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values | typology stringclasses 11
values | usage stringlengths 0 1.45k ⌀ | valid_data_mention bool 2
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value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
jdc_operational:000057 | 62 | 1 | SNSOP MIS | 548 | 557 | named | named | system | ⟦SNSOP MIS⟧ over the course of project implementation | true | null | |
jdc_operational:000057 | 62 | 1 | Payment data | 610 | 622 | vague | descriptive | other | ⟦Payment data⟧ will be regularly updated in the SNSOP MIS | true | null | |
jdc_operational:000057 | 63 | 0 | SNSOP MIS | 617 | 626 | named | named | system | ⟦SNSOP MIS⟧ | true | null | |
jdc_operational:000057 | 63 | 0 | Beneficiary data | 627 | 643 | descriptive | vague | other | ⟦Beneficiary data⟧ will be collected during registration and updated during project implementation | true | null | |
jdc_operational:000057 | 63 | 0 | SNSOP MIS | 792 | 801 | named | named | system | Payment data will be regularly updated in the ⟦SNSOP MIS⟧ | true | null | |
jdc_operational:000057 | 63 | 1 | GRM data | 153 | 161 | descriptive | descriptive | other | ⟦GRM data⟧ will be reviewed and analyzed on a monthly basis through the MIS GRM module | true | null | |
jdc_operational:000057 | 63 | 1 | Payment data | 660 | 672 | descriptive | descriptive | other | ⟦Payment data⟧ stored in the MIS will be compared with approved payment schedules | true | null | |
jdc_operational:000057 | 74 | 1 | corruptionperception index | 194 | 220 | descriptive | named | indicator | South Sudan is ranked second most corrupt country in the world on transparency ⟦corruptionperception index⟧ | true | null | |
jdc_operational:000058 | 11 | 0 | population data | 445 | 460 | descriptive | vague | other | using humanitarian agencies’ latest ⟦population data⟧ | true | null | |
jdc_operational:000058 | 11 | 0 | IOM’s DTM projections | 1,114 | 1,135 | named | named | estimates | utilizing ⟦IOM’s DTM projections⟧ | true | null | |
jdc_operational:000058 | 11 | 0 | population data | 1,223 | 1,238 | vague | vague | other | no ⟦population data⟧ are available | true | null | |
jdc_operational:000058 | 11 | 1 | 2008 census | 509 | 520 | descriptive | named | census | complementing ⟦2008 census⟧ with other data sources | true | null | |
jdc_operational:000058 | 11 | 1 | DTM | 559 | 562 | named | named | system | complementing 2008 census with other data sources (for example, ⟦DTM⟧.) | true | null | |
jdc_operational:000058 | 14 | 1 | flood and drought data | 1,593 | 1,615 | descriptive | descriptive | other | based on available ⟦flood and drought data⟧ | true | null | |
jdc_operational:000058 | 2 | 0 | global development indicators | 966 | 995 | descriptive | descriptive | indicator | ranked almost at the bottom of the ⟦global development indicators⟧ | true | null | |
jdc_operational:000058 | 2 | 0 | Global Climate Risk Index | 1,695 | 1,720 | named | named | indicator | The ⟦Global Climate Risk Index⟧ ranked the country 125 out of 171 between 1998 and 2018 | true | null | |
jdc_operational:000058 | 2 | 1 | Global Climate Risk Index | 1 | 26 | named | named | indicator | ⟦Global Climate Risk Index⟧ ranked the country 125 out of 171 between 1998 and 2018 | true | null | |
jdc_operational:000058 | 3 | 2 | Human Development Index | 395 | 418 | named | named | indicator | the ⟦Human Development Index⟧ (HDI) | true | null | |
jdc_operational:000058 | 4 | 2 | Displacement Tracking Matrix | 660 | 688 | named | named | system | International Organization for Migration (IOM), ⟦Displacement Tracking Matrix⟧ (DTM), Round 6 | true | null | |
jdc_operational:000058 | 6 | 0 | intention surveys | 717 | 734 | descriptive | descriptive | survey | According to recent ⟦intention surveys⟧ by both the United Nations High Commission for Refugees and IOM | true | null | |
jdc_operational:000058 | 6 | 1 | IOM assessment | 399 | 413 | named | named | report | An ⟦IOM assessment⟧ commissioned by the World Bank found | true | null | |
