doc_id stringlengths 16 25 | page int64 0 635 | chunk int64 0 24 | mention_name stringlengths 2 86 | start int64 0 2.75k | end int64 5 2.78k | extractor_specificity stringclasses 3
values | extractor_typology stringclasses 1
value | specificity stringclasses 3
values | typology stringclasses 11
values | usage stringlengths 6 756 ⌀ | valid_data_mention bool 2
classes | judge_error stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
reliefweb:001630 | 20 | 2 | Twitter data | 131 | 143 | named | named | database | conclude that ⟦Twitter data⟧ is | true | null | |
reliefweb:001630 | 21 | 0 | geotagged data | 247 | 261 | descriptive | descriptive | geospatial | even if forcibly displaced people are under-represented in the ⟦geotagged data⟧ | true | null | |
reliefweb:001630 | 21 | 0 | data from Skype | 984 | 999 | named | named | database | Studies using log-in information to track migration have used ⟦data from Skype⟧ | true | null | |
reliefweb:001630 | 21 | 0 | Yahoo! e-mail | 1,009 | 1,022 | named | named | database | and ⟦Yahoo! e-mail⟧ [50, 51] | true | null | |
reliefweb:001630 | 21 | 0 | call detail records | 1,436 | 1,455 | descriptive | descriptive | administrative | provide more detailed information on the individual than many other Big (Crisis) Data sources, e.g., ⟦call detail records⟧ | true | null | |
reliefweb:001630 | 21 | 0 | Log-in data | 1,464 | 1,475 | descriptive | descriptive | other | ⟦Log-in data⟧ are proprietary to the service provider and not publicly available | true | null | |
reliefweb:001630 | 21 | 0 | call detail records | 1,565 | 1,584 | descriptive | descriptive | administrative | However, contrary to ⟦call detail records⟧, many service providers operate on an international scale | true | null | |
reliefweb:001630 | 21 | 1 | log-in data | 137 | 148 | descriptive | descriptive | other | Like every other Big (Crisis) data source that uses exhaust data, ⟦log-in data⟧ have a problem with penetration bias | true | null | |
reliefweb:001630 | 21 | 1 | log-in data | 381 | 392 | descriptive | descriptive | other | the fact that ⟦log-in data⟧ often includes some basic demographics | true | null | |
reliefweb:001630 | 21 | 1 | Call Detail Records | 589 | 608 | descriptive | descriptive | administrative | **⟦Call Detail Records⟧** | true | null | |
reliefweb:001630 | 21 | 1 | call detail records | 636 | 655 | descriptive | descriptive | administrative | Carrier networks collect ⟦call detail records⟧ for billing purposes | true | null | |
reliefweb:001630 | 21 | 1 | call detail records | 1,100 | 1,119 | descriptive | descriptive | administrative | makes ⟦call detail records⟧ an accurate data source for population movements | true | null | |
reliefweb:001630 | 22 | 0 | call detail records | 51 | 70 | descriptive | descriptive | administrative | based on 72 billion anonymized ⟦call detail records⟧ from October 2010 to April 2014 | true | null | |
reliefweb:001630 | 22 | 0 | survey and census data | 275 | 297 | descriptive | descriptive | survey | surpasses the quality of ⟦survey and census data⟧ by far | true | null | |
reliefweb:001630 | 22 | 0 | call detail records | 1,069 | 1,088 | descriptive | descriptive | administrative | data from ⟦call detail records⟧ are only available in anonymised form | true | null | |
reliefweb:001630 | 22 | 1 | call detail records | 735 | 754 | descriptive | descriptive | administrative | the accuracy of the location data in ⟦call detail records⟧ might get compromised | true | null | |
reliefweb:001630 | 22 | 1 | location data | 1,652 | 1,665 | descriptive | vague | other | Hence, ⟦location data⟧ from rural areas will be systematically less precise than location data from urban areas | true | null | |
reliefweb:001630 | 23 | 0 | call detail records | 10 | 29 | descriptive | descriptive | administrative | As ⟦call detail records⟧[1] contain sensitive customer information | true | null | |
reliefweb:001630 | 23 | 0 | call detail records | 654 | 673 | descriptive | descriptive | administrative | Finally, ⟦call detail records⟧[2] contain ⟦mobility data⟧[3] with high granularity | true | null | |
