors » in title)*
  5. Number of unities: about 600
  6. File format: HTML / HTML and PDF
  7. What we can do: monopartite network of countries names appearing in the same sentences; bipartite network of countries names and issues nominal groups appearing in the same sentence; monopartite networks of issues nominal groups appearing in the same sentence; network of who is speaking of whom “NAME OF COUNTRY for NAME OF THE GROUP”. We could test http://voyeurtools.org/ on these texts

5. UNFCCC document

  1. Source: http://unfccc.int/documentation/documents/items/3595.php
  2. Query: Document type : “Meeting documents – Submissions by parties and organizations”
  3. Unities: position papers of countries before UNFCCC meeting,
  4. Entities: url, pdf_filename, symbol*, title, authors*, pdf_url, pdf_language, abstract*, meeting*, doctype* (meeting papers, draft conclusions, party submissions, in-depth review, meeting reports, workshop documents, IGO submissions, submissions by parties and organizations, compilation and synthesis reports, technical papers, reports by the Secretariat, progress reports, NGO submissions, submissions, resolutions and decisions, national adaptation programmes of action (NAPA), treaties, synthesis and assessment reports, scenario notes), topics*, keywords*, countries*, pub date*, year*, text (pdf)*
  5. Number of unities: about 800
  6. File format: HTML and PDF
  7. ToDo: Before the sprint: create an dictionary on interesting n-grams (with merge) and their frequencies
    Idea: Use this corpus to calculate terms frequencies and then make an index to compare the specific terms of others corpora such as “3.a IPCC report” or “4. Earth Negotiations Bulletin on UNFCCC” regarding that index. Look out to do it with Pattern or …

6. UNFCCC side events

  1. Source: http://regserver.unfccc.int/seors/reports/archive.html
  2. Query: all documents
  3. Unities: table of side events at all sessions from 2003 onwards
  4. Entities: session name, event title, event organizer, event date
  5. NB : possible to retrieve attachments (pdf) to each side events
  6. Number of unities: 26 tables
  7. File format: HTML

7. weADAPT.org, through their website API

  1. Source: http://weadapt.org/, http://api.weadapt.org/docs/
  2. Query: API Access
  3. Unities: placemark (= project), organization, initiative (to ask weADAPT)
  4. Entities: author name, organization name/acronym, placemark latitude, placemark longitude, placemark title, tags
  5. Number of unities: about 1000
  6. File format: XML

8. Websites on adaptation through Hyphe

  1. Source: Hyphe
  2. Query: Seeds websites decided by experts
  3. Unities: Websites and hyperlinks