jdc_operational:000058 | 7 | 2 | Trader Survey in South Sudan | 674 | 702 | named | named | survey | Findings from a ⟦Trader Survey in South Sudan⟧ | true | null | |
jdc_operational:000059 | 11 | 1 | Economic Survey 2016 | 1,901 | 1,921 | named | named | report | Kenya National Bureau of Statistics, 2016. “⟦Economic Survey 2016⟧.” | true | null | |
jdc_operational:000059 | 11 | 2 | Economic Survey 2016 | 139 | 159 | named | named | report | Kenya National Bureau of Statistics, 2016. “⟦Economic Survey 2016⟧.” | true | null | |
jdc_operational:000059 | 16 | 1 | 2014 Sanitation Benchmarking report | 353 | 388 | named | named | report | The ⟦2014 Sanitation Benchmarking report⟧ ranked Wajir County 44 out of 47 on sanitation performance | true | null | |
jdc_operational:000059 | 16 | 1 | sanitation statistics | 1,462 | 1,483 | vague | vague | other | Although ⟦sanitation statistics⟧ do not exist for Dadaab and Fafi subcounties | true | null | |
jdc_operational:000059 | 19 | 0 | customer identification surveys | 1,268 | 1,299 | descriptive | descriptive | survey | including ⟦customer identification surveys⟧[1], improving billing and collection systems | true | null | |
jdc_operational:000059 | 24 | 0 | project-specific data | 2,006 | 2,027 | descriptive | descriptive | other | the implementing agencies, and from ⟦project-specific data⟧[2] | true | null | |
jdc_operational:000059 | 39 | 1 | WSP data | 658 | 666 | descriptive | descriptive | other | ⟦WSP data⟧[3] on connections | true | null | |
jdc_operational:000059 | 39 | 2 | county data | 321 | 332 | descriptive | descriptive | other | WSP and ⟦county data⟧[4] | true | null | |
jdc_operational:000059 | 40 | 2 | WSP data | 201 | 209 | descriptive | descriptive | other | ⟦WSP data⟧[5] on operations | true | null | |
jdc_operational:000059 | 42 | 1 | WSP data | 245 | 253 | descriptive | descriptive | other | ⟦WSP data⟧[6] | true | null | |
jdc_operational:000059 | 42 | 2 | WSP data | 168 | 176 | descriptive | descriptive | other | ⟦WSP data⟧[7] | true | null | |
jdc_operational:000059 | 43 | 0 | customer identification surveys | 947 | 978 | descriptive | descriptive | survey | including ⟦customer identification surveys⟧[8], improving billing and collection systems | true | null | |
jdc_operational:000059 | 45 | 0 | NRW data | 27 | 35 | descriptive | descriptive | other | Establish a baseline for ⟦NRW data⟧[9] for zones | true | null | |
jdc_operational:000059 | 45 | 0 | database for all the WSP networks | 124 | 157 | descriptive | descriptive | database | Create a ⟦database for all the WSP networks⟧[10] | true | null | |
jdc_operational:000059 | 47 | 1 | 2009 population census | 244 | 266 | named | named | census | According to the ⟦2009 population census⟧[11], Wajir town had a population of about 82,800 inhabitants | true | null | |
jdc_operational:000059 | 48 | 0 | 2014 Sanitation Benchmarking Report | 1,415 | 1,450 | named | named | report | The ⟦2014 Sanitation Benchmarking Report⟧[12] ranked Wajir 44 of 47 counties on sanitation performance | true | null | |
jdc_operational:000059 | 50 | 0 | 2014 Sanitation Benchmarking report | 1,248 | 1,283 | named | named | report | The ⟦2014 Sanitation Benchmarking report⟧[13] put the stunting rate in Garissa at approximately 50 percent | true | null | |
jdc_operational:000059 | 50 | 0 | sanitation statistics | 1,355 | 1,376 | vague | vague | other | Although ⟦sanitation statistics⟧[14] do not exist for Dadaab and Fafi subcounties | true | null | |
jdc_operational:000059 | 54 | 1 | Customer database | 537 | 554 | descriptive | descriptive | database | ⟦Customer database⟧[15] through ⟦customer identification survey⟧[16] and standard computerized systems | true | null | |
jdc_operational:000059 | 54 | 1 | customer identification survey | 563 | 593 | descriptive | descriptive | survey | Customer database through ⟦customer identification survey⟧[16] and standard computerized systems | true | null | |
jdc_operational:000059 | 57 | 0 | customer database | 1,800 | 1,817 | descriptive | descriptive | database | improvements in ⟦customer database⟧[17] and billing and collection efficiency | true | null | |