reliefweb:001630 | 23 | 0 | mobility data | 682 | 695 | vague | vague | other | Finally, ⟦call detail records⟧[2] contain ⟦mobility data⟧[3] with high granularity | true | null | |
reliefweb:001630 | 23 | 0 | post-crisis data | 933 | 949 | vague | vague | other | it is usually recommended to compare ⟦post-crisis data⟧[4] with pre-crisis data [26] | true | null | |
reliefweb:001630 | 23 | 0 | Facebook’s raw data | 1,675 | 1,694 | named | named | other | offers several aggregated statistics and maps based on ⟦Facebook’s raw data⟧[5] | true | null | |
reliefweb:001630 | 23 | 1 | data from Facebook’s Advertising platform | 506 | 547 | descriptive | named | database | Zagheni et al. introduce ⟦data from Facebook’s Advertising platform⟧[6] to estimate migrant stocks | true | null | |
reliefweb:001630 | 23 | 1 | data on migration from Facebook’s advertising platform | 601 | 655 | descriptive | named | database | Spyratos et al. [60] use ⟦data on migration from Facebook’s advertising platform⟧[7] to map-out migration flows | true | null | |
reliefweb:001630 | 23 | 1 | Facebook data | 870 | 883 | named | named | database | They suggest a method to correct the bias in the ⟦Facebook data⟧[8] | true | null | |
reliefweb:001630 | 23 | 1 | data from Facebook advertising | 991 | 1,021 | descriptive | named | database | They conclude that ⟦data from Facebook advertising⟧[9], once corrected for biases, can be used as a cheap and globally available real-time supplement to official migration statistics | true | null | |
reliefweb:001630 | 23 | 1 | Facebook’s advertising data | 1,300 | 1,327 | named | named | database | develop a method to use ⟦Facebook’s advertising data⟧[10] for real-time monitoring of crises situations | true | null | |
reliefweb:001630 | 23 | 1 | Facebook data | 1,462 | 1,475 | named | named | database | despite the biases in the ⟦Facebook data⟧[11] and the potential noise in the Facebook algorithm | true | null | |
reliefweb:001630 | 24 | 0 | Big (Crisis) Data | 1,188 | 1,205 | descriptive | vague | other | ⟦Big (Crisis) Data⟧[12] offers the possibility to access timely information | true | null | |
reliefweb:001630 | 24 | 1 | Big (Crisis) Data | 325 | 342 | vague | vague | other | contributions of ⟦Big (Crisis) Data⟧[13] to predictive models of forced displacement | true | null | |
reliefweb:001630 | 28 | 0 | ICEWS event data | 1,314 | 1,330 | named | named | other | Comparing GDELT and ⟦ICEWS event data⟧[14] | false | null | |
reliefweb:001630 | 28 | 1 | ICEWS event data | 61 | 77 | named | named | other | Comparing GDELT and ⟦ICEWS event data⟧[15] | false | null | |
reliefweb:001630 | 29 | 0 | online search data | 847 | 865 | descriptive | descriptive | other | Estimating migration flows using ⟦online search data⟧[16] | false | null | |
reliefweb:001630 | 29 | 0 | geo-located social media data | 1,585 | 1,614 | descriptive | descriptive | other | Using ⟦geo-located social media data⟧[17] to study refugee crises | false | null | |
reliefweb:001630 | 29 | 1 | geo-located social media data | 98 | 127 | descriptive | descriptive | other | Using ⟦geo-located social media data⟧[18] to study refugee crises | false | null | |
reliefweb:001630 | 29 | 1 | geo-social network data | 805 | 828 | descriptive | descriptive | other | Exploratory spatiotemporal language analysis of ⟦geo-social network data⟧[19] for identifying movements of refugees | false | null | |
reliefweb:001630 | 30 | 0 | mobile phone network data | 1,126 | 1,151 | descriptive | descriptive | other | tracking population movements with ⟦mobile phone network data⟧[20] | false | null | |
reliefweb:001630 | 30 | 1 | Facebook Network data | 1,090 | 1,111 | named | named | other | Quantifying international human mobility patterns using ⟦Facebook Network data⟧[21] | false | null | |
reliefweb:001630 | 3 | 0 | EventRegistry | 1,664 | 1,677 | named | named | database | The currently biggest databases are ⟦EventRegistry⟧[22] | true | null | |