jdc_operational:000059 | 58 | 0 | customer identification survey | 289 | 319 | descriptive | descriptive | survey | Improving customer database through ⟦customer identification survey⟧[18] and/or standard computerized systems | true | null | |
jdc_operational:000059 | 5 | 1 | Project Financing Data | 142 | 164 | named | named | other | ⟦Project Financing Data⟧[19](in US$, Millions) | false | null | |
jdc_operational:000059 | 68 | 0 | fixed assets register | 1,464 | 1,485 | descriptive | descriptive | administrative | there is no complete ⟦fixed assets register⟧[20] | true | null | |
jdc_operational:000059 | 68 | 1 | Government exchequer requests systems | 567 | 604 | descriptive | descriptive | other | using the ⟦Government exchequer requests systems⟧[21] to a Special Purpose Account at the CBK | false | null | |
jdc_operational:000059 | 86 | 0 | national census | 1,630 | 1,645 | descriptive | descriptive | census | will come from the ⟦national census⟧[22] (most recently carried out in 2009) | true | null | |
jdc_operational:000059 | 86 | 1 | Data on operational performance of the WSPs | 9 | 52 | descriptive | descriptive | other | ⟦Data on operational performance of the WSPs⟧[23] will come from the WSPs themselves | true | null | |
jdc_operational:000060 | 2 | 1 | 2012 Jordan Investment Climate Survey | 524 | 561 | named | named | survey | The ⟦2012 Jordan Investment Climate Survey⟧[24] (ICS) shows the large disparities in terms of access to credit by size of firms | true | null | |
jdc_operational:000060 | 6 | 0 | complaints data | 2 | 17 | descriptive | vague | other | # ⟦complaints data⟧[25]. | true | null | |
jdc_operational:000060 | 6 | 1 | NBFI market study | 1,522 | 1,539 | descriptive | named | other | based on a ⟦NBFI market study⟧[26] | false | null | |
jdc_operational:000061 | 100 | 0 | information collected at water sites | 1,494 | 1,530 | descriptive | descriptive | other | Information on current prices paid for water needs was obtained from interviews with the population, information provided by community leaders, and ⟦information collected at water sites⟧[27] | true | null | |
jdc_operational:000061 | 100 | 1 | NSDS | 1,451 | 1,455 | named | named | survey | According to the ⟦NSDS⟧[28], the average amount of water fetched per household per day is 67 L | true | null | |
jdc_operational:000061 | 100 | 1 | NSDS | 1,652 | 1,656 | named | named | survey | Information from the ⟦NSDS⟧[29] indicated that the time spent walking and waiting in line varied from 29 | true | null | |
jdc_operational:000061 | 100 | 2 | NSDS | 61 | 65 | named | named | survey | Information from the ⟦NSDS⟧[30] indicated that the time spent walking and waiting in line varied from 29 | true | null | |
jdc_operational:000061 | 101 | 0 | NSDS | 539 | 543 | named | named | survey | current figures from the ⟦NSDS⟧[1] on the time spent fetching water | true | null | |
jdc_operational:000061 | 103 | 0 | reliable data | 1,210 | 1,223 | vague | vague | other | The UOs will collect ⟦reliable data⟧[2] to estimate tariffs | true | null | |
jdc_operational:000061 | 103 | 1 | reliable data on operating cost | 998 | 1,029 | descriptive | vague | other | a detailed financial evaluation will be conducted using ⟦reliable data on operating cost⟧[3] to determine the required tariffs | true | null | |
jdc_operational:000061 | 108 | 0 | financial reports of the Mbale water production system | 123 | 177 | descriptive | descriptive | report | Operating costs were based on ⟦financial reports of the Mbale water production system⟧[4] | true | null | |
jdc_operational:000061 | 109 | 0 | Financial figures from the NWSC | 1,543 | 1,574 | descriptive | descriptive | report | ⟦Financial figures from the NWSC⟧[5] show that revenue | true | null | |
jdc_operational:000061 | 109 | 1 | Financial figures from the NWSC | 226 | 257 | descriptive | descriptive | report | ⟦Financial figures from the NWSC⟧[6] show that revenue in Mbale will cover operating costs | true | null | |
jdc_operational:000061 | 109 | 1 | Financial figures of NWSC | 550 | 575 | descriptive | descriptive | report | > 59 ⟦Financial figures of NWSC⟧[7]. | true | null | |
jdc_operational:000061 | 112 | 1 | National Household Survey | 1,097 | 1,122 | named | named | survey | UBOS. ⟦National Household Survey⟧[8] 2016–2017. Page 106. | true | null | |
jdc_operational:000061 | 112 | 1 | NSDS 2016 | 1,219 | 1,228 | named | named | survey | ⟦NSDS 2016⟧[9]. 56 minutes corresponds to time spent in rural areas | true | null | |
jdc_operational:000061 | 115 | 0 | proxy data | 103 | 113 | vague | vague | other | ⟦proxy data⟧[10] of a pumping height of 10.36 m with a reasonable pumping efficiency of 75 percent were used | true | null | |
jdc_operational:000061 | 115 | 1 | on-site data | 306 | 318 | descriptive | vague | other | This ⟦on-site data⟧[11], however, were not available at the time of this analysis | true | null | |
jdc_operational:000061 | 118 | 2 | NWSC figures | 1,001 | 1,013 | named | descriptive | other | According to ⟦NWSC figures⟧[12], current tariffs cover production costs | true | null | |
jdc_operational:000061 | 120 | 0 | domestic consumer price index | 372 | 401 | descriptive | descriptive | indicator | automatic annual indexation against the ⟦domestic consumer price index⟧[13] (inflation) | true | null | |
jdc_operational:000061 | 120 | 0 | foreign price index | 430 | 449 | descriptive | descriptive | indicator | exchange rate, ⟦foreign price index⟧[14], and electricity tariffs | true | null | |
jdc_operational:000061 | 125 | 1 | NWSC data | 162 | 171 | named | descriptive | other | _Source:_ own calculations based on ⟦NWSC data⟧[15] | true | null | |
jdc_operational:000061 | 12 | 0 | Uganda Poverty Assessment Report | 1,778 | 1,810 | named | named | report | according to the ⟦Uganda Poverty Assessment Report⟧[16] (2016) | true | null | |
jdc_operational:000061 | 12 | 1 | Uganda Poverty Assessment Report | 109 | 141 | named | named | report | according to the ⟦Uganda Poverty Assessment Report⟧[17] (2016), in 2013 more than a third of Ugandans lived below the international extreme poverty line | true | null | |
jdc_operational:000061 | 13 | 0 | data from the United Nations High Commissioner for Refugees | 306 | 365 | named | descriptive | administrative | According to ⟦data from the United Nations High Commissioner for Refugees⟧[18] (UNHCR), Uganda had the highest number of new refugees | true | null | |
jdc_operational:000061 | 13 | 2 | National Population and Housing <u>Census | 610 | 651 | named | named | census | defined as urban centers by the UBOS’ ⟦National Population and Housing <u>Census⟧[19] (NPHC). | true | null | |
jdc_operational:000061 | 14 | 0 | National Water Resources Assessment | 1,944 | 1,979 | named | named | report | According to the ⟦National Water Resources Assessment⟧[20] (2013) | true | null | |
jdc_operational:000061 | 14 | 1 | National Water Resources Assessment | 272 | 307 | named | named | report | According to the ⟦National Water Resources Assessment⟧[21] (2013), only 2.8 percent of the internal renewable water resources are currently utilized | true | null | |
jdc_operational:000061 | 14 | 1 | 2015 climate diagnostic for Uganda | 493 | 527 | descriptive | named | report | A ⟦2015 climate diagnostic for Uganda⟧[22] showed that increased temperatures would produce higher levels of potential evapotranspiration | true | null | |
jdc_operational:000061 | 15 | 0 | United Nations Joint Monitoring Program | 568 | 607 | named | named | report | The ⟦United Nations Joint Monitoring Program⟧[23] reports that only 29 percent of the urban and 17 percent of the rural populations have access to individual improved sanitation facilities | true | null | |
jdc_operational:000061 | 15 | 1 | 2017 UNHCR WASH Gap Analysis | 1,804 | 1,832 | named | named | report | Per the ⟦2017 UNHCR WASH Gap Analysis⟧[24], sanitation coverage in the West Nile is about 34 percent | true | null | |
jdc_operational:000061 | 15 | 2 | 2017 UNHCR WASH Gap Analysis | 190 | 218 | named | named | report | Per the ⟦2017 UNHCR WASH Gap Analysis⟧[25], sanitation coverage in the West Nile is about 34 percent | true | null | |