reliefweb:001630 | 3 | 0 | GDELT | 1,679 | 1,684 | named | named | database | The currently biggest databases are ⟦EventRegistry⟧[22], ⟦GDELT⟧[23], which is publicly available | true | null | |
reliefweb:001630 | 3 | 0 | ICEWS | 1,719 | 1,724 | named | named | database | ⟦GDELT⟧[23], which is publicly available, and ⟦ICEWS⟧[24], with only limited access | true | null | |
reliefweb:001630 | 3 | 0 | EOS News Article Archive | 1,816 | 1,840 | named | named | database | Further smaller projects include, e.g., Georgetown University’s ⟦EOS News Article Archive⟧[25] | true | null | |
reliefweb:001630 | 3 | 0 | Global Terrorism Database | 1,852 | 1,877 | named | named | database | or GTD the ⟦Global Terrorism Database⟧[26] provided by the University of Maryland | true | null | |
reliefweb:001630 | 3 | 1 | ICEWS | 6 | 11 | named | named | database | and ⟦ICEWS⟧[1], with only limited access | true | null | |
reliefweb:001630 | 3 | 1 | EOS News Article Archive | 103 | 127 | named | named | database | Georgetown University’s ⟦EOS News Article Archive⟧[2] | true | null | |
reliefweb:001630 | 3 | 1 | Global Terrorism Database | 139 | 164 | named | named | database | the ⟦Global Terrorism Database⟧[3] provided by the University of Maryland | true | null | |
reliefweb:001630 | 3 | 1 | Decahose | 1,233 | 1,241 | named | named | database | gives access to the ⟦Decahose⟧[4] | true | null | |
reliefweb:001630 | 3 | 1 | Call Detail Records | 1,320 | 1,339 | descriptive | descriptive | administrative | ⟦Call Detail Records⟧[5]: ⟦Call detail records⟧[6] (CDR) are user data collected for billing purposes by carrier networks | true | null | |
reliefweb:001630 | 3 | 1 | Call detail records | 1,343 | 1,362 | descriptive | descriptive | administrative | ⟦Call Detail Records⟧[5]: ⟦Call detail records⟧[6] (CDR) are user data collected for billing purposes by carrier networks | true | null | |
reliefweb:001630 | 4 | 0 | Google Trends | 380 | 393 | named | named | system | ⟦Google Trends⟧[7] allows extracting aggregated search histories | true | null | |
reliefweb:001630 | 4 | 0 | climatic and weather data | 997 | 1,022 | descriptive | descriptive | other | data that are regularly posted online, e.g., ⟦climatic and weather data⟧[8] | true | null | |
reliefweb:001630 | 4 | 0 | price data from commodity exchanges | 1,024 | 1,059 | descriptive | descriptive | other | ⟦price data from commodity exchanges⟧[9] | true | null | |
reliefweb:001630 | 4 | 0 | price data from local food markets | 1,064 | 1,098 | descriptive | descriptive | other | ⟦price data from local food markets⟧[10] published by the FAO, national governments, or NGOs | true | null | |
reliefweb:001630 | 4 | 0 | Ushahidi | 1,236 | 1,244 | named | named | system | A further potential source of Big (Crisis) Data are crowdsourced crisis maps, e.g., ⟦Ushahidi⟧[11] | true | null | |
reliefweb:001630 | 4 | 0 | HOTOSM | 1,246 | 1,252 | named | named | system | A further potential source of Big (Crisis) Data are crowdsourced crisis maps, e.g., ⟦HOTOSM⟧[12] | true | null | |
reliefweb:001630 | 4 | 0 | Liveuamap | 1,257 | 1,266 | named | named | system | A further potential source of Big (Crisis) Data are crowdsourced crisis maps, e.g., ⟦Liveuamap⟧[13] | true | null | |
reliefweb:001630 | 5 | 0 | historical data | 1,454 | 1,469 | vague | vague | other | can be predicted based on ⟦historical data⟧[14] | true | null | |
reliefweb:001630 | 5 | 0 | historical data | 1,654 | 1,669 | vague | vague | other | no ⟦historical data⟧[15] from a recent event exist | true | null | |
reliefweb:001630 | 5 | 0 | historical data | 1,733 | 1,748 | vague | vague | other | to which degree ⟦historical data⟧[16] from other events are applicable | true | null | |
reliefweb:001630 | 5 | 1 | historical data | 8 | 23 | vague | vague | other | to which degree ⟦historical data⟧[17] from other events are applicable | true | null | |