jdc_operational:000061 | 16 | 0 | Financial data | 362 | 376 | vague | vague | other | ⟦Financial data⟧[26] indicate that the Northern Umbrella and the Midwestern Umbrella service 2,809 and 2,387 active connections | true | null | |
jdc_operational:000061 | 20 | 1 | Augmented Water Supply Study | 1,031 | 1,059 | named | named | other | implementing the recommendations from the ⟦Augmented Water Supply Study⟧[27] | false | null | |
jdc_operational:000061 | 23 | 0 | Rural Water and Sanitation Information System | 1,153 | 1,198 | named | named | system | Latin America on the ⟦Rural Water and Sanitation Information System⟧[28] | true | null | |
jdc_operational:000061 | 25 | 0 | key performance data | 185 | 205 | descriptive | vague | other | focus on ⟦key performance data⟧[1] from specific Project activities | true | null | |
jdc_operational:000061 | 2 | 0 | National Population and HousingCensus | 753 | 790 | named | named | census | |NPHC|=⟦National Population and HousingCensus⟧[2] | true | null | |
jdc_operational:000061 | 2 | 0 | National Service DeliverySurvey | 846 | 877 | named | named | survey | |NSDS|=⟦National Service DeliverySurvey⟧[3] | true | null | |
jdc_operational:000061 | 31 | 2 | procurement records | 111 | 130 | descriptive | descriptive | administrative | inadequate storage capacity for ⟦procurement records⟧[4] | true | null | |
jdc_operational:000061 | 35 | 0 | Beneficiary satisfaction surveys | 1,802 | 1,834 | descriptive | descriptive | survey | ⟦Beneficiary satisfaction surveys⟧[5], including a ⟦survey specifically for districts hosting refugees⟧[6], will be conducted | true | null | |
jdc_operational:000061 | 35 | 0 | survey specifically for districts hosting refugees | 1,848 | 1,898 | descriptive | descriptive | survey | including a ⟦survey specifically for districts hosting refugees⟧[6], will be conducted | true | null | |
jdc_operational:000061 | 39 | 0 | National Water information systems | 793 | 827 | named | descriptive | system | ⟦National Water information systems⟧[7] established and operationalized under the project | false | null | |
jdc_operational:000061 | 40 | 0 | MWE M&E system | 455 | 469 | named | named | system | Primary sources include: ⟦MWE M&E system⟧[8], ⟦NWSC Area performance reports⟧[9], ⟦Refugee Database⟧[10] and ⟦UPMiS⟧[11] | true | null | |
jdc_operational:000061 | 40 | 0 | NWSC Area performance reports | 471 | 500 | named | descriptive | report | Primary sources include: ⟦MWE M&E system⟧[8], ⟦NWSC Area performance reports⟧[9], ⟦Refugee Database⟧[10] and ⟦UPMiS⟧[11] | true | null | |
jdc_operational:000061 | 40 | 0 | Refugee Database | 502 | 518 | named | named | database | Primary sources include: ⟦MWE M&E system⟧[8], ⟦NWSC Area performance reports⟧[9], ⟦Refugee Database⟧[10] and ⟦UPMiS⟧[11] | true | null | |
jdc_operational:000061 | 40 | 0 | UPMiS | 526 | 531 | named | named | system | Primary sources include: ⟦MWE M&E system⟧[8], ⟦NWSC Area performance reports⟧[9], ⟦Refugee Database⟧[10] and ⟦UPMiS⟧[11] | true | null | |
jdc_operational:000061 | 40 | 0 | NWSC annual report | 655 | 673 | named | descriptive | report | Secondary sources include: MWE/DWD/DWRM progress reports, annual water and environments sector performance report and ⟦NWSC annual report⟧[12] | true | null | |
jdc_operational:000061 | 40 | 0 | Supply Atlas | 1,134 | 1,146 | named | named | database | Water ⟦Supply Atlas⟧[13] (database of water supply, functionality and distribution of all Uganda districts) | true | null | |
jdc_operational:000061 | 40 | 0 | refugee database | 1,257 | 1,273 | descriptive | descriptive | database | NWSC annual report and ⟦refugee database⟧[14] | true | null | |
jdc_operational:000061 | 41 | 0 | annual water & environments sector performance report | 401 | 454 | descriptive | descriptive | report | ⟦annual water & environments sector performance report⟧[15], Water ⟦Supply Atlas⟧[16] | true | null | |
jdc_operational:000061 | 41 | 0 | Supply Atlas | 465 | 477 | named | named | database | Water ⟦Supply Atlas⟧[16] (database of water supply, functionality and distribution of all Uganda districts) | true | null |
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