reliefweb:001630 | 5 | 1 | Big (Crisis) Data | 713 | 730 | descriptive | descriptive | other | Novel data sources, like ⟦Big (Crisis) Data⟧[18], can provide such timely data | true | null | |
reliefweb:001630 | 5 | 1 | Big (Crisis) Data | 830 | 847 | descriptive | descriptive | other | ⟦Big (Crisis) Data⟧[19] is an umbrella term for data sources characterised by volume, velocity, and variety | true | null | |
reliefweb:001630 | 5 | 1 | data from social network sites | 972 | 1,002 | descriptive | descriptive | other | such as satellite imagery, ⟦data from social network sites⟧[20], or exhaust data | true | null | |
reliefweb:001630 | 5 | 1 | call detail records | 1,028 | 1,047 | descriptive | descriptive | administrative | exhaust data such as ⟦call detail records⟧[21] (CDR) | true | null | |
reliefweb:001630 | 5 | 1 | data from search engines | 1,055 | 1,079 | descriptive | descriptive | other | ⟦data from search engines⟧[22], or log-ins | true | null | |
reliefweb:001630 | 6 | 0 | Internet World Stats | 83 | 103 | named | named | database | According to ⟦Internet World Stats⟧[23] (2018), at the beginning of the year 2018 | true | null | |
reliefweb:001630 | 7 | 0 | Big (Crisis) Data | 176 | 193 | vague | descriptive | other | the information in ⟦Big (Crisis) Data⟧[24] that is valuable for predictive models | true | null | |
reliefweb:001630 | 8 | 0 | Big (Crisis) data | 284 | 301 | vague | descriptive | other | different sources of ⟦Big (Crisis) data⟧[25] | true | null | |
reliefweb:001632 | 4 | 0 | data resources | 1,560 | 1,574 | vague | vague | other | No identifying information will be revealed in ⟦data resources⟧[26] | true | null | |
reliefweb:001633 | 11 | 3 | Rapport mensuel de monitoring de protection Bandundu | 861 | 913 | named | named | report | ⟦Rapport mensuel de monitoring de protection Bandundu⟧[27] mois de décembre 2023 Kadima Foundation et UNHCR | true | null | |
reliefweb:001633 | 12 | 2 | Rapport mensuel de monitoring de protection Bandundu | 1,210 | 1,262 | named | named | report | ⟦Rapport mensuel de monitoring de protection Bandundu⟧[28] mois de déc | true | null | |
reliefweb:001633 | 12 | 3 | Rapport mensuel de monitoring de protection Bandundu | 95 | 147 | named | named | report | ⟦Rapport mensuel de monitoring de protection Bandundu⟧[29] mois de décembre 2023 Kadima Foundation et UNHCR | true | null | |
reliefweb:001633 | 13 | 0 | données de suivi de la protection | 1,003 | 1,036 | descriptive | descriptive | other | Les ⟦données de suivi de la protection⟧[30] sont utilisées tout au long du rapport | true | null | |
reliefweb:001633 | 13 | 1 | chiffres du suivi de la protection | 283 | 317 | descriptive | descriptive | other | Les ⟦chiffres du suivi de la protection⟧ peuvent ne pas correspondre aux derniers développements | true | null | |
reliefweb:001636 | 1 | 0 | national birth registration system | 945 | 979 | descriptive | descriptive | other | refugees being included in the ⟦national birth registration system⟧ | false | null | |
reliefweb:001637 | 18 | 0 | SATELLITE IMAGEMAP | 507 | 525 | named | descriptive | geospatial | ⟦SATELLITE IMAGEMAP⟧ © 1996-2004 PLANETARY VISIONS | true | null | |
reliefweb:001637 | 26 | 0 | SATELLITE IMAGEMAP | 1,355 | 1,373 | named | descriptive | geospatial | ⟦SATELLITE IMAGEMAP⟧ © 1996-2004 PLANETARY VISIONS | true | null | |
reliefweb:001637 | 2 | 0 | Aral Sea SATELLITE IMAGEMAP | 785 | 812 | named | descriptive | geospatial | ⟦Aral Sea SATELLITE IMAGEMAP⟧ © 1996-2004 PLANETARY VISIONS | true | null | |
reliefweb:001637 | 31 | 1 | asylum- and refugee-related data | 1,131 | 1,163 | descriptive | descriptive | other | the comprehensive collection of ⟦asylum- and refugee-related data⟧ | true | null | |
reliefweb:001637 | 3 | 0 | UNHCR archives | 456 | 470 | named | named | other | **Historical documents** ⟦UNHCR archives⟧ | true | null | |
reliefweb:001638 | 16 | 0 | UK Government figures | 174 | 195 | descriptive | descriptive | other | ⟦UK Government figures⟧ show that approximately twothirds of the refugees | true | null | |
reliefweb:001638 | 21 | 1 | skills audit of refugees | 1,965 | 1,989 | descriptive | descriptive | other | A ⟦skills audit of refugees⟧, which is recommended, provides a basis for engagement with local and national employers | false | null | |
reliefweb:001638 | 25 | 0 | Survey of New Refugees | 326 | 348 | named | named | survey | there has also been no widespread systematic evaluation of the integration of refugees since the ⟦Survey of New Refugees⟧ in the United Kingdom | true | null | |
reliefweb:001638 | 25 | 0 | monitoring data on their VPRS arrivals | 765 | 803 | descriptive | descriptive | other | LAs are now asked to provide ⟦monitoring data on their VPRS arrivals⟧ at two points during their first 12 to 18 months in the UK | true | null | |
reliefweb:001638 | 25 | 0 | data being collected by the central government | 1,239 | 1,285 | descriptive | vague | other | the ⟦data being collected by the central government⟧ can provide a useful baseline | true | null | |
reliefweb:001638 | 29 | 0 | survey of new refugees in United Kingdom | 500 | 540 | named | named | other | findings from the ⟦survey of new refugees in United Kingdom⟧: Home Office Research Report 37 | false | null | |
reliefweb:001642 | 2 | 0 | mécanisme MRM | 517 | 530 | named | named | other | 11 attacks against hospitals had been recorded by the ⟦mécanisme MRM⟧ | false | null | |
reliefweb:001643 | 10 | 1 | données de suivi de la protection | 368 | 401 | descriptive | descriptive | other | Les ⟦données de suivi de la protection⟧ sont utilisées tout au long du rapport | true | null | |
reliefweb:001643 | 2 | 1 | monitoring de protection 2 | 339 | 365 | named | descriptive | other | Tableau présentant les tendances de violations et abus des droits signalées par le ⟦monitoring de protection 2⟧ en Ituri | true | null | |
reliefweb:001643 | 4 | 2 | monitoring de protection | 67 | 91 | descriptive | descriptive | other | ont été documentés par le ⟦monitoring de protection⟧ au cours de cette période | true | null | |
reliefweb:001645 | 11 | 0 | Survivor testimonies | 1,360 | 1,380 | descriptive | descriptive | other | ⟦Survivor testimonies⟧ collected by NGOs and the IOM generally describe the following mode of operation | true | null | |
reliefweb:001645 | 23 | 1 | United Nations Treaty Collection | 802 | 834 | named | named | other | ⟦United Nations Treaty Collection⟧, http://treaties.un.org/Pages/ViewDetails.aspx | false | null | |
reliefweb:001645 | 3 | 1 | United Nations Treaty Collection | 1,325 | 1,357 | named | named | other | ⟦United Nations Treaty Collection⟧: | false | null | |
reliefweb:001645 | 45 | 1 | UNHCR Regional Operations File | 544 | 574 | named | named | database | ⟦UNHCR Regional Operations File⟧ – Latin America: Mexico, Statistical Snapshot | true | null | |
reliefweb:001645 | 5 | 2 | U.S. Department of State 2008 estimations | 780 | 821 | named | named | other | referring to ⟦U.S. Department of State 2008 estimations⟧ | false | null | |
reliefweb:001645 | 8 | 1 | 2003 IOM World Migration Report | 481 | 512 | named | named | report | The ⟦2003 IOM World Migration Report⟧ informed that around the period of reporting | true | null | |
reliefweb:001645 | 8 | 1 | World Bank Migration and Remittances Factbook 2011 | 681 | 731 | named | named | report | ⟦World Bank Migration and Remittances Factbook 2011⟧, _supra_ note 5, p. 3 | true | null | |
reliefweb:001645 | 8 | 1 | UNHCR Regional Operations File | 1,438 | 1,468 | named | named | database | ⟦UNHCR Regional Operations File⟧ – Latin America: Mexico, Statistical Snapshot | true | null | |
reliefweb:001645 | 8 | 2 | UNHCR Regional Operations File | 107 | 137 | named | named | database | ⟦UNHCR Regional Operations File⟧ – Latin America: Mexico, Statistical Snapshot | true | null | |
reliefweb:001645 | 9 | 0 | UNHCR statistics on Mexico | 1,371 | 1,397 | named | named | other | ⟦UNHCR statistics on Mexico⟧ hold that, as at January 2011, there were 1,395 recognized refugees in Mexico | true | null |
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